{"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/dropout/papers/100","list_of":"/method/dropout","method":"Dropout","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":100,"pages_in_order":275,"rows_per_page":100,"rows":[9901,10000],"of":27472,"counts":{"archive_papers_tagged":27472,"with_a_code_link":12129,"where_syntology_ran_a_sample":3620,"not_listed_spam_title":0,"listed":27472,"listed_where_code_ran":3620,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3044,"every_run_a_failure_of_syntologys_instrument":576,"listed_with_a_run_with_no_instrument_failure":3044,"listed_every_run_a_failure_of_syntologys_instrument":576,"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/dropout","prev":"/method/dropout/papers/99","next":"/method/dropout/papers/101","papers":[{"paper":"/paper/hybrid-proposal-refiner-revisiting-detr","slug":"hybrid-proposal-refiner-revisiting-detr","title":"Hybrid Proposal Refiner: Revisiting DETR Series from the Faster R-CNN Perspective","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/jointsq-joint-sparsification-quantization-for","slug":"jointsq-joint-sparsification-quantization-for","title":"JointSQ: Joint Sparsification-Quantization for Distributed Learning","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"kd-detr-knowledge-distillation-for-detection","title":"KD-DETR: Knowledge Distillation for Detection Transformer with Consistent Distillation Points Sampling","date":"2024-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"large-language-models-aren-t-all-that-you","title":"Large Language Models aren't all that you need","date":"2024-01-01","arxiv_id":"2401.00698","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-language-models-in-mental-health-care-a","title":"Large Language Models in Mental Health Care: a Scoping Review","date":"2024-01-01","arxiv_id":"2401.02984","n_code_links":0,"syntology":null},{"paper":"/paper/mean-shift-feature-transformer","slug":"mean-shift-feature-transformer","title":"Mean-Shift Feature Transformer","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/multi-attribute-interactions-matter-for-3d","slug":"multi-attribute-interactions-matter-for-3d","title":"Multi-Attribute Interactions Matter for 3D Visual Grounding","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/pairdetr-joint-detection-and-association-of","slug":"pairdetr-joint-detection-and-association-of","title":"PairDETR : Joint Detection and Association of Human Bodies and Faces","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"parameternet-parameters-are-all-you-need-for-1","title":"ParameterNet: Parameters Are All You Need for Large-scale Visual Pretraining of Mobile Networks","date":"2024-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"person-in-wifi-3d-end-to-end-multi-person-3d","title":"Person-in-WiFi 3D: End-to-End Multi-Person 3D Pose Estimation with Wi-Fi","date":"2024-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/point-transformer-v3-simpler-faster-stronger-1","slug":"point-transformer-v3-simpler-faster-stronger-1","title":"Point Transformer V3: Simpler Faster Stronger","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/pre-training-vision-models-with-mandelbulb","slug":"pre-training-vision-models-with-mandelbulb","title":"Pre-training Vision Models with Mandelbulb Variations","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"random-entangled-tokens-for-adversarially","title":"Random Entangled Tokens for Adversarially Robust Vision Transformer","date":"2024-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/revisiting-counterfactual-problems-in","slug":"revisiting-counterfactual-problems-in","title":"Revisiting Counterfactual Problems in Referring Expression Comprehension","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/secformer-towards-fast-and-accurate-privacy","slug":"secformer-towards-fast-and-accurate-privacy","title":"SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC","date":"2024-01-01","arxiv_id":"2401.00793","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":3,"phrase":"2 