{"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/label-smoothing/papers/22","list_of":"/method/label-smoothing","method":"Label Smoothing","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":22,"pages_in_order":144,"rows_per_page":100,"rows":[2101,2200],"of":14327,"counts":{"archive_papers_tagged":14327,"with_a_code_link":6651,"where_syntology_ran_a_sample":2259,"not_listed_spam_title":0,"listed":14327,"listed_where_code_ran":2259,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1920,"every_run_a_failure_of_syntologys_instrument":339,"listed_with_a_run_with_no_instrument_failure":1920,"listed_every_run_a_failure_of_syntologys_instrument":339,"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/label-smoothing","prev":"/method/label-smoothing/papers/21","next":"/method/label-smoothing/papers/23","papers":[{"paper":null,"slug":"enhancing-transformer-training-efficiency","title":"Enhancing Transformer Training Efficiency with Dynamic Dropout","date":"2024-11-05","arxiv_id":"2411.03236","n_code_links":0,"syntology":null},{"paper":null,"slug":"foundation-ai-model-for-medical-image","title":"Foundation AI Model for Medical Image Segmentation","date":"2024-11-05","arxiv_id":"2411.02745","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-pixels-to-prose-advancing-multi-modal","title":"From Pixels to Prose: Advancing Multi-Modal Language Models for Remote Sensing","date":"2024-11-05","arxiv_id":"2411.05826","n_code_links":0,"syntology":null},{"paper":"/paper/kernel-approximation-using-analog-in-memory","slug":"kernel-approximation-using-analog-in-memory","title":"Kernel Approximation using Analog In-Memory Computing","date":"2024-11-05","arxiv_id":"2411.03375","n_code_links":1,"syntology":null},{"paper":null,"slug":"laser-attention-with-exponential","title":"LASER: Attention with Exponential Transformation","date":"2024-11-05","arxiv_id":"2411.03493","n_code_links":0,"syntology":null},{"paper":null,"slug":"mixtures-of-in-context-learners","title":"Mixtures of In-Context Learners","date":"2024-11-05","arxiv_id":"2411.02830","n_code_links":0,"syntology":null},{"paper":null,"slug":"neurons-for-neutrons-a-transformer-model-for","title":"Neurons for Neutrons: A Transformer Model for Computation Load Estimation on Domain-Decomposed Neutron Transport Problems","date":"2024-11-05","arxiv_id":"2411.03389","n_code_links":0,"syntology":null},{"paper":null,"slug":"p-moss-learned-scheduling-for-indexes-over","title":"P-MOSS: Learned Scheduling For Indexes Over NUMA Servers Using Low-Level Hardware Statistics","date":"2024-11-05","arxiv_id":"2411.02933","n_code_links":0,"syntology":null},{"paper":null,"slug":"predictor-corrector-enhanced-transformers","title":"Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning","date":"2024-11-05","arxiv_id":"2411.03042","n_code_links":0,"syntology":null},{"paper":"/paper/rethinking-decoders-for-transformer-based","slug":"rethinking-decoders-for-transformer-based","title":"Rethinking Decoders for Transformer-based Semantic Segmentation: A Compression Perspective","date":"2024-11-05","arxiv_id":"2411.03033","n_code_links":1,"syntology":null},{"paper":null,"slug":"transunext-towards-a-more-advanced-u-shaped","title":"TransUNext: towards a more advanced U-shaped framework for automatic vessel segmentation in the fundus image","date":"2024-11-05","arxiv_id":"2411.02724","n_code_links":0,"syntology":null},{"paper":null,"slug":"uncertainty-quantification-for-clinical","title":"Uncertainty Quantification for Clinical Outcome Predictions with (Large) Language Models","date":"2024-11-05","arxiv_id":"2411.03497","n_code_links":0,"syntology":null},{"paper":null,"slug":"user-centric-semantic-communications","title":"Receiver-Centric Generative Semantic Communications","date":"2024-11-05","arxiv_id":"2411.03127","n_code_links":0,"syntology":null},{"paper":null,"slug":"veritas-a-unified-approach-to-reliability","title":"VERITAS: A Unified Approach to Reliability Evaluation","date":"2024-11-05","arxiv_id":"2411.03300","n_code_links":0,"syntology":null},{"paper":"/paper/amortized-bayesian-experimental-design-for","slug":"amortized-bayesian-experimental-design-for","title":"Amortized