{"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":"/method/base/papers/46","list_of":"/method/base","method":"BASE","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":46,"pages_in_order":58,"rows_per_page":100,"rows":[4501,4600],"of":5784,"counts":{"archive_papers_tagged":5784,"with_a_code_link":1913,"where_syntology_ran_a_sample":621,"not_listed_spam_title":0,"listed":5784,"listed_where_code_ran":621,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":523,"every_run_a_failure_of_syntologys_instrument":98,"listed_with_a_run_with_no_instrument_failure":523,"listed_every_run_a_failure_of_syntologys_instrument":98,"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":"/method/base","prev":"/method/base/papers/45","next":"/method/base/papers/47","papers":[{"paper":null,"slug":"a-robust-multilabel-method-integrating-rule","title":"A Robust Multilabel Method Integrating Rule-based Transparent Model, Soft Label Correlation Learning and Label Noise Resistance","date":"2023-01-09","arxiv_id":"2301.03283","n_code_links":0,"syntology":null},{"paper":null,"slug":"instance-segmentation-based-graph-extraction","title":"Instance Segmentation Based Graph Extraction for Handwritten Circuit Diagram Images","date":"2023-01-09","arxiv_id":"2301.03155","n_code_links":0,"syntology":null},{"paper":null,"slug":"leveraging-contextual-relatedness-to-identify","title":"Leveraging Contextual Relatedness to Identify Suicide Documentation in Clinical Notes through Zero Shot Learning","date":"2023-01-09","arxiv_id":"2301.03531","n_code_links":0,"syntology":null},{"paper":null,"slug":"machining-feature-recognition-using","title":"Machining feature recognition using descriptors with range constraints for mechanical 3D models","date":"2023-01-09","arxiv_id":"2301.03167","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-uav-path-learning-for-age-and-power","title":"Multi-UAV Path Learning for Age and Power Optimization in IoT with UAV Battery Recharge","date":"2023-01-09","arxiv_id":"2301.03423","n_code_links":0,"syntology":null},{"paper":null,"slug":"hierarchical-reinforcement-learning-for-ris","title":"Hierarchical Reinforcement Learning for RIS-Assisted Energy-Efficient RAN","date":"2023-01-07","arxiv_id":"2301.02771","n_code_links":0,"syntology":null},{"paper":null,"slug":"three-efficient-beamforming-methods-for","title":"Two Efficient Beamforming Methods for Hybrid IRS-aided AF Relay Wireless Networks","date":"2023-01-07","arxiv_id":"2301.02858","n_code_links":0,"syntology":null},{"paper":null,"slug":"algorithm-unrolling-based-distributed","title":"Algorithm Unrolling-Based Distributed Optimization for RIS-Assisted Cell-Free Networks","date":"2023-01-06","arxiv_id":"2301.02360","n_code_links":0,"syntology":null},{"paper":null,"slug":"co-channel-interference-management-for-the","title":"Co-channel Interference Management for the Next-Generation Heterogeneous Networks using Deep Leaning","date":"2023-01-06","arxiv_id":"2301.10177","n_code_links":0,"syntology":null},{"paper":"/paper/exploring-efficient-few-shot-adaptation-for","slug":"exploring-efficient-few-shot-adaptation-for","title":"Exploring Efficient Few-shot Adaptation for Vision Transformers","date":"2023-01-06","arxiv_id":"2301.02419","n_code_links":1,"syntology":null},{"paper":null,"slug":"spectrum-monitoring-and-analysis-in-urban-and","title":"Spectrum Monitoring and Analysis in Urban and Rural Environments at Different Altitudes","date":"2023-01-06","arxiv_id":"2301.02380","n_code_links":0,"syntology":null},{"paper":"/paper/topics-as-entity-clusters-entity-based-topics","slug":"topics-as-entity-clusters-entity-based-topics","title":"Topics as Entity Clusters: Entity-based Topics from Large Language Models and Graph Neural Networks","date":"2023-01-06","arxiv_id":"2301.02458","n_code_links":1,"syntology":null},{"paper":null,"slug":"domain-generalization-via-ensemble-stacking","title":"Domain Generalization via Ensemble Stacking for Face Presentation Attack Detection","date":"2023-01-05","arxiv_id":"2301.02145","n_code_links":0,"syntology":null},{"paper":"/paper/extending-source-code-pre-trained-language","slug":"extending-source-code-pre-trained-language","title":"Extending Source Code Pre-Trained Language Models to Summarise Decompiled Binaries","date":"2023-01-04","arxiv_id":"2301.01701","n_code_links":1,"syntology":null},{"paper":null,"slug":"object-segmentation-with-audio-context","title":"Object