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; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["jinglong696/secformer"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["unlocated"]}}},{"paper":"/paper/seed-bench-benchmarking-multimodal-large","slug":"seed-bench-benchmarking-multimodal-large","title":"SEED-Bench: Benchmarking Multimodal Large Language Models","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/specat-spatial-spectral-cumulative-attention","slug":"specat-spatial-spectral-cumulative-attention","title":"SPECAT: SPatial-spEctral Cumulative-Attention Transformer for High-Resolution Hyperspectral Image Reconstruction","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"taking-the-next-step-with-generative","title":"Taking the Next Step with Generative Artificial Intelligence: The Transformative Role of Multimodal Large Language Models in Science Education","date":"2024-01-01","arxiv_id":"2401.00832","n_code_links":0,"syntology":null},{"paper":"/paper/training-vision-transformers-for-semi","slug":"training-vision-transformers-for-semi","title":"Training Vision Transformers for Semi-Supervised Semantic Segmentation","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/transloc4d-transformer-based-4d-radar-place","slug":"transloc4d-transformer-based-4d-radar-place","title":"TransLoc4D: Transformer-based 4D Radar Place Recognition","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/uncertainty-aware-action-decoupling","slug":"uncertainty-aware-action-decoupling","title":"Uncertainty-aware Action Decoupling Transformer for Action Anticipation","date":"2024-01-01","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":"/paper/video-harmonization-with-triplet-spatio","slug":"video-harmonization-with-triplet-spatio","title":"Video Harmonization with Triplet Spatio-Temporal Variation Patterns","date":"2024-01-01","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"a-two-stream-hybrid-cnn-transformer-network","title":"A Two-stream Hybrid CNN-Transformer Network for Skeleton-based Human Interaction Recognition","date":"2023-12-31","arxiv_id":"2401.00409","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-analysis-of-embedding-layers-and","title":"An Analysis of Embedding Layers and Similarity Scores using Siamese Neural Networks","date":"2023-12-31","arxiv_id":"2401.00582","n_code_links":0,"syntology":null},{"paper":"/paper/emage-towards-unified-holistic-co-speech","slug":"emage-towards-unified-holistic-co-speech","title":"EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling","date":"2023-12-31","arxiv_id":"2401.00374","n_code_links":1,"syntology":{"ran":4,"of":4,"n_ran_checked":3,"n_instrument":1,"unverified":0,"pointer_only":4,"phrase":"4 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 2 honoured, 1 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["PantoMatrix/PantoMatrix"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/generative-model-driven-synthetic-training","slug":"generative-model-driven-synthetic-training","title":"Generative Model-Driven Synthetic Training Image Generation: An Approach to Cognition in Rail Defect Detection","date":"2023-12-31","arxiv_id":"2401.00393","n_code_links":1,"syntology":null},{"paper":"/paper/ragtruth-a-hallucination-corpus-for","slug":"ragtruth-a-hallucination-corpus-for","title":"RAGTruth: A Hallucination Corpus for Developing Trustworthy Retrieval-Augmented Language Models","date":"2023-12-31","arxiv_id":"2401.00396","n_code_links":3,"syntology":{"ran":3,"of":5,"n_ran_checked":3,"n_instrument":0,"unverified":2,"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) · 2 unverified","official":{"repos":["particlemedia/ragtruth"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/svfap-self-supervised-video-facial-affect","slug":"svfap-self-supervised-video-facial-affect","title":"SVFAP: Self-supervised Video Facial Affect Perceiver","date":"2023-12-31","arxiv_id":"2401.00416","n_code_links":1,"syntology":null},{"paper":"/paper/tsgan-an-optical-to-sar-dual-conditional-gan","slug":"tsgan-an-optical-to-sar-dual-conditional-gan","title":"TSGAN: An Optical-to-SAR Dual