{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/architecture-search/papers/5","list_of":"/task/architecture-search","task":"Neural Architecture Search","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":5,"pages_in_order":20,"rows_per_page":100,"rows":[401,500],"of":1915,"counts":{"archive_papers_tagged":1915,"with_a_code_link":859,"where_syntology_ran_a_sample":243,"not_listed_spam_title":0,"listed":1915,"listed_where_code_ran":243,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":204,"every_run_a_failure_of_syntologys_instrument":39,"listed_with_a_run_with_no_instrument_failure":204,"listed_every_run_a_failure_of_syntologys_instrument":39,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/architecture-search","prev":"/task/architecture-search/papers/4","next":"/task/architecture-search/papers/6","papers":[{"url":"/paper/cross-task-neural-architecture-search-for-eeg","slug":"cross-task-neural-architecture-search-for-eeg","title":"Cross Task Neural Architecture Search for EEG Signal Classifications","date":"2022-10-01","arxiv_id":"2210.06298","repositories_listed":1,"syntology":null},{"url":"/paper/bayesft-bayesian-optimization-for-fault","slug":"bayesft-bayesian-optimization-for-fault","title":"BayesFT: Bayesian Optimization for Fault Tolerant Neural Network Architecture","date":"2022-09-30","arxiv_id":"2210.01795","repositories_listed":1,"syntology":null},{"url":"/paper/hyper-representations-as-generative-models","slug":"hyper-representations-as-generative-models","title":"Hyper-Representations as Generative Models: Sampling Unseen Neural Network Weights","date":"2022-09-29","arxiv_id":"2209.14733","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":2,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; every one of the 2 samples that ran constructed an object rather than computing a result","sample_list":"/paper/hyper-representations-as-generative-models#ran","syntology_url":"https://syntology.ai/paper/2209.14733","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2209.14733"}},"official":{"repos":["hsg-aiml/neurips_2022-generative_hyper_representations"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/structure-learning-of-quantum-embeddings","slug":"structure-learning-of-quantum-embeddings","title":"Automatic and effective discovery of quantum kernels","date":"2022-09-22","arxiv_id":"2209.11144","repositories_listed":1,"syntology":null},{"url":"/paper/naap-440-dataset-and-baseline-for-network","slug":"naap-440-dataset-and-baseline-for-network","title":"NAAP-440 Dataset and Baseline for Neural Architecture Accuracy Prediction","date":"2022-09-14","arxiv_id":"2209.06626","repositories_listed":1,"syntology":null},{"url":"/paper/3dlanenas-neural-architecture-search-for","slug":"3dlanenas-neural-architecture-search-for","title":"3DLaneNAS: Neural Architecture Search for Accurate and Light-Weight 3D Lane Detection","date":"2022-09-06","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/on-the-privacy-risks-of-cell-based-nas","slug":"on-the-privacy-risks-of-cell-based-nas","title":"On the Privacy Risks of Cell-Based NAS Architectures","date":"2022-09-04","arxiv_id":"2209.01688","repositories_listed":1,"syntology":null},{"url":"/paper/you-only-search-once-on-lightweight","slug":"you-only-search-once-on-lightweight","title":"You Only Search Once: On Lightweight Differentiable Architecture Search for Resource-Constrained Embedded Platforms","date":"2022-08-30","arxiv_id":"2208.14446","repositories_listed":1,"syntology":null},{"url":"/paper/bayesian-neural-network-language-modeling-for","slug":"bayesian-neural-network-language-modeling-for","title":"Bayesian Neural Network Language Modeling for Speech Recognition","date":"2022-08-28","arxiv_id":"2208.13259","repositories_listed":1,"syntology":null},{"url":"/paper/learn-basic-skills-and-reuse-modularized","slug":"learn-basic-skills-and-reuse-modularized","title":"Learn Basic Skills and Reuse: Modularized Adaptive Neural Architecture Search (MANAS)","date":"2022-08-23","arxiv_id":"2208.11083","repositories_listed":1,"syntology":{"n":6,"n_ran":6,"n_constructed":0,"n_ran_checked":6,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"6 ran (of which 0 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/learn-basic-skills-and-reuse-modularized#ran","syntology_url":"https://syntology.ai/paper/2208.11083","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2208.11083"}},"official":{"repos":["taloncb/manas"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/zoomnas-searching-for-whole-body-human-pose","slug":"zoomnas-searching-for-whole-body-human-pose","title":"ZoomNAS: Searching for Whole-body Human Pose Estimation in the Wild","date":"2022-08-23","arxiv_id":"2208.11547","repositories_listed":1,"syntology":null},{"url":"/paper/svd-nas-coupling-low-rank-approximation-and","slug":"svd-nas-coupling-low-rank-approximation-and","title":"SVD-NAS: Coupling Low-Rank Approximation and Neural Architecture Search","date":"2022-08-22","arxiv_id":"2208.10404","repositories_listed":1,"syntology":null},{"url":"/paper/grato-graph-neural-network-framework-tackling","slug":"grato-graph-neural-network-framework-tackling","title":"GraTO: Graph Neural Network Framework Tackling Over-smoothing with Neural Architecture Search","date":"2022-08-18","arxiv_id":"2208.09027","repositories_listed":1,"syntology":null},{"url":"/paper/obfunas-a-neural-architecture-search-based","slug":"obfunas-a-neural-architecture-search-based","title":"ObfuNAS: A Neural Architecture Search-based DNN Obfuscation Approach","date":"2022-08-17","arxiv_id":"2208.08569","repositories_listed":1,"syntology":{"n":6,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/obfunas-a-neural-architecture-search-based#ran","syntology_url":"https://syntology.ai/paper/2208.08569","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2208.08569"}},"official":{"repos":["tongzhou0101/obfunas"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/tackling-neural-architecture-search-with","slug":"tackling-neural-architecture-search-with","title":"Tackling Neural Architecture Search With Quality Diversity Optimization","date":"2022-07-30","arxiv_id":"2208.00204","repositories_listed":1,"syntology":null},{"url":"/paper/albench-a-framework-for-evaluating-active","slug":"albench-a-framework-for-evaluating-active","title":"ALBench: A Framework for Evaluating Active Learning in Object Detection","date":"2022-07-27","arxiv_id":"2207.13339","repositories_listed":1,"syntology":null},{"url":"/paper/compiler-aware-neural-architecture-search-for","slug":"compiler-aware-neural-architecture-search-for","title":"Compiler-Aware Neural Architecture Search for On-Mobile Real-time Super-Resolution","date":"2022-07-25","arxiv_id":"2207.12577","repositories_listed":1,"syntology":{"n":6,"n_ran":5,"n_constructed":4,"n_ran_checked":4,"n_instrument":1,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":4,"n_pointer_only":6,"phrase":"5 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/compiler-aware-neural-architecture-search-for#ran","syntology_url":"https://syntology.ai/paper/2207.12577","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.12577"}},"official":{"repos":["wuyushuwys/compiler-aware-nas-sr"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/hyper-representations-for-pre-training-and","slug":"hyper-representations-for-pre-training-and","title":"Hyper-Representations for Pre-Training and Transfer Learning","date":"2022-07-22","arxiv_id":"2207.10951","repositories_listed":1,"syntology":null},{"url":"/paper/easnet-searching-elastic-and-accurate-network","slug":"easnet-searching-elastic-and-accurate-network","title":"EASNet: Searching Elastic and Accurate Network Architecture for Stereo Matching","date":"2022-07-20","arxiv_id":"2207.09796","repositories_listed":1,"syntology":null},{"url":"/paper/improving-neural-architecture-search-by","slug":"improving-neural-architecture-search-by","title":"Improving Neural Architecture Search by Mixing a FireFly algorithm with a Training Free Evaluation","date":"2022-07-18","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/close-curriculum-learning-on-the-sharing","slug":"close-curriculum-learning-on-the-sharing","title":"CLOSE: Curriculum Learning On the Sharing Extent Towards Better One-shot NAS","date":"2022-07-16","arxiv_id":"2207.07868","repositories_listed":1,"syntology":null},{"url":"/paper/pasha-efficient-hpo-with-progressive-resource","slug":"pasha-efficient-hpo-with-progressive-resource","title":"PASHA: Efficient HPO and NAS with Progressive Resource Allocation","date":"2022-07-14","arxiv_id":"2207.06940","repositories_listed":1,"syntology":{"n":8,"n_ran":3,"n_constructed":0,"n_ran_checked":1,"n_instrument":2,"n_unverified":5,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 5 unverified","sample_list":"/paper/pasha-efficient-hpo-with-progressive-resource#ran","syntology_url":"https://syntology.ai/paper/2207.06940","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.06940"}},"official":{"repos":["ondrejbohdal/pasha"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":5,"ran_from_kinds":["official"]}}},{"url":"/paper/graph-property-prediction-on-open-graph","slug":"graph-property-prediction-on-open-graph","title":"Graph Property Prediction on Open Graph Benchmark: A Winning Solution by Graph Neural Architecture Search","date":"2022-07-13","arxiv_id":"2207.06027","repositories_listed":1,"syntology":null},{"url":"/paper/mrf-unets-searching-unet-with-markov-random","slug":"mrf-unets-searching-unet-with-markov-random","title":"MRF-UNets: Searching UNet with Markov Random Fields","date":"2022-07-13","arxiv_id":"2207.06168","repositories_listed":1,"syntology":null},{"url":"/paper/long-term-reproducibility-for-neural","slug":"long-term-reproducibility-for-neural","title":"Long-term