Segmentation with Audio Context","date":"2023-01-04","arxiv_id":"2301.10295","n_code_links":0,"syntology":null},{"paper":"/paper/analogical-inference-enhanced-knowledge-graph","slug":"analogical-inference-enhanced-knowledge-graph","title":"Analogical Inference Enhanced Knowledge Graph Embedding","date":"2023-01-03","arxiv_id":"2301.00982","n_code_links":1,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"0 ran · 2 unverified","official":{"repos":["zjukg/ankge"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":[]}}},{"paper":null,"slug":"frequency-aware-learned-image-compression-for","title":"Frequency-aware Learned Image Compression for Quality Scalability","date":"2023-01-03","arxiv_id":"2301.01290","n_code_links":0,"syntology":null},{"paper":null,"slug":"lunarnav-crater-based-localization-for-long","title":"LunarNav: Crater-based Localization for Long-range Autonomous Lunar Rover Navigation","date":"2023-01-03","arxiv_id":"2301.01350","n_code_links":0,"syntology":null},{"paper":"/paper/reference-twice-a-simple-and-unified-baseline","slug":"reference-twice-a-simple-and-unified-baseline","title":"Reference Twice: A Simple and Unified Baseline for Few-Shot Instance Segmentation","date":"2023-01-03","arxiv_id":"2301.01156","n_code_links":1,"syntology":null},{"paper":"/paper/tinymim-an-empirical-study-of-distilling-mim","slug":"tinymim-an-empirical-study-of-distilling-mim","title":"TinyMIM: An Empirical Study of Distilling MIM Pre-trained Models","date":"2023-01-03","arxiv_id":"2301.01296","n_code_links":2,"syntology":{"ran":8,"of":11,"n_ran_checked":8,"n_instrument":0,"unverified":3,"pointer_only":11,"phrase":"8 ran (of which 5 constructed an object rather than computing a result; 8 with no instrument failure: 1 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["oliverrensu/tinymim"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["listed","official"]}}},{"paper":"/paper/towards-knowledge-intensive-text-to-sql","slug":"towards-knowledge-intensive-text-to-sql","title":"Towards Knowledge-Intensive Text-to-SQL Semantic Parsing with Formulaic Knowledge","date":"2023-01-03","arxiv_id":"2301.01067","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"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) · 0 unverified","official":{"repos":["microsoft/ContextualSP"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"transfer-learning-for-classification-of","title":"Transfer Learning for Classification of Alzheimer's Disease Based on Genome Wide Data","date":"2023-01-03","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"beef-up-mmwave-dense-cellular-networks-with","title":"Beef up mmWave Dense Cellular Networks with D2D-Assisted Cooperative Edge Caching","date":"2023-01-02","arxiv_id":"2301.01141","n_code_links":0,"syntology":null},{"paper":null,"slug":"design-and-analysis-of-tweet-based-election","title":"Design and analysis of tweet-based election models for the 2021 Mexican legislative election","date":"2023-01-02","arxiv_id":"2301.00626","n_code_links":0,"syntology":null},{"paper":null,"slug":"model-driven-deep-learning-for-non-coherent","title":"Model-Driven Deep Learning for Non-Coherent Massive Machine-Type Communications","date":"2023-01-02","arxiv_id":"2301.00516","n_code_links":0,"syntology":null},{"paper":"/paper/p3dc-shot-prior-driven-discrete-data","slug":"p3dc-shot-prior-driven-discrete-data","title":"P3DC-Shot: Prior-Driven Discrete Data Calibration for Nearest-Neighbor Few-Shot Classification","date":"2023-01-02","arxiv_id":"2301.00740","n_code_links":1,"syntology":null},{"paper":null,"slug":"3d-spatial-multimodal-knowledge-accumulation","title":"3D Spatial Multimodal Knowledge Accumulation for Scene Graph Prediction in Point Cloud","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"an-actor-centric-causality-graph-for","title":"An Actor-Centric Causality Graph for Asynchronous Temporal Inference in Group Activity","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"bi-level-meta-learning-for-few-shot-domain","title":"Bi-Level Meta-Learning for Few-Shot Domain Generalization","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/bootstrap-your-own-prior-towards-distribution","slug":"bootstrap-your-own-prior-towards-distribution","title":"Bootstrap Your Own Prior: Towards Distribution-Agnostic Novel Class