Conditional GAN for Optical based SAR Temporal Shifting","date":"2023-12-31","arxiv_id":"2401.00440","n_code_links":1,"syntology":null},{"paper":"/paper/advancing-ttp-analysis-harnessing-the-power","slug":"advancing-ttp-analysis-harnessing-the-power","title":"Advancing TTP Analysis: Harnessing the Power of Large Language Models with Retrieval Augmented Generation","date":"2023-12-30","arxiv_id":"2401.00280","n_code_links":1,"syntology":null},{"paper":"/paper/hybridgait-a-benchmark-for-spatial-temporal","slug":"hybridgait-a-benchmark-for-spatial-temporal","title":"HybridGait: A Benchmark for Spatial-Temporal Cloth-Changing Gait Recognition with Hybrid Explorations","date":"2023-12-30","arxiv_id":"2401.00271","n_code_links":1,"syntology":null},{"paper":null,"slug":"image-super-resolution-reconstruction-network","title":"Image Super-resolution Reconstruction Network based on Enhanced Swin Transformer via Alternating Aggregation of Local-Global Features","date":"2023-12-30","arxiv_id":"2401.00241","n_code_links":0,"syntology":null},{"paper":"/paper/l3cube-mahasocialner-a-social-media-based","slug":"l3cube-mahasocialner-a-social-media-based","title":"L3Cube-MahaSocialNER: A Social Media based Marathi NER Dataset and BERT models","date":"2023-12-30","arxiv_id":"2401.00170","n_code_links":1,"syntology":null},{"paper":null,"slug":"trace-and-edit-relation-associations-in-gpt","title":"Trace and Edit Relation Associations in GPT","date":"2023-12-30","arxiv_id":"2401.02976","n_code_links":0,"syntology":null},{"paper":"/paper/why-is-the-user-interface-a-dark-pattern","slug":"why-is-the-user-interface-a-dark-pattern","title":"Why is the User Interface a Dark Pattern? : Explainable Auto-Detection and its Analysis","date":"2023-12-30","arxiv_id":"2401.04119","n_code_links":1,"syntology":null},{"paper":"/paper/action-item-driven-summarization-of-long","slug":"action-item-driven-summarization-of-long","title":"Action-Item-Driven Summarization of Long Meeting Transcripts","date":"2023-12-29","arxiv_id":"2312.17581","n_code_links":1,"syntology":null},{"paper":"/paper/adaptive-control-strategy-for-quadruped","slug":"adaptive-control-strategy-for-quadruped","title":"Adaptive Control Strategy for Quadruped Robots in Actuator Degradation Scenarios","date":"2023-12-29","arxiv_id":"2312.17606","n_code_links":1,"syntology":null},{"paper":null,"slug":"efficacy-of-utilizing-large-language-models","title":"Efficacy of Utilizing Large Language Models to Detect Public Threat Posted Online","date":"2023-12-29","arxiv_id":"2401.02974","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-quantitative-reasoning-skills-of","title":"Enhancing Quantitative Reasoning Skills of Large Language Models through Dimension Perception","date":"2023-12-29","arxiv_id":"2312.17532","n_code_links":0,"syntology":null},{"paper":"/paper/gemini-in-reasoning-unveiling-commonsense-in","slug":"gemini-in-reasoning-unveiling-commonsense-in","title":"Gemini in Reasoning: Unveiling Commonsense in Multimodal Large Language Models","date":"2023-12-29","arxiv_id":"2312.17661","n_code_links":1,"syntology":null},{"paper":"/paper/jatmo-prompt-injection-defense-by-task","slug":"jatmo-prompt-injection-defense-by-task","title":"Jatmo: Prompt Injection Defense by Task-Specific Finetuning","date":"2023-12-29","arxiv_id":"2312.17673","n_code_links":1,"syntology":{"ran":10,"of":18,"n_ran_checked":10,"n_instrument":0,"unverified":8,"pointer_only":18,"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) · 8 unverified","official":{"repos":["wagner-group/prompt-injection-defense"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":8,"ran_from_kinds":["official"]}}},{"paper":"/paper/mosaicbert-a-bidirectional-encoder-optimized-1","slug":"mosaicbert-a-bidirectional-encoder-optimized-1","title":"MosaicBERT: A Bidirectional Encoder Optimized for Fast Pretraining","date":"2023-12-29","arxiv_id":"2312.17482","n_code_links":1,"syntology":null},{"paper":"/paper/multiscale-vision-transformers-meet-bipartite","slug":"multiscale-vision-transformers-meet-bipartite","title":"Multiscale Vision Transformers meet Bipartite