Reproducibility for Neural Architecture Search","date":"2022-07-11","arxiv_id":"2207.04821","repositories_listed":1,"syntology":null},{"url":"/paper/noisy-heuristics-nas-a-network-morphism-based","slug":"noisy-heuristics-nas-a-network-morphism-based","title":"Noisy Heuristics NAS: A Network Morphism based Neural Architecture Search using Heuristics","date":"2022-07-10","arxiv_id":"2207.04467","repositories_listed":1,"syntology":null},{"url":"/paper/supertickets-drawing-task-agnostic-lottery","slug":"supertickets-drawing-task-agnostic-lottery","title":"SuperTickets: Drawing Task-Agnostic Lottery Tickets from Supernets via Jointly Architecture Searching and Parameter Pruning","date":"2022-07-08","arxiv_id":"2207.03677","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":1,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","sample_list":"/paper/supertickets-drawing-task-agnostic-lottery#ran","syntology_url":"https://syntology.ai/paper/2207.03677","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2207.03677"}},"official":{"repos":["rice-eic/supertickets"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/betty-an-automatic-differentiation-library","slug":"betty-an-automatic-differentiation-library","title":"Betty: An Automatic Differentiation Library for Multilevel Optimization","date":"2022-07-05","arxiv_id":"2207.02849","repositories_listed":1,"syntology":null},{"url":"/paper/flownas-neural-architecture-search-for","slug":"flownas-neural-architecture-search-for","title":"FlowNAS: Neural Architecture Search for Optical Flow Estimation","date":"2022-07-04","arxiv_id":"2207.01271","repositories_listed":1,"syntology":null},{"url":"/paper/multi-scale-attentive-image-de-raining","slug":"multi-scale-attentive-image-de-raining","title":"Multi-scale Attentive Image De-raining Networks via Neural Architecture Search","date":"2022-07-02","arxiv_id":"2207.00728","repositories_listed":1,"syntology":null},{"url":"/paper/tree-ensemble-kernels-for-bayesian","slug":"tree-ensemble-kernels-for-bayesian","title":"Tree ensemble kernels for Bayesian optimization with known constraints over mixed-feature spaces","date":"2022-07-02","arxiv_id":"2207.00879","repositories_listed":1,"syntology":null},{"url":"/paper/multi-prior-learning-via-neural-architecture","slug":"multi-prior-learning-via-neural-architecture","title":"Multi-Prior Learning via Neural Architecture Search for Blind Face Restoration","date":"2022-06-28","arxiv_id":"2206.13962","repositories_listed":1,"syntology":null},{"url":"/paper/prior-guided-one-shot-neural-architecture","slug":"prior-guided-one-shot-neural-architecture","title":"Prior-Guided One-shot Neural Architecture Search","date":"2022-06-27","arxiv_id":"2206.13329","repositories_listed":1,"syntology":{"n":3,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/prior-guided-one-shot-neural-architecture#ran","syntology_url":"https://syntology.ai/paper/2206.13329","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.13329"}},"official":{"repos":["pprp/CVPR2022-NAS-competition-Track1-3th-solution"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/survival-kernets-scalable-and-interpretable","slug":"survival-kernets-scalable-and-interpretable","title":"Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee","date":"2022-06-21","arxiv_id":"2206.10477","repositories_listed":1,"syntology":null},{"url":"/paper/shapley-nas-discovering-operation-1","slug":"shapley-nas-discovering-operation-1","title":"Shapley-NAS: Discovering Operation Contribution for Neural Architecture Search","date":"2022-06-20","arxiv_id":"2206.09811","repositories_listed":1,"syntology":{"n":3,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":3,"phrase":"0 ran · 3 unverified","sample_list":"/paper/shapley-nas-discovering-operation-1#ran","syntology_url":"https://syntology.ai/paper/2206.09811","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.09811"}},"official":{"repos":["euphoria16/shapley-nas"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":[]}}},{"url":"/paper/nas-bench-graph-benchmarking-graph-neural","slug":"nas-bench-graph-benchmarking-graph-neural","title":"NAS-Bench-Graph: Benchmarking Graph Neural Architecture Search","date":"2022-06-18","arxiv_id":"2206.09166","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/nas-bench-graph-benchmarking-graph-neural#ran","syntology_url":"https://syntology.ai/paper/2206.09166","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.09166"}},"official":{"repos":["thumnlab/nas-bench-graph"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/channel-wise-mixed-precision-assignment-for","slug":"channel-wise-mixed-precision-assignment-for","title":"Channel-wise Mixed-precision Assignment for DNN Inference on Constrained Edge