Bayesian Experimental Design for Decision-Making","date":"2024-11-04","arxiv_id":"2411.02064","n_code_links":1,"syntology":null},{"paper":"/paper/ask-and-it-shall-be-given-turing-completeness","slug":"ask-and-it-shall-be-given-turing-completeness","title":"Ask, and it shall be given: On the Turing completeness of prompting","date":"2024-11-04","arxiv_id":"2411.01992","n_code_links":1,"syntology":null},{"paper":null,"slug":"disrupting-test-development-with-ai","title":"Disrupting Test Development with AI Assistants","date":"2024-11-04","arxiv_id":"2411.02328","n_code_links":0,"syntology":null},{"paper":"/paper/elastst-towards-robust-varied-horizon","slug":"elastst-towards-robust-varied-horizon","title":"ElasTST: Towards Robust Varied-Horizon Forecasting with Elastic Time-Series Transformer","date":"2024-11-04","arxiv_id":"2411.01842","n_code_links":1,"syntology":{"ran":14,"of":14,"n_ran_checked":12,"n_instrument":2,"unverified":0,"pointer_only":1,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["microsoft/probts"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"encoding-multi-level-dynamics-in-effect","title":"Optimizing Multi-Scale Representations to Detect Effect Heterogeneity Using Earth Observation and Computer Vision: Applications to Two Anti-Poverty RCTs","date":"2024-11-04","arxiv_id":"2411.02134","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-risk-assessment-in-transformers","title":"Enhancing Risk Assessment in Transformers with Loss-at-Risk Functions","date":"2024-11-04","arxiv_id":"2411.02558","n_code_links":0,"syntology":null},{"paper":"/paper/scalable-efficient-training-of-large-language","slug":"scalable-efficient-training-of-large-language","title":"Scalable Efficient Training of Large Language Models with Low-dimensional Projected Attention","date":"2024-11-04","arxiv_id":"2411.02063","n_code_links":1,"syntology":{"ran":5,"of":5,"n_ran_checked":3,"n_instrument":2,"unverified":0,"pointer_only":5,"phrase":"5 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["tsinghuac3i/lpa"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/seq-vcr-preventing-collapse-in-intermediate","slug":"seq-vcr-preventing-collapse-in-intermediate","title":"Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning","date":"2024-11-04","arxiv_id":"2411.02344","n_code_links":1,"syntology":null},{"paper":"/paper/sira-scalable-inter-frame-relation-and-1","slug":"sira-scalable-inter-frame-relation-and-1","title":"SIRA: Scalable Inter-frame Relation and Association for Radar Perception","date":"2024-11-04","arxiv_id":"2411.02220","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-leveraging-news-media-to-support","title":"Towards Leveraging News Media to Support Impact Assessment of AI Technologies","date":"2024-11-04","arxiv_id":"2411.02536","n_code_links":0,"syntology":null},{"paper":"/paper/training-compute-optimal-protein-language","slug":"training-compute-optimal-protein-language","title":"Training Compute-Optimal Protein Language Models","date":"2024-11-04","arxiv_id":"2411.02142","n_code_links":1,"syntology":null},{"paper":"/paper/training-free-regional-prompting-for","slug":"training-free-regional-prompting-for","title":"Training-free Regional Prompting for Diffusion Transformers","date":"2024-11-04","arxiv_id":"2411.02395","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 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; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["instantX-research/Regional-Prompting-FLUX"],"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","unlocated"]}}},{"paper":null,"slug":"wave-network-an-ultra-small-language-model","title":"Wave Network: An Ultra-Small Language Model","date":"2024-11-04","arxiv_id":"2411.02674","n_code_links":0,"syntology":null},{"paper":"/paper/xdit-an-inference-engine-for-diffusion","slug":"xdit-an-inference-engine-for-diffusion","title":"xDiT: an Inference Engine for Diffusion Transformers (DiTs) with Massive Parallelism","date":"2024-11-04","arxiv_id":"2411.01738","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-deep-dive-into-large-language-model-code","title":"A Deep Dive Into Large Language Model Code Generation