Discovery","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"clipping-distilling-clip-based-models-with-a","title":"CLIPPING: Distilling CLIP-Based Models With a Student Base for Video-Language Retrieval","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/compression-aware-video-super-resolution","slug":"compression-aware-video-super-resolution","title":"Compression-Aware Video Super-Resolution","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/distilling-detr-with-visual-linguistic","slug":"distilling-detr-with-visual-linguistic","title":"Distilling DETR with Visual-Linguistic Knowledge for Open-Vocabulary Object Detection","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"exploring-intra-class-variation-factors-with","title":"Exploring Intra-Class Variation Factors With Learnable Cluster Prompts for Semi-Supervised Image Synthesis","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/few-shot-class-incremental-learning-via-class","slug":"few-shot-class-incremental-learning-via-class","title":"Few-Shot Class-Incremental Learning via Class-Aware Bilateral Distillation","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"few-shot-continual-infomax-learning","title":"Few-shot Continual Infomax Learning","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/growing-a-brain-with-sparsity-inducing","slug":"growing-a-brain-with-sparsity-inducing","title":"Growing a Brain with Sparsity-Inducing Generation for Continual Learning","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/hdg-ode-a-hierarchical-continuous-time-model","slug":"hdg-ode-a-hierarchical-continuous-time-model","title":"HDG-ODE: A Hierarchical Continuous-Time Model for Human Pose Forecasting","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/learning-orthogonal-prototypes-for","slug":"learning-orthogonal-prototypes-for","title":"Learning Orthogonal Prototypes for Generalized Few-Shot Semantic Segmentation","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/masqclip-for-open-vocabulary-universal-image","slug":"masqclip-for-open-vocabulary-universal-image","title":"MasQCLIP for Open-Vocabulary Universal Image Segmentation","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"ml-2-p-encoder-on-exploration-of-channel","title":"(ML)$^2$P-Encoder: On Exploration of Channel-Class Correlation for Multi-Label Zero-Shot Learning","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/novel-scenes-classes-towards-adaptive-open","slug":"novel-scenes-classes-towards-adaptive-open","title":"Novel Scenes & Classes: Towards Adaptive Open-set Object Detection","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"open-vocabulary-object-detection-with-an-open","title":"Open-Vocabulary Object Detection With an Open Corpus","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"regen-a-good-generative-zero-shot-video","title":"ReGen: A good Generative Zero-Shot Video Classifier Should be Rewarded","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"riformer-keep-your-vision-backbone-effective-1","title":"RIFormer: Keep Your Vision Backbone Effective but Removing Token Mixer","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/starting-from-non-parametric-networks-for-3d","slug":"starting-from-non-parametric-networks-for-3d","title":"Starting From Non-Parametric Networks for 3D Point Cloud Analysis","date":"2023-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"weak-shot-object-detection-through-mutual","title":"Weak-Shot Object Detection Through Mutual Knowledge Transfer","date":"2023-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"computational-charisma-a-brick-by-brick","title":"Computational Charisma -- A Brick by Brick Blueprint for Building Charismatic Artificial Intelligence","date":"2022-12-31","arxiv_id":"2301.00142","n_code_links":0,"syntology":null},{"paper":null,"slug":"high-accuracy-absolute-position-aided-code","title":"High-Accuracy Absolute-Position-Aided Code Phase Tracking Based on RTK/INS Deep Integration in Challenging Static Scenarios","date":"2022-12-31","arxiv_id":"2301.00308","n_code_links":0,"syntology":null},{"paper":"/paper/pontryagin-optimal-controller-via-neural","slug":"pontryagin-optimal-controller-via-neural","title":"Pontryagin Optimal Control via Neural Networks","date":"2022-12-30","arxiv_id":"2212.14566","n_code_links":1,"syntology":null},{"paper":null,"slug":"can-5-rm-th-generation-local-training-methods","title":"Can 