Nodes","date":"2022-06-17","arxiv_id":"2206.08852","repositories_listed":1,"syntology":null},{"url":"/paper/dfg-nas-deep-and-flexible-graph-neural","slug":"dfg-nas-deep-and-flexible-graph-neural","title":"DFG-NAS: Deep and Flexible Graph Neural Architecture Search","date":"2022-06-17","arxiv_id":"2206.08582","repositories_listed":1,"syntology":null},{"url":"/paper/freerea-training-free-evolution-based","slug":"freerea-training-free-evolution-based","title":"FreeREA: Training-Free Evolution-based Architecture Search","date":"2022-06-17","arxiv_id":"2207.05135","repositories_listed":1,"syntology":null},{"url":"/paper/emprox-neural-network-performance-estimation","slug":"emprox-neural-network-performance-estimation","title":"EmProx: Neural Network Performance Estimation For Neural Architecture Search","date":"2022-06-13","arxiv_id":"2206.05972","repositories_listed":1,"syntology":null},{"url":"/paper/improve-ranking-correlation-of-super-net","slug":"improve-ranking-correlation-of-super-net","title":"Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NAS","date":"2022-06-13","arxiv_id":"2206.05896","repositories_listed":1,"syntology":null},{"url":"/paper/neural-prompt-search","slug":"neural-prompt-search","title":"Neural Prompt Search","date":"2022-06-09","arxiv_id":"2206.04673","repositories_listed":1,"syntology":{"n":9,"n_ran":8,"n_constructed":0,"n_ran_checked":5,"n_instrument":3,"n_unverified":1,"n_honours":2,"n_violates":0,"n_no_contract":3,"n_pointer_only":2,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 2 honoured, 0 violated, 3 with no contract checked; 3 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/neural-prompt-search#ran","syntology_url":"https://syntology.ai/paper/2206.04673","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.04673"}},"official":{"repos":["ZhangYuanhan-AI/NOAH"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/towards-self-supervised-and-weight-preserving","slug":"towards-self-supervised-and-weight-preserving","title":"Towards Self-supervised and Weight-preserving Neural Architecture Search","date":"2022-06-08","arxiv_id":"2206.04125","repositories_listed":1,"syntology":null},{"url":"/paper/agnas-attention-guided-micro-and-macro","slug":"agnas-attention-guided-micro-and-macro","title":"AGNAS: Attention-Guided Micro- and Macro-Architecture Search","date":"2022-06-05","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/supernet-training-for-federated-image","slug":"supernet-training-for-federated-image","title":"Supernet Training for Federated Image Classification under System Heterogeneity","date":"2022-06-03","arxiv_id":"2206.01366","repositories_listed":1,"syntology":{"n":4,"n_ran":1,"n_constructed":0,"n_ran_checked":0,"n_instrument":1,"n_unverified":3,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/supernet-training-for-federated-image#ran","syntology_url":"https://syntology.ai/paper/2206.01366","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.01366"}},"official":{"repos":["Kthyeon/fedsup"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/pruning-as-search-efficient-neural","slug":"pruning-as-search-efficient-neural","title":"Pruning-as-Search: Efficient Neural Architecture Search via Channel Pruning and Structural Reparameterization","date":"2022-06-02","arxiv_id":"2206.01198","repositories_listed":1,"syntology":{"n":1,"n_ran":0,"n_constructed":0,"n_ran_checked":0,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":1,"phrase":"0 ran · 1 unverified","sample_list":"/paper/pruning-as-search-efficient-neural#ran","syntology_url":"https://syntology.ai/paper/2206.01198","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2206.01198"}},"official":null}},{"url":"/paper/multi-complexity-loss-dnas-for-energy","slug":"multi-complexity-loss-dnas-for-energy","title":"Multi-Complexity-Loss DNAS for Energy-Efficient and Memory-Constrained Deep Neural Networks","date":"2022-06-01","arxiv_id":"2206.00302","repositories_listed":1,"syntology":null},{"url":"/paper/automatic-relation-aware-graph-network","slug":"automatic-relation-aware-graph-network","title":"Automatic Relation-aware Graph Network Proliferation","date":"2022-05-31","arxiv_id":"2205.15678","repositories_listed":1,"syntology":null},{"url":"/paper/a-classification-of-g-invariant-shallow","slug":"a-classification-of-g-invariant-shallow","title":"A Classification of $G$-invariant Shallow Neural Networks","date":"2022-05-18","arxiv_id":"2205.09219","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":0,"n_instrument":2,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":0,"n_pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/a-classification-of-g-invariant-shallow#ran","syntology_url":"https://syntology.ai/paper/2205.09219","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.09219"}},"official":{"repos":["dagrawa2/gsnn_classification_code"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/autoke-an-automatic-knowledge-embedding","slug":"autoke-an-automatic-knowledge-embedding","title":"AutoKE: An automatic knowledge embedding framework for scientific machine learning","date":"2022-05-11","arxiv_id":"2205.05390","repositories_listed":1,"syntology":null},{"url":"/paper/autolc-search-lightweight-and-top-performing","slug":"autolc-search-lightweight-and-top-performing","title":"AutoLC: Search Lightweight and Top-Performing Architecture for Remote Sensing Image Land-Cover Classification","date":"2022-05-11","arxiv_id":"2205.05369","repositories_listed":1,"syntology":null},{"url":"/paper/efficient-automated-deep-learning-for-time","slug":"efficient-automated-deep-learning-for-time","title":"Efficient Automated Deep Learning for Time Series Forecasting","date":"2022-05-11","arxiv_id":"2205.05511","repositories_listed":1,"syntology":{"n":2,"n_ran":2,"n_constructed":0,"n_ran_checked":2,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/efficient-automated-deep-learning-for-time#ran","syntology_url":"https://syntology.ai/paper/2205.05511","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.05511"}},"official":{"repos":["automl/Auto-PyTorch"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/a-nas-neural-architecture-search-using","slug":"a-nas-neural-architecture-search-using","title":"Neural Architecture Search using Property Guided Synthesis","date":"2022-05-08","arxiv_id":"2205.03960","repositories_listed":1,"syntology":null},{"url":"/paper/gait-recognition-in-the-wild-a-benchmark-1","slug":"gait-recognition-in-the-wild-a-benchmark-1","title":"Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline","date":"2022-05-05","arxiv_id":"2205.02692","repositories_listed":1,"syntology":null},{"url":"/paper/gpunet-searching-the-deployable-convolution","slug":"gpunet-searching-the-deployable-convolution","title":"GPUNet: Searching the Deployable Convolution Neural Networks for GPUs","date":"2022-04-26","arxiv_id":"2205.00841","repositories_listed":1,"syntology":null},{"url":"/paper/adaptive-hybrid-activation-function-for-deep","slug":"adaptive-hybrid-activation-function-for-deep","title":"Adaptive hybrid activation function for deep neural networks","date":"2022-04-25","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/spidernet-hybrid-differentiable-evolutionary","slug":"spidernet-hybrid-differentiable-evolutionary","title":"SpiderNet: Hybrid Differentiable-Evolutionary Architecture Search via Train-Free Metrics","date":"2022-04-20","arxiv_id":"2204.09320","repositories_listed":1,"syntology":null},{"url":"/paper/deepcore-a-comprehensive-library-for-coreset","slug":"deepcore-a-comprehensive-library-for-coreset","title":"DeepCore: A Comprehensive Library for Coreset Selection in Deep Learning","date":"2022-04-18","arxiv_id":"2204.08499","repositories_listed":1,"syntology":null},{"url":"/paper/efficient-architecture-search-for-diverse","slug":"efficient-architecture-search-for-diverse","title":"Efficient Architecture Search for Diverse Tasks","date":"2022-04-15","arxiv_id":"2204.07554","repositories_listed":1,"syntology":null},{"url":"/paper/resource-constrained-neural-architecture","slug":"resource-constrained-neural-architecture","title":"TabNAS: Rejection Sampling for Neural Architecture Search on Tabular Datasets","date":"2022-04-15","arxiv_id":"2204.07615","repositories_listed":1,"syntology":null},{"url":"/paper/arch-graph-acyclic-architecture-relation","slug":"arch-graph-acyclic-architecture-relation","title":"Arch-Graph: Acyclic Architecture Relation Predictor for Task-Transferable Neural Architecture Search","date":"2022-04-12","arxiv_id":"2204.05941","repositories_listed":1,"syntology":null},{"url":"/paper/when-nas-meets-trees-an-efficient-algorithm","slug":"when-nas-meets-trees-an-efficient-algorithm","title":"When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search","date":"2022-04-11","arxiv_id":"2204.04918","repositories_listed":1,"syntology":null},{"url":"/paper/bridging-the-gap-of-autograph-between","slug":"bridging-the-gap-of-autograph-between","title":"Bridging the Gap of AutoGraph between Academia and Industry: Analysing AutoGraph Challenge at KDD Cup 2020","date":"2022-04-06","arxiv_id":"2204.02625","repositories_listed":1,"syntology":null},{"url":"/paper/i-razor-a-neural-input-razor-for-feature","slug":"i-razor-a-neural-input-razor-for-feature","title":"i-Razor: A Differentiable Neural Input Razor for Feature Selection and Dimension Search in DNN-Based Recommender Systems","date":"2022-04-01","arxiv_id":"2204.00281","repositories_listed":1,"syntology":null},{"url":"/paper/novelty-driven-evolutionary-neural","slug":"novelty-driven-evolutionary-neural","title":"Novelty Driven Evolutionary Neural Architecture Search","date":"2022-04-01","arxiv_id":"2204.00188","repositories_listed":1,"syntology":null},{"url":"/paper/generalizing-few-shot-nas-with-gradient-1","slug":"generalizing-few-shot-nas-with-gradient-1","title":"Generalizing