Mistakes: What and Why?","date":"2024-11-03","arxiv_id":"2411.01414","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-glucose-level-prediction-of-icu","slug":"enhancing-glucose-level-prediction-of-icu","title":"Enhancing Glucose Level Prediction of ICU Patients through Hierarchical Modeling of Irregular Time-Series","date":"2024-11-03","arxiv_id":"2411.01418","n_code_links":1,"syntology":null},{"paper":null,"slug":"gitsr-graph-interaction-transformer-based","title":"GITSR: Graph Interaction Transformer-based Scene Representation for Multi Vehicle Collaborative Decision-making","date":"2024-11-03","arxiv_id":"2411.01608","n_code_links":0,"syntology":null},{"paper":"/paper/graphxform-graph-transformer-for-computer","slug":"graphxform-graph-transformer-for-computer","title":"GraphXForm: Graph transformer for computer-aided molecular design","date":"2024-11-03","arxiv_id":"2411.01667","n_code_links":1,"syntology":null},{"paper":null,"slug":"high-performance-automated-abstract-screening","title":"High-performance automated abstract screening with large language model ensembles","date":"2024-11-03","arxiv_id":"2411.02451","n_code_links":0,"syntology":null},{"paper":null,"slug":"himemformer-hierarchical-memory-aware","title":"HiMemFormer: Hierarchical Memory-Aware Transformer for Multi-Agent Action Anticipation","date":"2024-11-03","arxiv_id":"2411.01455","n_code_links":0,"syntology":null},{"paper":null,"slug":"integration-of-large-vision-language-models","title":"Integration of Large Vision Language Models for Efficient Post-disaster Damage Assessment and Reporting","date":"2024-11-03","arxiv_id":"2411.01511","n_code_links":0,"syntology":null},{"paper":"/paper/linrec-linear-attention-mechanism-for-long","slug":"linrec-linear-attention-mechanism-for-long","title":"LinRec: Linear Attention Mechanism for Long-term Sequential Recommender Systems","date":"2024-11-03","arxiv_id":"2411.01537","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"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) · 0 unverified","official":{"repos":["Applied-Machine-Learning-Lab/LinRec"],"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":"uniguard-towards-universal-safety-guardrails","title":"UniGuard: Towards Universal Safety Guardrails for Jailbreak Attacks on Multimodal Large Language Models","date":"2024-11-03","arxiv_id":"2411.01703","n_code_links":0,"syntology":null},{"paper":"/paper/few-class-arena-a-benchmark-for-efficient","slug":"few-class-arena-a-benchmark-for-efficient","title":"Few-Class Arena: A Benchmark for Efficient Selection of Vision Models and Dataset Difficulty Measurement","date":"2024-11-02","arxiv_id":"2411.01099","n_code_links":1,"syntology":null},{"paper":null,"slug":"reasoning-limitations-of-multimodal-large","title":"Reasoning Limitations of Multimodal Large Language Models. A case study of Bongard Problems","date":"2024-11-02","arxiv_id":"2411.01173","n_code_links":0,"syntology":null},{"paper":"/paper/task-aware-harmony-multi-task-decision","slug":"task-aware-harmony-multi-task-decision","title":"Task-Aware Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning","date":"2024-11-02","arxiv_id":"2411.01146","n_code_links":1,"syntology":{"ran":10,"of":11,"n_ran_checked":10,"n_instrument":0,"unverified":1,"pointer_only":2,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["charleshsc/HarmoDT"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/a-lorentz-equivariant-transformer-for-all-of","slug":"a-lorentz-equivariant-transformer-for-all-of","title":"A Lorentz-Equivariant Transformer for All of the LHC","date":"2024-11-01","arxiv_id":"2411.00446","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"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":["heidelberg-hepml/lorentz-gatr"],"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":"cross-fundus-transformer-for-multi-modal","title":"Cross-Fundus Transformer for Multi-modal Diabetic Retinopathy Grading with Cataract","date":"2024-11-01","arxiv_id":"2411.00726","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-the-impact-of-lab-test-results-on","title":"Evaluating the Impact of Lab Test Results on Large Language Models Generated