5th Generation Local Training Methods Support Client Sampling? Yes!","date":"2022-12-29","arxiv_id":"2212.14370","n_code_links":0,"syntology":null},{"paper":"/paper/deep-r-programming","slug":"deep-r-programming","title":"Deep R Programming","date":"2022-12-29","arxiv_id":"2301.01188","n_code_links":4,"syntology":null},{"paper":null,"slug":"wireless-semantic-communication-a-networking","title":"Joint User Association and Bandwidth Allocation in Semantic Communication Networks","date":"2022-12-29","arxiv_id":"2212.14142","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-distributed-game-theoretic-solution-for","title":"A Distributed Game-Theoretic Solution for Power Management in the Uplink of Cell-Free Systems","date":"2022-12-28","arxiv_id":"2212.13804","n_code_links":0,"syntology":null},{"paper":null,"slug":"don-t-do-it-safer-reinforcement-learning-with","title":"Don't do it: Safer Reinforcement Learning With Rule-based Guidance","date":"2022-12-28","arxiv_id":"2212.13819","n_code_links":0,"syntology":null},{"paper":null,"slug":"joint-receive-antenna-selection-and","title":"Joint Receive Antenna Selection and Beamforming in RIS-Aided MIMO Systems","date":"2022-12-28","arxiv_id":"2212.13684","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-scale-cell-level-quality-of-service","title":"Large-Scale Cell-Level Quality of Service Estimation on 5G Networks Using Machine Learning Techniques","date":"2022-12-28","arxiv_id":"2212.14071","n_code_links":0,"syntology":null},{"paper":null,"slug":"bayesian-optimization-enhanced-deep","title":"Bayesian Optimization Enhanced Deep Reinforcement Learning for Trajectory Planning and Network Formation in Multi-UAV Networks","date":"2022-12-27","arxiv_id":"2212.13396","n_code_links":0,"syntology":null},{"paper":null,"slug":"brain-cancer-segmentation-using-yolov5-deep","title":"Brain Cancer Segmentation Using YOLOv5 Deep Neural Network","date":"2022-12-27","arxiv_id":"2212.13599","n_code_links":0,"syntology":null},{"paper":null,"slug":"biologically-inspired-design-concept","title":"Biologically Inspired Design Concept Generation Using Generative Pre-Trained Transformers","date":"2022-12-26","arxiv_id":"2212.13196","n_code_links":0,"syntology":null},{"paper":"/paper/improving-complex-knowledge-base-question","slug":"improving-complex-knowledge-base-question","title":"Improving Complex Knowledge Base Question Answering via Question-to-Action and Question-to-Question Alignment","date":"2022-12-26","arxiv_id":"2212.13036","n_code_links":1,"syntology":{"ran":1,"of":4,"n_ran_checked":0,"n_instrument":1,"unverified":3,"pointer_only":4,"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","official":{"repos":["tttttttty/alcqa"],"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"]}}},{"paper":null,"slug":"linear-combinatorial-semi-bandit-with","title":"Linear Combinatorial Semi-Bandit with Causally Related Rewards","date":"2022-12-25","arxiv_id":"2212.12923","n_code_links":0,"syntology":null},{"paper":null,"slug":"activity-detection-for-grant-free-noma-in","title":"Activity Detection for Grant-Free NOMA in Massive IoT Networks","date":"2022-12-23","arxiv_id":"2301.01274","n_code_links":0,"syntology":null},{"paper":null,"slug":"collective-intelligent-strategy-for-improved","title":"Collective Intelligent Strategy for Improved Segmentation of COVID-19 from CT","date":"2022-12-23","arxiv_id":"2212.12264","n_code_links":0,"syntology":null},{"paper":null,"slug":"grant-free-random-access-with-self","title":"Grant-free Random Access with Self-conjugating Metasurfaces","date":"2022-12-23","arxiv_id":"2212.12453","n_code_links":0,"syntology":null},{"paper":null,"slug":"proximal-policy-optimization-with-graph","title":"Proximal Policy Optimization with Graph Neural Networks for Optimal Power Flow","date":"2022-12-23","arxiv_id":"2212.12470","n_code_links":0,"syntology":null},{"paper":"/paper/the-choice-of-scaling-technique-matters-for","slug":"the-choice-of-scaling-technique-matters-for","title":"The choice of scaling technique matters for classification performance","date":"2022-12-23","arxiv_id":"2212.12343","n_code_links":1,"syntology":null},{"paper":"/paper/good-exploring-geometric-cues-for-detecting","slug":"good-exploring-geometric-cues-for-detecting","title":"GOOD: Exploring Geometric Cues for Detecting Objects in an Open