Few-Shot NAS with Gradient Matching","date":"2022-03-29","arxiv_id":"2203.15207","repositories_listed":1,"syntology":{"n":7,"n_ran":3,"n_constructed":0,"n_ran_checked":3,"n_instrument":0,"n_unverified":4,"n_honours":0,"n_violates":0,"n_no_contract":3,"n_pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","sample_list":"/paper/generalizing-few-shot-nas-with-gradient-1#ran","syntology_url":"https://syntology.ai/paper/2203.15207","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.15207"}},"official":{"repos":["skhu101/GM-NAS"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":4,"ran_from_kinds":["official"]}}},{"url":"/paper/nix-tts-an-incredibly-lightweight-end-to-end","slug":"nix-tts-an-incredibly-lightweight-end-to-end","title":"Nix-TTS: Lightweight and End-to-End Text-to-Speech via Module-wise Distillation","date":"2022-03-29","arxiv_id":"2203.15643","repositories_listed":1,"syntology":null},{"url":"/paper/demystifying-the-neural-tangent-kernel-from-a","slug":"demystifying-the-neural-tangent-kernel-from-a","title":"Demystifying the Neural Tangent Kernel from a Practical Perspective: Can it be trusted for Neural Architecture Search without training?","date":"2022-03-28","arxiv_id":"2203.14577","repositories_listed":1,"syntology":null},{"url":"/paper/a-semi-decoupled-approach-to-fast-and-optimal","slug":"a-semi-decoupled-approach-to-fast-and-optimal","title":"A Semi-Decoupled Approach to Fast and Optimal Hardware-Software Co-Design of Neural Accelerators","date":"2022-03-25","arxiv_id":"2203.13921","repositories_listed":1,"syntology":null},{"url":"/paper/q-ppg-energy-efficient-ppg-based-heart-rate","slug":"q-ppg-energy-efficient-ppg-based-heart-rate","title":"Q-PPG: Energy-Efficient PPG-based Heart Rate Monitoring on Wearable Devices","date":"2022-03-24","arxiv_id":"2203.14907","repositories_listed":1,"syntology":null},{"url":"/paper/u-boost-nas-utilization-boosted-1","slug":"u-boost-nas-utilization-boosted-1","title":"U-Boost NAS: Utilization-Boosted Differentiable Neural Architecture Search","date":"2022-03-23","arxiv_id":"2203.12412","repositories_listed":1,"syntology":null},{"url":"/paper/pace-a-parallelizable-computation-encoder-for-1","slug":"pace-a-parallelizable-computation-encoder-for-1","title":"PACE: A Parallelizable Computation Encoder for Directed Acyclic Graphs","date":"2022-03-19","arxiv_id":"2203.10304","repositories_listed":1,"syntology":{"n":1,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/pace-a-parallelizable-computation-encoder-for-1#ran","syntology_url":"https://syntology.ai/paper/2203.10304","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.10304"}},"official":{"repos":["zehao-dong/pace"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/data-domain-aware-and-task-aware-pre-training","slug":"data-domain-aware-and-task-aware-pre-training","title":"DATA: Domain-Aware and Task-Aware Self-supervised Learning","date":"2022-03-17","arxiv_id":"2203.09041","repositories_listed":1,"syntology":{"n":2,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/data-domain-aware-and-task-aware-pre-training#ran","syntology_url":"https://syntology.ai/paper/2203.09041","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.09041"}},"official":{"repos":["gaia-vision/gaia-ssl"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/global-convergence-of-maml-and-theory","slug":"global-convergence-of-maml-and-theory","title":"Global Convergence of MAML and Theory-Inspired Neural Architecture Search for Few-Shot Learning","date":"2022-03-17","arxiv_id":"2203.09137","repositories_listed":1,"syntology":{"n":4,"n_ran":4,"n_constructed":0,"n_ran_checked":1,"n_instrument":3,"n_unverified":0,"n_honours":0,"n_violates":1,"n_no_contract":0,"n_pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 1 violated, 0 with no contract checked; 3 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/global-convergence-of-maml-and-theory#ran","syntology_url":"https://syntology.ai/paper/2203.09137","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.09137"}},"official":{"repos":["yitewang/metantk-nas"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/progressive-subsampling-for-oversampled-data","slug":"progressive-subsampling-for-oversampled-data","title":"Progressive Subsampling for Oversampled Data -- Application to Quantitative MRI","date":"2022-03-17","arxiv_id":"2203.09268","repositories_listed":1,"syntology":null},{"url":"/paper/learning-where-to-look-generative-nas-is","slug":"learning-where-to-look-generative-nas-is","title":"Learning Where To Look -- Generative NAS is Surprisingly Efficient","date":"2022-03-16","arxiv_id":"2203.08734","repositories_listed":1,"syntology":{"n":15,"n_ran":8,"n_constructed":5,"n_ran_checked":6,"n_instrument":2,"n_unverified":7,"n_honours":0,"n_violates":0,"n_no_contract":6,"n_pointer_only":0,"phrase":"8 