Differential Diagnoses from Clinical Case Vignettes","date":"2024-11-01","arxiv_id":"2411.02523","n_code_links":0,"syntology":null},{"paper":null,"slug":"llms-a-game-changer-for-software-engineers","title":"LLMs: A Game-Changer for Software Engineers?","date":"2024-11-01","arxiv_id":"2411.00932","n_code_links":0,"syntology":null},{"paper":"/paper/self-evolved-reward-learning-for-llms","slug":"self-evolved-reward-learning-for-llms","title":"Self-Evolved Reward Learning for LLMs","date":"2024-11-01","arxiv_id":"2411.00418","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 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","official":null}},{"paper":"/paper/staa-spatio-temporal-attention-attribution","slug":"staa-spatio-temporal-attention-attribution","title":"STAA: Spatio-Temporal Attention Attribution for Real-Time Interpreting Transformer-based Video Models","date":"2024-11-01","arxiv_id":"2411.00630","n_code_links":1,"syntology":null},{"paper":"/paper/target-guided-adversarial-point-cloud","slug":"target-guided-adversarial-point-cloud","title":"Target-Guided Adversarial Point Cloud Transformer Towards Recognition Against Real-world Corruptions","date":"2024-11-01","arxiv_id":"2411.00462","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"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":["roywangj/apct"],"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":"towards-high-fidelity-head-blending-with","title":"Towards High-fidelity Head Blending with Chroma Keying for Industrial Applications","date":"2024-11-01","arxiv_id":"2411.00652","n_code_links":0,"syntology":null},{"paper":"/paper/ada-mshyper-adaptive-multi-scale-hypergraph","slug":"ada-mshyper-adaptive-multi-scale-hypergraph","title":"Ada-MSHyper: Adaptive Multi-Scale Hypergraph Transformer for Time Series Forecasting","date":"2024-10-31","arxiv_id":"2410.23992","n_code_links":1,"syntology":{"ran":0,"of":4,"n_ran_checked":0,"n_instrument":0,"unverified":4,"pointer_only":4,"phrase":"0 ran · 4 unverified","official":{"repos":["shangzongjiang/Ada-MSHyper"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":4,"ran_from_kinds":[]}}},{"paper":null,"slug":"aerial-flood-scene-classification-using-fine","title":"Aerial Flood Scene Classification Using Fine-Tuned Attention-based Architecture for Flood-Prone Countries in South Asia","date":"2024-10-31","arxiv_id":"2411.00169","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-in-long-short-stock-portfolio","title":"Deep Learning in Long-Short Stock Portfolio Allocation: An Empirical Study","date":"2024-10-31","arxiv_id":"2411.13555","n_code_links":0,"syntology":null},{"paper":null,"slug":"desert-camels-and-oil-sheikhs-arab-centric","title":"Desert Camels and Oil Sheikhs: Arab-Centric Red Teaming of Frontier LLMs","date":"2024-10-31","arxiv_id":"2410.24049","n_code_links":0,"syntology":null},{"paper":"/paper/edt-an-efficient-diffusion-transformer","slug":"edt-an-efficient-diffusion-transformer","title":"EDT: An Efficient Diffusion Transformer Framework Inspired by Human-like Sketching","date":"2024-10-31","arxiv_id":"2410.23788","n_code_links":1,"syntology":{"ran":12,"of":15,"n_ran_checked":9,"n_instrument":3,"unverified":3,"pointer_only":2,"phrase":"12 ran (of which 7 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 0 violated, 8 with no contract checked; 3 where Syntology's instrument failed) · 3 unverified","official":{"repos":["xinwangchen/edt"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":7,"n_ran_no_instrument_failure":9,"n_unverified":3,"ran_from_kinds":["official","unlocated"]}}},{"paper":null,"slug":"enhancing-brain-tumor-classification-using","title":"Enhancing Brain Tumor Classification Using TrAdaBoost and Multi-Classifier Deep Learning Approaches","date":"2024-10-31","arxiv_id":"2411.00875","n_code_links":0,"syntology":null},{"paper":null,"slug":"handwriting-recognition-in-historical","title":"Handwriting Recognition in Historical Documents with Multimodal LLM","date":"2024-10-31","arxiv_id":"2410.24034","n_code_links":0,"syntology":null},{"paper":null,"slug":"io-transformer-evaluating-swinv2-based-reward","title":"IO Transformer: Evaluating SwinV2-Based Reward