Matching for efficient single-stage Action Localization","date":"2023-12-29","arxiv_id":"2312.17686","n_code_links":1,"syntology":null},{"paper":"/paper/tupy-e-detecting-hate-speech-in-brazilian","slug":"tupy-e-detecting-hate-speech-in-brazilian","title":"TuPy-E: detecting hate speech in Brazilian Portuguese social media with a novel dataset and comprehensive analysis of models","date":"2023-12-29","arxiv_id":"2312.17704","n_code_links":1,"syntology":null},{"paper":"/paper/xai-for-in-hospital-mortality-prediction-via","slug":"xai-for-in-hospital-mortality-prediction-via","title":"XAI for In-hospital Mortality Prediction via Multimodal ICU Data","date":"2023-12-29","arxiv_id":"2312.17624","n_code_links":1,"syntology":null},{"paper":"/paper/challenge-llms-to-reason-about-reasoning-a","slug":"challenge-llms-to-reason-about-reasoning-a","title":"MR-GSM8K: A Meta-Reasoning Benchmark for Large Language Model Evaluation","date":"2023-12-28","arxiv_id":"2312.17080","n_code_links":2,"syntology":null},{"paper":"/paper/empirical-fits-to-inclusive-electron-carbon","slug":"empirical-fits-to-inclusive-electron-carbon","title":"Empirical fits to inclusive electron-carbon scattering data obtained by deep-learning methods","date":"2023-12-28","arxiv_id":"2312.17298","n_code_links":1,"syntology":null},{"paper":null,"slug":"evaluating-the-performance-of-large-language-1","title":"Evaluating the Performance of Large Language Models for Spanish Language in Undergraduate Admissions Exams","date":"2023-12-28","arxiv_id":"2312.16845","n_code_links":0,"syntology":null},{"paper":"/paper/geometry-biased-transformer-for-robust-multi","slug":"geometry-biased-transformer-for-robust-multi","title":"Geometry-Biased Transformer for Robust Multi-View 3D Human Pose Reconstruction","date":"2023-12-28","arxiv_id":"2312.17106","n_code_links":0,"syntology":null},{"paper":"/paper/gitagent-facilitating-autonomous-agent-with","slug":"gitagent-facilitating-autonomous-agent-with","title":"Enhancing Open-Domain Task-Solving Capability of LLMs via Autonomous Tool Integration from GitHub","date":"2023-12-28","arxiv_id":"2312.17294","n_code_links":1,"syntology":null},{"paper":null,"slug":"language-model-as-an-annotator-unsupervised","title":"Language Model as an Annotator: Unsupervised Context-aware Quality Phrase Generation","date":"2023-12-28","arxiv_id":"2312.17349","n_code_links":0,"syntology":null},{"paper":null,"slug":"large-language-model-for-causal-decision","title":"LLM4Causal: Democratized Causal Tools for Everyone via Large Language Model","date":"2023-12-28","arxiv_id":"2312.17122","n_code_links":0,"syntology":null},{"paper":"/paper/learning-multi-axis-representation-in","slug":"learning-multi-axis-representation-in","title":"Learning Multi-axis Representation in Frequency Domain for Medical Image Segmentation","date":"2023-12-28","arxiv_id":"2312.17030","n_code_links":1,"syntology":null},{"paper":null,"slug":"length-extrapolation-of-transformers-a-survey","title":"Length Extrapolation of Transformers: A Survey from the Perspective of Positional Encoding","date":"2023-12-28","arxiv_id":"2312.17044","n_code_links":0,"syntology":null},{"paper":null,"slug":"roi-aware-multiscale-cross-attention-vision","title":"ROI-Aware Multiscale Cross-Attention Vision Transformer for Pest Image Identification","date":"2023-12-28","arxiv_id":"2312.16914","n_code_links":0,"syntology":null},{"paper":"/paper/sentinellms-encrypted-input-adaptation-and","slug":"sentinellms-encrypted-input-adaptation-and","title":"SentinelLMs: Encrypted Input Adaptation and Fine-tuning of Language Models for Private and Secure Inference","date":"2023-12-28","arxiv_id":"2312.17342","n_code_links":1,"syntology":null},{"paper":"/paper/the-llm-surgeon","slug":"the-llm-surgeon","title":"The LLM Surgeon","date":"2023-12-28","arxiv_id":"2312.17244","n_code_links":1,"syntology":{"ran":4,"of":10,"n_ran_checked":4,"n_instrument":0,"unverified":6,"pointer_only":10,"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) · 6 