World","date":"2022-12-22","arxiv_id":"2212.11720","n_code_links":1,"syntology":null},{"paper":"/paper/multilingual-news-location-detection-using-an","slug":"multilingual-news-location-detection-using-an","title":"Multilingual News Location Detection using an Entity-Based Siamese Network with Semi-Supervised Contrastive Learning and Knowledge Base","date":"2022-12-22","arxiv_id":"2212.11856","n_code_links":1,"syntology":null},{"paper":null,"slug":"5g-long-term-and-large-scale-mobile-traffic","title":"5G Long-Term and Large-Scale Mobile Traffic Forecasting","date":"2022-12-21","arxiv_id":"2212.10869","n_code_links":0,"syntology":null},{"paper":null,"slug":"impakt-a-dataset-for-open-schema-knowledge","title":"ImPaKT: A Dataset for Open-Schema Knowledge Base Construction","date":"2022-12-21","arxiv_id":"2212.10770","n_code_links":0,"syntology":null},{"paper":"/paper/multiinstruct-improving-multi-modal-zero-shot","slug":"multiinstruct-improving-multi-modal-zero-shot","title":"MultiInstruct: Improving Multi-Modal Zero-Shot Learning via Instruction Tuning","date":"2022-12-21","arxiv_id":"2212.10773","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"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) · 0 unverified","official":{"repos":["vt-nlp/multiinstruct"],"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"]}}},{"paper":null,"slug":"apollo-a-simple-approach-for-adaptive","title":"APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning","date":"2022-12-19","arxiv_id":"2212.09282","n_code_links":0,"syntology":null},{"paper":"/paper/don-t-generate-discriminate-a-proposal-for","slug":"don-t-generate-discriminate-a-proposal-for","title":"Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environments","date":"2022-12-19","arxiv_id":"2212.09736","n_code_links":2,"syntology":{"ran":1,"of":3,"n_ran_checked":0,"n_instrument":1,"unverified":2,"pointer_only":3,"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) · 2 unverified","official":{"repos":["dki-lab/pangu"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/focal-unet-unet-like-focal-modulation-for","slug":"focal-unet-unet-like-focal-modulation-for","title":"Focal-UNet: UNet-like Focal Modulation for Medical Image Segmentation","date":"2022-12-19","arxiv_id":"2212.09263","n_code_links":1,"syntology":null},{"paper":"/paper/graph-based-semantical-extractive-text","slug":"graph-based-semantical-extractive-text","title":"Graph-based Semantical Extractive Text Analysis","date":"2022-12-19","arxiv_id":"2212.09701","n_code_links":1,"syntology":null},{"paper":null,"slug":"task-oriented-communications-for-nextg-end-to","title":"Task-Oriented Communications for NextG: End-to-End Deep Learning and AI Security Aspects","date":"2022-12-19","arxiv_id":"2212.09668","n_code_links":0,"syntology":null},{"paper":null,"slug":"annotation-by-clicks-a-point-supervised","title":"Annotation by Clicks: A Point-Supervised Contrastive Variance Method for Medical Semantic Segmentation","date":"2022-12-17","arxiv_id":"2212.08774","n_code_links":0,"syntology":null},{"paper":null,"slug":"toward-bci-enabled-metaverse-a-joint-radio","title":"Toward BCI-enabled Metaverse: A Joint Learning and Resource Allocation Approach","date":"2022-12-17","arxiv_id":"2212.08811","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-new-weighted-ensemble-model-for-phishing","title":"A new weighted ensemble model for phishing detection based on feature selection","date":"2022-12-15","arxiv_id":"2212.11125","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-level-association-rule-mining-for","title":"Multi-Level Association Rule Mining for Wireless Network Time Series Data","date":"2022-12-15","arxiv_id":"2212.07860","n_code_links":0,"syntology":null},{"paper":null,"slug":"physics-informed-neural-networks-for-material","title":"Physics-Informed Neural Networks for Material Model Calibration from Full-Field Displacement Data","date":"2022-12-15","arxiv_id":"2212.07723","n_code_links":0,"syntology":null},{"paper":"/paper/proposal-distribution-calibration-for-few","slug":"proposal-distribution-calibration-for-few","title":"Proposal Distribution Calibration for Few-Shot Object Detection","date":"2022-12-15","arxiv_id":"2212.07618","n_code_links":1,"syntology":null},{"paper":null,"slug":"retrieval-based-disentanglement-with-distant","title":"Retrieval-based Disentangled Representation Learning with Natural Language