Models for Computer Vision","date":"2024-10-31","arxiv_id":"2411.00252","n_code_links":0,"syntology":null},{"paper":null,"slug":"jema-a-joint-embedding-framework-for-scalable","title":"JEMA: A Joint Embedding Framework for Scalable Co-Learning with Multimodal Alignment","date":"2024-10-31","arxiv_id":"2410.23988","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-language-models-for-patient-comments","title":"Large Language Models for Patient Comments Multi-Label Classification","date":"2024-10-31","arxiv_id":"2410.23528","n_code_links":0,"syntology":null},{"paper":null,"slug":"lseattention-is-all-you-need-for-time-series","title":"LSEAttention is All You Need for Time Series Forecasting","date":"2024-10-31","arxiv_id":"2410.23749","n_code_links":0,"syntology":null},{"paper":"/paper/reinforcement-learning-gradients-as-vitamin","slug":"reinforcement-learning-gradients-as-vitamin","title":"Reinforcement Learning Gradients as Vitamin for Online Finetuning Decision Transformers","date":"2024-10-31","arxiv_id":"2410.24108","n_code_links":1,"syntology":{"ran":4,"of":7,"n_ran_checked":4,"n_instrument":0,"unverified":3,"pointer_only":7,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["kaiyan289/rl_as_vitamin_for_online_decision_transformers"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/rsl-sql-robust-schema-linking-in-text-to-sql","slug":"rsl-sql-robust-schema-linking-in-text-to-sql","title":"RSL-SQL: Robust Schema Linking in Text-to-SQL Generation","date":"2024-10-31","arxiv_id":"2411.00073","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":["laqcce-cao/rsl-sql"],"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":"a-comprehensive-study-on-quantization","title":"A Comprehensive Study on Quantization Techniques for Large Language Models","date":"2024-10-30","arxiv_id":"2411.02530","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-neural-transformer-framework-for","title":"A Transformer Model for Segmentation, Classification, and Caller Identification of Marmoset Vocalization","date":"2024-10-30","arxiv_id":"2410.23279","n_code_links":0,"syntology":null},{"paper":null,"slug":"danoliteracy-of-generative-large-language","title":"Danoliteracy of Generative, Large Language Models","date":"2024-10-30","arxiv_id":"2410.22839","n_code_links":0,"syntology":null},{"paper":null,"slug":"emergence-of-meta-stable-clustering-in-mean","title":"Emergence of meta-stable clustering in mean-field transformer models","date":"2024-10-30","arxiv_id":"2410.23228","n_code_links":0,"syntology":null},{"paper":null,"slug":"epipolar-free-3d-gaussian-splatting-for","title":"Epipolar-Free 3D Gaussian Splatting for Generalizable Novel View Synthesis","date":"2024-10-30","arxiv_id":"2410.22817","n_code_links":0,"syntology":null},{"paper":"/paper/evocodebench-an-evolving-code-generation-1","slug":"evocodebench-an-evolving-code-generation-1","title":"EvoCodeBench: An Evolving Code Generation Benchmark with Domain-Specific Evaluations","date":"2024-10-30","arxiv_id":"2410.22821","n_code_links":0,"syntology":{"ran":4,"of":4,"n_ran_checked":3,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/high-fidelity-document-stain-removal-via-a","slug":"high-fidelity-document-stain-removal-via-a","title":"High-Fidelity Document Stain Removal via A Large-Scale Real-World Dataset and A Memory-Augmented Transformer","date":"2024-10-30","arxiv_id":"2410.22922","n_code_links":1,"syntology":null},{"paper":null,"slug":"higher-order-cross-structural-embedding-model","title":"Higher-order Cross-structural Embedding Model for Time Series Analysis","date":"2024-10-30","arxiv_id":"2410.22984","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-to-achieve-goals-with-belief-state","title":"Learning to Achieve Goals with Belief State Transformers","date":"2024-10-30","arxiv_id":"2410.23506","n_code_links":0,"syntology":null},{"paper":null,"slug":"loflat-local-feature-matching-using-focused","title":"LoFLAT: Local Feature Matching using Focused Linear Attention Transformer","date":"2024-10-30","arxiv_id":"2410.22710","n_code_links":0,"syntology":null},{"paper":null,"slug":"return-augmented-decision-transformer-for-off","title":"Return