ran (of which 5 constructed an object rather than computing a result; 6 with no instrument failure: 0 honoured, 0 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 7 unverified","sample_list":"/paper/learning-where-to-look-generative-nas-is#ran","syntology_url":"https://syntology.ai/paper/2203.08734","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.08734"}},"official":{"repos":["jovitalukasik/AG-Net"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":5,"n_ran_no_instrument_failure":6,"n_unverified":7,"ran_from_kinds":["official"]}}},{"url":"/paper/less-is-more-proxy-datasets-in-nas-approaches","slug":"less-is-more-proxy-datasets-in-nas-approaches","title":"Less is More: Proxy Datasets in NAS approaches","date":"2022-03-14","arxiv_id":"2203.06905","repositories_listed":1,"syntology":null},{"url":"/paper/tas-ternarized-neural-architecture-search-for","slug":"tas-ternarized-neural-architecture-search-for","title":"TAS: Ternarized Neural Architecture Search for Resource-Constrained Edge Devices","date":"2022-03-14","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/towards-less-constrained-macro-neural","slug":"towards-less-constrained-macro-neural","title":"Towards Less Constrained Macro-Neural Architecture Search","date":"2022-03-10","arxiv_id":"2203.05508","repositories_listed":1,"syntology":null},{"url":"/paper/evolutionary-neural-cascade-search-across","slug":"evolutionary-neural-cascade-search-across","title":"Evolutionary Neural Cascade Search across Supernetworks","date":"2022-03-08","arxiv_id":"2203.04011","repositories_listed":1,"syntology":null},{"url":"/paper/adaptive-cross-layer-attention-for-image-1","slug":"adaptive-cross-layer-attention-for-image-1","title":"Adaptive Cross-Layer Attention for Image Restoration","date":"2022-03-04","arxiv_id":"2203.03619","repositories_listed":1,"syntology":{"n":5,"n_ran":4,"n_constructed":0,"n_ran_checked":2,"n_instrument":2,"n_unverified":1,"n_honours":0,"n_violates":0,"n_no_contract":2,"n_pointer_only":1,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 2 where Syntology's instrument failed) · 1 unverified","sample_list":"/paper/adaptive-cross-layer-attention-for-image-1#ran","syntology_url":"https://syntology.ai/paper/2203.03619","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.03619"}},"official":{"repos":["sdl-asu/acla"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"url":"/paper/litetransformersearch-training-free-on-device","slug":"litetransformersearch-training-free-on-device","title":"LiteTransformerSearch: Training-free Neural Architecture Search for Efficient Language Models","date":"2022-03-04","arxiv_id":"2203.02094","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":5,"n_instrument":0,"n_unverified":0,"n_honours":0,"n_violates":0,"n_no_contract":5,"n_pointer_only":1,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/litetransformersearch-training-free-on-device#ran","syntology_url":"https://syntology.ai/paper/2203.02094","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2203.02094"}},"official":{"repos":["microsoft/archai"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/b-darts-beta-decay-regularization-for","slug":"b-darts-beta-decay-regularization-for","title":"$β$-DARTS: Beta-Decay Regularization for Differentiable Architecture Search","date":"2022-03-03","arxiv_id":"2203.01665","repositories_listed":1,"syntology":null},{"url":"/paper/neural-architecture-search-using-progressive","slug":"neural-architecture-search-using-progressive","title":"Neural Architecture Search using Progressive Evolution","date":"2022-03-03","arxiv_id":"2203.01559","repositories_listed":1,"syntology":null},{"url":"/paper/pasca-a-graph-neural-architecture-search","slug":"pasca-a-graph-neural-architecture-search","title":"PaSca: a Graph Neural Architecture Search System under the Scalable Paradigm","date":"2022-03-01","arxiv_id":"2203.00638","repositories_listed":1,"syntology":null},{"url":"/paper/an-efficient-end-to-end-3d-model","slug":"an-efficient-end-to-end-3d-model","title":"An Efficient End-to-End 3D Voxel Reconstruction based on Neural Architecture Search","date":"2022-02-27","arxiv_id":"2202.13313","repositories_listed":1,"syntology":null},{"url":"/paper/bayesian-model-selection-the-marginal","slug":"bayesian-model-selection-the-marginal","title":"Bayesian Model Selection, the Marginal Likelihood, and Generalization","date":"2022-02-23","arxiv_id":"2202.11678","repositories_listed":1,"syntology":{"n":5,"n_ran":5,"n_constructed":0,"n_ran_checked":1,"n_instrument":4,"n_unverified":0,"n_honours":1,"n_violates":0,"n_no_contract":0,"n_pointer_only":0,"phrase":"5 