unverified","official":{"repos":["qualcomm-ai-research/llm-surgeon"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":6,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"uncertainty-quantification-in-machine-2","title":"Uncertainty Quantification in Machine Learning for Joint Speaker Diarization and Identification","date":"2023-12-28","arxiv_id":"2312.16763","n_code_links":0,"syntology":null},{"paper":"/paper/vot-revolutionizing-speaker-verification-with","slug":"vot-revolutionizing-speaker-verification-with","title":"A New Perspective on Speaker Verification: Joint Modeling with DFSMN and Transformer","date":"2023-12-28","arxiv_id":"2312.16826","n_code_links":1,"syntology":null},{"paper":"/paper/weed-mapping-in-multispectral-drone-imagery","slug":"weed-mapping-in-multispectral-drone-imagery","title":"Weed mapping in multispectral drone imagery using lightweight vision transformers","date":"2023-12-28","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":"/paper/a-non-uniform-low-light-image-enhancement","slug":"a-non-uniform-low-light-image-enhancement","title":"A Non-Uniform Low-Light Image Enhancement Method with Multi-Scale Attention Transformer and Luminance Consistency Loss","date":"2023-12-27","arxiv_id":"2312.16498","n_code_links":1,"syntology":null},{"paper":"/paper/group-multi-view-transformer-for-3d-shape","slug":"group-multi-view-transformer-for-3d-shape","title":"Group Multi-View Transformer for 3D Shape Analysis with Spatial Encoding","date":"2023-12-27","arxiv_id":"2312.16477","n_code_links":1,"syntology":null},{"paper":null,"slug":"keeping-teams-in-the-game-predicting-dropouts","title":"Keeping Teams in the Game: Predicting Dropouts in Online Problem-Based Learning Competition","date":"2023-12-27","arxiv_id":"2312.16362","n_code_links":0,"syntology":null},{"paper":null,"slug":"learn-from-orientation-prior-for-radiograph","title":"Learn From Orientation Prior for Radiograph Super-Resolution: Orientation Operator Transformer","date":"2023-12-27","arxiv_id":"2312.16455","n_code_links":0,"syntology":null},{"paper":null,"slug":"pangu-p-enhancing-language-model","title":"PanGu-$π$: Enhancing Language Model Architectures via Nonlinearity Compensation","date":"2023-12-27","arxiv_id":"2312.17276","n_code_links":0,"syntology":null},{"paper":null,"slug":"refinenet-enhancing-text-to-image-conversion","title":"RefineNet: Enhancing Text-to-Image Conversion with High-Resolution and Detail Accuracy through Hierarchical Transformers and Progressive Refinement","date":"2023-12-27","arxiv_id":"2312.17274","n_code_links":0,"syntology":null},{"paper":null,"slug":"relationship-between-auditory-and-semantic","title":"Relationship between auditory and semantic entrainment using Deep Neural Networks (DNN)","date":"2023-12-27","arxiv_id":"2312.16599","n_code_links":0,"syntology":null},{"paper":"/paper/scrna-seq-data-clustering-by-cluster-aware","slug":"scrna-seq-data-clustering-by-cluster-aware","title":"scRNA-seq Data Clustering by Cluster-aware Iterative Contrastive Learning","date":"2023-12-27","arxiv_id":"2312.16600","n_code_links":1,"syntology":null},{"paper":null,"slug":"spatial-related-sensors-matters-3d-human","title":"Spatial-Related Sensors Matters: 3D Human Motion Reconstruction Assisted with Textual Semantics","date":"2023-12-27","arxiv_id":"2401.05412","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-aware-social-graph-transformer","title":"Attention-aware Social Graph Transformer Networks for Stochastic Trajectory Prediction","date":"2023-12-26","arxiv_id":"2312.15881","n_code_links":0,"syntology":null},{"paper":"/paper/c2t-net-channel-aware-cross-fused-transformer","slug":"c2t-net-channel-aware-cross-fused-transformer","title":"C2T-Net: Channel-Aware Cross-Fused Transformer-Style Networks for Pedestrian Attribute Recognition","date":"2023-12-26","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"chartbench-a-benchmark-for-complex-visual","title":"ChartBench: A Benchmark for Complex Visual Reasoning in Charts","date":"2023-12-26","arxiv_id":"2312.15915","n_code_links":0,"syntology":null},{"paper":"/paper/graph-context-transformation-learning-for","slug":"graph-context-transformation-learning-for","title":"Graph