Augmented Decision Transformer for Off-Dynamics Reinforcement Learning","date":"2024-10-30","arxiv_id":"2410.23450","n_code_links":0,"syntology":null},{"paper":"/paper/scipip-an-llm-based-scientific-paper-idea","slug":"scipip-an-llm-based-scientific-paper-idea","title":"SciPIP: An LLM-based Scientific Paper Idea Proposer","date":"2024-10-30","arxiv_id":"2410.23166","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"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","official":{"repos":["cheerss/scipip"],"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"]}}},{"paper":null,"slug":"st-dtpm-spatial-temporal-guided-diffusion","title":"st-DTPM: Spatial-Temporal Guided Diffusion Transformer Probabilistic Model for Delayed Scan PET Image Prediction","date":"2024-10-30","arxiv_id":"2410.22732","n_code_links":0,"syntology":null},{"paper":"/paper/a-large-recurrent-action-model-xlstm-enables","slug":"a-large-recurrent-action-model-xlstm-enables","title":"A Large Recurrent Action Model: xLSTM enables Fast Inference for Robotics Tasks","date":"2024-10-29","arxiv_id":"2410.22391","n_code_links":1,"syntology":{"ran":6,"of":7,"n_ran_checked":6,"n_instrument":0,"unverified":1,"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) · 1 unverified","official":{"repos":["ml-jku/lram"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":6,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/amplegcg-plus-a-strong-generative-model-of","slug":"amplegcg-plus-a-strong-generative-model-of","title":"AmpleGCG-Plus: A Strong Generative Model of Adversarial Suffixes to Jailbreak LLMs with Higher Success Rates in Fewer Attempts","date":"2024-10-29","arxiv_id":"2410.22143","n_code_links":1,"syntology":{"ran":7,"of":7,"n_ran_checked":7,"n_instrument":0,"unverified":0,"pointer_only":7,"phrase":"7 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; 0 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":null,"slug":"cfsafety-comprehensive-fine-grained-safety","title":"CFSafety: Comprehensive Fine-grained Safety Assessment for LLMs","date":"2024-10-29","arxiv_id":"2410.21695","n_code_links":0,"syntology":null},{"paper":null,"slug":"dineuro-distilling-knowledge-from-2d-natural","title":"DINeuro: Distilling Knowledge from 2D Natural Images via Deformable Tubular Transferring Strategy for 3D Neuron Reconstruction","date":"2024-10-29","arxiv_id":"2410.22078","n_code_links":0,"syntology":null},{"paper":null,"slug":"dual-conditional-diffusion-models-for","title":"Dual Conditional Diffusion Models for Sequential Recommendation","date":"2024-10-29","arxiv_id":"2410.21967","n_code_links":0,"syntology":null},{"paper":"/paper/efficient-machine-translation-with-a-bilstm","slug":"efficient-machine-translation-with-a-bilstm","title":"Efficient Machine Translation with a BiLSTM-Attention Approach","date":"2024-10-29","arxiv_id":"2410.22335","n_code_links":2,"syntology":null},{"paper":null,"slug":"emotion-guided-image-to-music-generation","title":"Emotion-Guided Image to Music Generation","date":"2024-10-29","arxiv_id":"2410.22299","n_code_links":0,"syntology":null},{"paper":"/paper/et-flow-equivariant-flow-matching-for","slug":"et-flow-equivariant-flow-matching-for","title":"ET-Flow: Equivariant Flow-Matching for Molecular Conformer Generation","date":"2024-10-29","arxiv_id":"2410.22388","n_code_links":1,"syntology":{"ran":12,"of":12,"n_ran_checked":12,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["shenoynikhil/etflow"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":12,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"evaluating-k-fold-cross-validation-for","title":"Evaluating K-Fold Cross Validation for Transformer Based Symbolic Regression Models","date":"2024-10-29","arxiv_id":"2410.21896","n_code_links":0,"syntology":null},{"paper":null,"slug":"fourier-head-helping-large-language-models","title":"Fourier Head: Helping Large Language Models Learn Complex Probability Distributions","date":"2024-10-29","arxiv_id":"2410.22269","n_code_links":0,"syntology":null},{"paper":"/paper/leveraging-user-history-with-transformers-for","slug":"leveraging-user-history-with-transformers-for","title":"Leveraging User History with Transformers