Supervision","date":"2022-12-15","arxiv_id":"2212.07699","n_code_links":0,"syntology":null},{"paper":null,"slug":"two-measure-is-two-know-calibration-free-full","title":"Two Measure is Two Know: Calibration-free Full Duplex Monitoring for Software Radio Platforms","date":"2022-12-15","arxiv_id":"2212.08179","n_code_links":0,"syntology":null},{"paper":"/paper/api-spector-an-api-to-api-specification","slug":"api-spector-an-api-to-api-specification","title":"API-Miner: an API-to-API Specification Recommendation Engine","date":"2022-12-14","arxiv_id":"2212.07253","n_code_links":1,"syntology":null},{"paper":null,"slug":"deep-negative-correlation-classification","title":"Deep Negative Correlation Classification","date":"2022-12-14","arxiv_id":"2212.07070","n_code_links":0,"syntology":null},{"paper":null,"slug":"dialogqae-n-to-n-question-answer-pair","title":"DialogQAE: N-to-N Question Answer Pair Extraction from Customer Service Chatlog","date":"2022-12-14","arxiv_id":"2212.07112","n_code_links":0,"syntology":null},{"paper":"/paper/engnn-a-general-edge-update-empowered-gnn","slug":"engnn-a-general-edge-update-empowered-gnn","title":"ENGNN: A General Edge-Update Empowered GNN Architecture for Radio Resource Management in Wireless Networks","date":"2022-12-14","arxiv_id":"2301.00757","n_code_links":1,"syntology":null},{"paper":"/paper/ma-gcl-model-augmentation-tricks-for-graph","slug":"ma-gcl-model-augmentation-tricks-for-graph","title":"MA-GCL: Model Augmentation Tricks for Graph Contrastive Learning","date":"2022-12-14","arxiv_id":"2212.07035","n_code_links":1,"syntology":null},{"paper":"/paper/post-hoc-uncertainty-learning-using-a","slug":"post-hoc-uncertainty-learning-using-a","title":"Post-hoc Uncertainty Learning using a Dirichlet Meta-Model","date":"2022-12-14","arxiv_id":"2212.07359","n_code_links":1,"syntology":{"ran":8,"of":11,"n_ran_checked":7,"n_instrument":1,"unverified":3,"pointer_only":2,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":{"repos":["maohaos2/PosthocUQ"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"the-challenges-of-htr-model-training-feedback","title":"The Challenges of HTR Model Training: Feedback from the Project Donner le gout de l'archive a l'ere numerique","date":"2022-12-13","arxiv_id":"2212.11146","n_code_links":0,"syntology":null},{"paper":null,"slug":"decentralized-cooperative-perception-for","title":"Decentralized cooperative perception for autonomous vehicles: Learning to value the unknown","date":"2022-12-12","arxiv_id":"2301.01250","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimizing-ship-detection-efficiency-in-sar","title":"Optimizing ship detection efficiency in SAR images","date":"2022-12-12","arxiv_id":"2212.05843","n_code_links":0,"syntology":null},{"paper":"/paper/perfex-classifier-performance-explanations","slug":"perfex-classifier-performance-explanations","title":"PERFEX: Classifier Performance Explanations for Trustworthy AI Systems","date":"2022-12-12","arxiv_id":"2212.06045","n_code_links":1,"syntology":null},{"paper":null,"slug":"synthetic-image-data-for-deep-learning","title":"Synthetic Image Data for Deep Learning","date":"2022-12-12","arxiv_id":"2212.06232","n_code_links":0,"syntology":null},{"paper":null,"slug":"hierarchical-deep-reinforcement-learning-for-1","title":"Hierarchical Deep Reinforcement Learning for VWAP Strategy Optimization","date":"2022-12-11","arxiv_id":"2212.14670","n_code_links":0,"syntology":null},{"paper":"/paper/indicxtreme-a-multi-task-benchmark-for","slug":"indicxtreme-a-multi-task-benchmark-for","title":"Towards Leaving No Indic Language Behind: Building Monolingual Corpora, Benchmark and Models for Indic Languages","date":"2022-12-11","arxiv_id":"2212.05409","n_code_links":1,"syntology":null},{"paper":"/paper/maps-kb-a-million-scale-probabilistic-simile","slug":"maps-kb-a-million-scale-probabilistic-simile","title":"MAPS-KB: A Million-scale Probabilistic Simile Knowledge Base","date":"2022-12-10","arxiv_id":"2212.05254","n_code_links":2,"syntology":null},{"paper":null,"slug":"motion-and-context-aware-audio-visual","title":"Motion and Context-Aware Audio-Visual Conditioned Video Prediction","date":"2022-12-09","arxiv_id":"2212.04679","n_code_links":0,"syntology":null}],"record_sha256":"ba80abc3608de3665bb2bc6bf4ae85fb974b6ba0db90d7350804e2666c805d99","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}