Context Transformation Learning for Progressive Correspondence Pruning","date":"2023-12-26","arxiv_id":"2312.15971","n_code_links":1,"syntology":null},{"paper":null,"slug":"heterogeneous-encoders-scaling-in-the","title":"Heterogeneous Encoders Scaling In The Transformer For Neural Machine Translation","date":"2023-12-26","arxiv_id":"2312.15872","n_code_links":0,"syntology":null},{"paper":"/paper/modality-collaborative-transformer-with","slug":"modality-collaborative-transformer-with","title":"Modality-Collaborative Transformer with Hybrid Feature Reconstruction for Robust Emotion Recognition","date":"2023-12-26","arxiv_id":"2312.15848","n_code_links":1,"syntology":null},{"paper":"/paper/pdit-interleaving-perception-and-decision","slug":"pdit-interleaving-perception-and-decision","title":"PDiT: Interleaving Perception and Decision-making Transformers for Deep Reinforcement Learning","date":"2023-12-26","arxiv_id":"2312.15863","n_code_links":2,"syntology":null},{"paper":"/paper/principled-instructions-are-all-you-need-for","slug":"principled-instructions-are-all-you-need-for","title":"Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4","date":"2023-12-26","arxiv_id":"2312.16171","n_code_links":2,"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":["vila-lab/atlas"],"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":"/paper/roleeval-a-bilingual-role-evaluation","slug":"roleeval-a-bilingual-role-evaluation","title":"RoleEval: A Bilingual Role Evaluation Benchmark for Large Language Models","date":"2023-12-26","arxiv_id":"2312.16132","n_code_links":1,"syntology":null},{"paper":"/paper/scaling-down-litting-up-efficient-zero-shot","slug":"scaling-down-litting-up-efficient-zero-shot","title":"Scaling Down, LiTting Up: Efficient Zero-Shot Listwise Reranking with Seq2seq Encoder-Decoder Models","date":"2023-12-26","arxiv_id":"2312.16098","n_code_links":2,"syntology":null},{"paper":"/paper/secqa-a-concise-question-answering-dataset","slug":"secqa-a-concise-question-answering-dataset","title":"SecQA: A Concise Question-Answering Dataset for Evaluating Large Language Models in Computer Security","date":"2023-12-26","arxiv_id":"2312.15838","n_code_links":1,"syntology":{"ran":6,"of":7,"n_ran_checked":5,"n_instrument":1,"unverified":1,"pointer_only":1,"phrase":"6 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; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["zefang-liu/lm-evaluation-harness"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"task-contamination-language-models-may-not-be","title":"Task Contamination: Language Models May Not Be Few-Shot Anymore","date":"2023-12-26","arxiv_id":"2312.16337","n_code_links":0,"syntology":null},{"paper":null,"slug":"compositional-generalization-in-spoken","title":"Compositional Generalization in Spoken Language Understanding","date":"2023-12-25","arxiv_id":"2312.15815","n_code_links":0,"syntology":null},{"paper":null,"slug":"esgreveal-an-llm-based-approach-for","title":"ESGReveal: An LLM-based approach for extracting structured data from ESG reports","date":"2023-12-25","arxiv_id":"2312.17264","n_code_links":0,"syntology":null},{"paper":null,"slug":"iqagpt-image-quality-assessment-with-vision","title":"IQAGPT: Image Quality Assessment with Vision-language and ChatGPT Models","date":"2023-12-25","arxiv_id":"2312.15663","n_code_links":0,"syntology":null},{"paper":null,"slug":"lifting-by-image-leveraging-image-cues-for","title":"Lifting by Image -- Leveraging Image Cues for Accurate 3D Human Pose Estimation","date":"2023-12-25","arxiv_id":"2312.15636","n_code_links":0,"syntology":null},{"paper":"/paper/nighttime-person-re-identification-via","slug":"nighttime-person-re-identification-via","title":"Nighttime Person Re-Identification via Collaborative Enhancement Network with Multi-domain Learning","date":"2023-12-25","arxiv_id":"2312.16246","n_code_links":1,"syntology":null},{"paper":null,"slug":"proximal-gradient-descent-unfolding-dense","title":"Proximal Gradient Descent Unfolding Dense-spatial Spectral-attention Transformer for Compressive Spectral