for News Clicking: The DArgk Approach","date":"2024-10-29","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/long-context-protein-language-model","slug":"long-context-protein-language-model","title":"Long-context Protein Language Modeling Using Bidirectional Mamba with Shared Projection Layers","date":"2024-10-29","arxiv_id":"2411.08909","n_code_links":1,"syntology":null},{"paper":"/paper/multi-step-feature-fusion-for-natural","slug":"multi-step-feature-fusion-for-natural","title":"Multi-step feature fusion for natural disaster damage assessment on satellite images","date":"2024-10-29","arxiv_id":"2410.21901","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-role-of-depth-and-looping-for-in","title":"On the Role of Depth and Looping for In-Context Learning with Task Diversity","date":"2024-10-29","arxiv_id":"2410.21698","n_code_links":0,"syntology":null},{"paper":"/paper/sam-swin-sam-driven-dual-swin-transformers","slug":"sam-swin-sam-driven-dual-swin-transformers","title":"SAM-Swin: SAM-Driven Dual-Swin Transformers with Adaptive Lesion Enhancement for Laryngo-Pharyngeal Tumor Detection","date":"2024-10-29","arxiv_id":"2410.21813","n_code_links":1,"syntology":null},{"paper":null,"slug":"self-preference-bias-in-llm-as-a-judge","title":"Self-Preference Bias in LLM-as-a-Judge","date":"2024-10-29","arxiv_id":"2410.21819","n_code_links":0,"syntology":null},{"paper":null,"slug":"sequential-choice-in-ordered-bundles","title":"Sequential choice in ordered bundles","date":"2024-10-29","arxiv_id":"2410.21670","n_code_links":0,"syntology":null},{"paper":null,"slug":"spatio-temporal-transformers-for-action-unit","title":"Spatio-temporal Transformers for Action Unit Classification with Event Cameras","date":"2024-10-29","arxiv_id":"2410.21958","n_code_links":0,"syntology":null},{"paper":"/paper/topic-conversation-relevance-tcr-dataset-and","slug":"topic-conversation-relevance-tcr-dataset-and","title":"Topic-Conversation Relevance (TCR) Dataset and Benchmarks","date":"2024-10-29","arxiv_id":"2411.00038","n_code_links":1,"syntology":{"ran":8,"of":10,"n_ran_checked":8,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified","official":{"repos":["microsoft/topic_conversation"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/a-simple-yet-effective-corpus-construction-1","slug":"a-simple-yet-effective-corpus-construction-1","title":"A Simple Yet Effective Corpus Construction Framework for Indonesian Grammatical Error Correction","date":"2024-10-28","arxiv_id":"2410.20838","n_code_links":1,"syntology":null},{"paper":"/paper/belief-in-the-machine-investigating","slug":"belief-in-the-machine-investigating","title":"Belief in the Machine: Investigating Epistemological Blind Spots of Language Models","date":"2024-10-28","arxiv_id":"2410.21195","n_code_links":1,"syntology":null},{"paper":"/paper/bytenet-rethinking-multimedia-file-fragment","slug":"bytenet-rethinking-multimedia-file-fragment","title":"ByteNet: Rethinking Multimedia File Fragment Classification through Visual Perspectives","date":"2024-10-28","arxiv_id":"2410.20855","n_code_links":1,"syntology":null},{"paper":null,"slug":"ct2c-qa-multimodal-question-answering-over","title":"CT2C-QA: Multimodal Question Answering over Chinese Text, Table and Chart","date":"2024-10-28","arxiv_id":"2410.21414","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-learning-for-medical-text-processing","title":"Deep Learning for Medical Text Processing: BERT Model Fine-Tuning and Comparative Study","date":"2024-10-28","arxiv_id":"2410.20792","n_code_links":0,"syntology":null},{"paper":null,"slug":"efficient-bilinear-attention-based-fusion-for","title":"Efficient Bilinear Attention-based Fusion for Medical Visual Question Answering","date":"2024-10-28","arxiv_id":"2410.21000","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-the-robustness-of-lidar-point","title":"Evaluating the Robustness of LiDAR Point Cloud Tracking Against Adversarial Attack","date":"2024-10-28","arxiv_id":"2410.20893","n_code_links":0,"syntology":null}],"record_sha256":"77b140df53a7bf61f7796ee7d4e81dc3c79867f1a7c8531e7d89dee45ea0e235","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}