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","sample_list":"/paper/bayesian-model-selection-the-marginal#ran","syntology_url":"https://syntology.ai/paper/2202.11678","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2202.11678"}},"official":{"repos":["sanaelotfi/bayesian_model_comparison"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"url":"/paper/b2ea-an-evolutionary-algorithm-assisted-by","slug":"b2ea-an-evolutionary-algorithm-assisted-by","title":"B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture Search","date":"2022-02-07","arxiv_id":"2202.03005","repositories_listed":1,"syntology":null},{"url":"/paper/nas-bench-suite-nas-evaluation-is-now-1","slug":"nas-bench-suite-nas-evaluation-is-now-1","title":"NAS-Bench-Suite: NAS Evaluation is (Now) Surprisingly Easy","date":"2022-01-31","arxiv_id":"2201.13396","repositories_listed":1,"syntology":null},{"url":"/paper/autosnn-towards-energy-efficient-spiking","slug":"autosnn-towards-energy-efficient-spiking","title":"AutoSNN: Towards Energy-Efficient Spiking Neural Networks","date":"2022-01-30","arxiv_id":"2201.12738","repositories_listed":1,"syntology":{"n":3,"n_ran":1,"n_constructed":0,"n_ran_checked":1,"n_instrument":0,"n_unverified":2,"n_honours":0,"n_violates":0,"n_no_contract":1,"n_pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","sample_list":"/paper/autosnn-towards-energy-efficient-spiking#ran","syntology_url":"https://syntology.ai/paper/2201.12738","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.12738"}},"official":{"repos":["nabk89/autosnn"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"url":"/paper/neural-architecture-ranker","slug":"neural-architecture-ranker","title":"Generalized Global Ranking-Aware Neural Architecture Ranker for Efficient Image Classifier Search","date":"2022-01-30","arxiv_id":"2201.12725","repositories_listed":1,"syntology":null},{"url":"/paper/dropnas-grouped-operation-dropout-for","slug":"dropnas-grouped-operation-dropout-for","title":"DropNAS: Grouped Operation Dropout for Differentiable Architecture Search","date":"2022-01-27","arxiv_id":"2201.11679","repositories_listed":1,"syntology":null},{"url":"/paper/part-parallel-learning-towards-robust-and","slug":"part-parallel-learning-towards-robust-and","title":"PaRT: Parallel Learning Towards Robust and Transparent AI","date":"2022-01-24","arxiv_id":"2201.09534","repositories_listed":1,"syntology":null},{"url":"/paper/unifying-and-boosting-gradient-based-training","slug":"unifying-and-boosting-gradient-based-training","title":"Unifying and Boosting Gradient-Based Training-Free Neural Architecture Search","date":"2022-01-24","arxiv_id":"2201.09785","repositories_listed":1,"syntology":{"n":7,"n_ran":4,"n_constructed":2,"n_ran_checked":3,"n_instrument":1,"n_unverified":3,"n_honours":1,"n_violates":0,"n_no_contract":2,"n_pointer_only":7,"phrase":"4 ran (of which 2 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","sample_list":"/paper/unifying-and-boosting-gradient-based-training#ran","syntology_url":"https://syntology.ai/paper/2201.09785","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2201.09785"}},"official":{"repos":["shuyao95/HNAS"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":2,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"url":"/paper/neural-architecture-search-for-spiking-neural","slug":"neural-architecture-search-for-spiking-neural","title":"Neural Architecture Search for Spiking Neural Networks","date":"2022-01-23","arxiv_id":"2201.10355","repositories_listed":1,"syntology":null},{"url":"/paper/nas-vad-neural-architecture-search-for-voice","slug":"nas-vad-neural-architecture-search-for-voice","title":"NAS-VAD: Neural Architecture Search for Voice Activity Detection","date":"2022-01-22","arxiv_id":"2201.09032","repositories_listed":1,"syntology":null},{"url":"/paper/neural-architecture-search-for-lf-mmi-trained","slug":"neural-architecture-search-for-lf-mmi-trained","title":"Neural Architecture Search For LF-MMI Trained Time Delay Neural Networks","date":"2022-01-08","arxiv_id":"2201.03943","repositories_listed":1,"syntology":null},{"url":"/paper/automated-graph-machine-learning-approaches","slug":"automated-graph-machine-learning-approaches","title":"Automated Graph Machine Learning: Approaches, Libraries, Benchmarks and Directions","date":"2022-01-04","arxiv_id":"2201.01288","repositories_listed":1,"syntology":null},{"url":"/paper/b-darts-beta-decay-regularization-for-1","slug":"b-darts-beta-decay-regularization-for-1","title":"b-DARTS: Beta-Decay Regularization for Differentiable Architecture Search","date":"2022-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null},{"url":"/paper/neural-architecture-search-with","slug":"neural-architecture-search-with","title":"Neural Architecture Search With Representation Mutual Information","date":"2022-01-01","arxiv_id":null,"repositories_listed":1,"syntology":null}],"record_sha256":"c00dd1fdcfa8c61076efd310463170368eba112c3943651d5d99a435676a0a01","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}