Imaging","date":"2023-12-25","arxiv_id":"2312.16237","n_code_links":0,"syntology":null},{"paper":"/paper/uniref-segment-every-reference-object-in","slug":"uniref-segment-every-reference-object-in","title":"UniRef++: Segment Every Reference Object in Spatial and Temporal Spaces","date":"2023-12-25","arxiv_id":"2312.15715","n_code_links":2,"syntology":{"ran":9,"of":9,"n_ran_checked":5,"n_instrument":4,"unverified":0,"pointer_only":2,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 1 honoured, 0 violated, 4 with no contract checked; 4 where Syntology's instrument failed) · 0 unverified","official":{"repos":["foundationvision/uniref"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"word-length-aware-text-spotting-enhancing","title":"Word length-aware text spotting: Enhancing detection and recognition in dense text image","date":"2023-12-25","arxiv_id":"2312.15690","n_code_links":0,"syntology":null},{"paper":null,"slug":"deap-design-space-exploration-for-dnn","title":"DEAP: Design Space Exploration for DNN Accelerator Parallelism","date":"2023-12-24","arxiv_id":"2312.15388","n_code_links":0,"syntology":null},{"paper":null,"slug":"deformable-audio-transformer-for-audio-event","title":"Deformable Audio Transformer for Audio Event Detection","date":"2023-12-24","arxiv_id":"2312.16228","n_code_links":0,"syntology":null},{"paper":null,"slug":"diffusion-exr-controllable-review-generation","title":"Diffusion-EXR: Controllable Review Generation for Explainable Recommendation via Diffusion Models","date":"2023-12-24","arxiv_id":"2312.15490","n_code_links":0,"syntology":null},{"paper":"/paper/fairness-aware-structured-pruning-in","slug":"fairness-aware-structured-pruning-in","title":"Fairness-Aware Structured Pruning in Transformers","date":"2023-12-24","arxiv_id":"2312.15398","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":["chandar-lab/fasp"],"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":"multi-level-biomedical-ner-through-multi","title":"Multi-level biomedical NER through multi-granularity embeddings and enhanced labeling","date":"2023-12-24","arxiv_id":"2312.15550","n_code_links":0,"syntology":null},{"paper":"/paper/pointct-point-central-transformer-network-for","slug":"pointct-point-central-transformer-network-for","title":"PointCT: Point Central Transformer Network for Weakly-supervised Point Cloud Semantic Segmentation","date":"2023-12-24","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"do-llm-agents-exhibit-social-behavior","title":"Do LLM Agents Exhibit Social Behavior?","date":"2023-12-23","arxiv_id":"2312.15198","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-user-intent-capture-in-session-1","slug":"enhancing-user-intent-capture-in-session-1","title":"Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns","date":"2023-12-23","arxiv_id":"2312.16199","n_code_links":1,"syntology":{"ran":5,"of":9,"n_ran_checked":5,"n_instrument":0,"unverified":4,"pointer_only":9,"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) · 4 unverified","official":{"repos":["hkust-knowcomp/fapat"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":"/paper/multimodal-machine-learning-combining-facial","slug":"multimodal-machine-learning-combining-facial","title":"GestaltMML: Enhancing Rare Genetic Disease Diagnosis through Multimodal Machine Learning Combining Facial Images and Clinical Texts","date":"2023-12-23","arxiv_id":"2312.15320","n_code_links":2,"syntology":null},{"paper":"/paper/narrowing-the-semantic-gaps-in-u-net-with","slug":"narrowing-the-semantic-gaps-in-u-net-with","title":"Narrowing the semantic gaps in U-Net with learnable skip connections: The case of medical image segmentation","date":"2023-12-23","arxiv_id":"2312.15182","n_code_links":3,"syntology":null},{"paper":null,"slug":"paralinguistics-enhanced-large-language","title":"Paralinguistics-Enhanced Large Language Modeling of Spoken Dialogue","date":"2023-12-23","arxiv_id":"2312.15316","n_code_links":0,"syntology":null}],"record_sha256":"655c62dd65972a8fd2e5e0bd702f7f50cfb54ab37440503d161b50c681705261","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}