{"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/position-wise-feed-forward-layer/papers/9","list_of":"/method/position-wise-feed-forward-layer","method":"Position-Wise Feed-Forward Layer","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":9,"pages_in_order":139,"rows_per_page":100,"rows":[801,900],"of":13895,"counts":{"archive_papers_tagged":13895,"with_a_code_link":6514,"where_syntology_ran_a_sample":2229,"not_listed_spam_title":0,"listed":13895,"listed_where_code_ran":2229,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1902,"every_run_a_failure_of_syntologys_instrument":327,"listed_with_a_run_with_no_instrument_failure":1902,"listed_every_run_a_failure_of_syntologys_instrument":327,"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/position-wise-feed-forward-layer","prev":"/method/position-wise-feed-forward-layer/papers/8","next":"/method/position-wise-feed-forward-layer/papers/10","papers":[{"paper":"/paper/bhvit-binarized-hybrid-vision-transformer","slug":"bhvit-binarized-hybrid-vision-transformer","title":"BHViT: Binarized Hybrid Vision Transformer","date":"2025-03-04","arxiv_id":"2503.02394","n_code_links":1,"syntology":{"ran":16,"of":29,"n_ran_checked":15,"n_instrument":1,"unverified":13,"pointer_only":0,"phrase":"16 ran (of which 13 constructed an object rather than computing a result; 15 with no instrument failure: 0 honoured, 0 violated, 15 with no contract checked; 1 where Syntology's instrument failed) · 13 unverified","official":{"repos":["IMRL/BHViT"],"state":"official (archive's flag): 16 ran","n_ran":16,"n_constructed":13,"n_ran_no_instrument_failure":15,"n_unverified":13,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"coserve-efficient-collaboration-of-experts","title":"CoServe: Efficient Collaboration-of-Experts (CoE) Model Inference with Limited Memory","date":"2025-03-04","arxiv_id":"2503.02354","n_code_links":0,"syntology":null},{"paper":null,"slug":"developing-a-pet-ct-foundation-model-for","title":"Developing a PET/CT Foundation Model for Cross-Modal Anatomical and Functional Imaging","date":"2025-03-04","arxiv_id":"2503.02824","n_code_links":0,"syntology":null},{"paper":null,"slug":"fouriernat-a-fourier-mixing-based-non","title":"FourierNAT: A Fourier-Mixing-Based Non-Autoregressive Transformer for Parallel Sequence Generation","date":"2025-03-04","arxiv_id":"2503.07630","n_code_links":0,"syntology":null},{"paper":"/paper/graph-transformer-with-disease-subgraph","slug":"graph-transformer-with-disease-subgraph","title":"Graph Transformer with Disease Subgraph Positional Encoding for Improved Comorbidity Prediction","date":"2025-03-04","arxiv_id":"2503.03046","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-precoding-in-multi-user-multi","title":"Learning Precoding in Multi-user Multi-antenna Systems: Transformer or Graph Transformer?","date":"2025-03-04","arxiv_id":"2503.02998","n_code_links":0,"syntology":null},{"paper":null,"slug":"network-traffic-classification-using-machine","title":"Network Traffic Classification Using Machine Learning, Transformer, and Large Language Models","date":"2025-03-04","arxiv_id":"2503.02141","n_code_links":0,"syntology":null},{"paper":null,"slug":"tabby-tabular-data-synthesis-with-language","title":"Tabby: Tabular Data Synthesis with Language Models","date":"2025-03-04","arxiv_id":"2503.02152","n_code_links":0,"syntology":null},{"paper":null,"slug":"target-return-optimizer-for-multi-game","title":"Target Return Optimizer for Multi-Game Decision Transformer","date":"2025-03-04","arxiv_id":"2503.02311","n_code_links":0,"syntology":null},{"paper":null,"slug":"tetra-vpr-a-ternary-transformer-approach-for","title":"TeTRA-VPR: A Ternary Transformer Approach for Compact Visual Place Recognition","date":"2025-03-04","arxiv_id":"2503.02511","n_code_links":0,"syntology":null},{"paper":null,"slug":"weak-to-strong-generalization-even-in-random","title":"Weak-to-Strong Generalization Even in Random Feature Networks, Provably","date":"2025-03-04","arxiv_id":"2503.02877","n_code_links":0,"syntology":null},{"paper":"/paper/wyckoff-transformer-generation-of-symmetric","slug":"wyckoff-transformer-generation-of-symmetric","title":"Wyckoff Transformer: Generation of Symmetric Crystals","date":"2025-03-04","arxiv_id":"2503.02407","n_code_links":1,"syntology":null},{"paper":"/paper/2503-01306","slug":"2503-01306","title":"From Claims to Evidence: A Unified Framework and Critical Analysis of CNN vs. Transformer vs. Mamba in Medical Image Segmentation","date":"2025-03-03","arxiv_id":"2503.01306","n_code_links":1,"syntology":null},{"paper":null,"slug":"2503-01458","title":"SrSv: Integrating Sequential Rollouts with Sequential Value Estimation for Multi-agent Reinforcement Learning","date":"2025-03-03","arxiv_id":"2503.01458","n_code_links":0,"syntology":null},{"paper":null,"slug":"2503-01592","title":"An Efficient Approach to Detecting Lung Nodules Using Swin Transformer","date":"2025-03-03","arxiv_id":"2503.01592","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-hybrid-cnn-transformer-model-for-heart","title":"A Hybrid CNN-Transformer Model for Heart Disease Prediction Using Life History Data","date":"2025-03-03","arxiv_id":"2503.02124","n_code_links":0,"syntology":null},{"paper":"/paper/architectural-and-inferential-inductive","slug":"architectural-and-inferential-inductive","title":"Architectural and Inferential Inductive Biases For Exchangeable Sequence Modeling","date":"2025-03-03","arxiv_id":"2503.01215","n_code_links":1,"syntology":null},{"paper":null,"slug":"asktoact-enhancing-llms-tool-use-via-self","title":"AskToAct: Enhancing LLMs Tool Use via Self-Correcting Clarification","date":"2025-03-03","arxiv_id":"2503.01940","n_code_links":0,"syntology":null},{"paper":null,"slug":"dementia-insights-a-context-based-multimodal","title":"Dementia Insights: A Context-Based MultiModal Approach","date":"2025-03-03","arxiv_id":"2503.01226","n_code_links":0,"syntology":null},{"paper":"/paper/forgetting-transformer-softmax-attention-with","slug":"forgetting-transformer-softmax-attention-with","title":"Forgetting Transformer: Softmax Attention with a Forget Gate","date":"2025-03-03","arxiv_id":"2503.02130","n_code_links":1,"syntology":{"ran":11,"of":13,"n_ran_checked":9,"n_instrument":2,"unverified":2,"pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["zhixuan-lin/forgetting-transformer"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"hierarchical-causal-transformer-with","title":"HeterRec: Heterogeneous Information Transformer for Scalable Sequential Recommendation","date":"2025-03-03","arxiv_id":"2503.01469","n_code_links":0,"syntology":null},{"paper":"/paper/how-simple-can-you-go-an-off-the-shelf","slug":"how-simple-can-you-go-an-off-the-shelf","title":"How simple can you go? An off-the-shelf transformer approach to molecular dynamics","date":"2025-03-03","arxiv_id":"2503.01431","n_code_links":1,"syntology":null},{"paper":"/paper/interactive-gadolinium-free-mri-synthesis-a","slug":"interactive-gadolinium-free-mri-synthesis-a","title":"Interactive Gadolinium-Free MRI Synthesis: A Transformer with Localization Prompt Learning","date":"2025-03-03","arxiv_id":"2503.01265","n_code_links":1,"syntology":null},{"paper":null,"slug":"meshpad-interactive-sketch-conditioned","title":"MeshPad: Interactive Sketch-Conditioned Artist-Designed Mesh Generation and Editing","date":"2025-03-03","arxiv_id":"2503.01425","n_code_links":0,"syntology":null},{"paper":null,"slug":"primus-enforcing-attention-usage-for-3d","title":"Primus: Enforcing Attention Usage for 3D Medical Image Segmentation","date":"2025-03-03","arxiv_id":"2503.01835","n_code_links":0,"syntology":null},{"paper":null,"slug":"streaming-piano-transcription-based-on","title":"Streaming Piano Transcription Based on Consistent Onset and Offset Decoding with Sustain Pedal Detection","date":"2025-03-03","arxiv_id":"2503.01362","n_code_links":0,"syntology":null},{"paper":null,"slug":"syntactic-learnability-of-echo-state-neural","title":"Syntactic Learnability of Echo State Neural Language Models at Scale","date":"2025-03-03","arxiv_id":"2503.01724","n_code_links":0,"syntology":null},{"paper":null,"slug":"unify-and-anchor-a-context-aware-transformer","title":"Unify and Anchor: A Context-Aware Transformer for Cross-Domain Time Series Forecasting","date":"2025-03-03","arxiv_id":"2503.01157","n_code_links":0,"syntology":null},{"paper":null,"slug":"vikanformer-embedding-kolmogorov-arnold","title":"ViKANformer: Embedding Kolmogorov Arnold Networks in Vision Transformers for Pattern-Based Learning","date":"2025-03-03","arxiv_id":"2503.01124","n_code_links":0,"syntology":null},{"paper":"/paper/training-free-dataset-pruning-for-instance","slug":"training-free-dataset-pruning-for-instance","title":"Training-Free Dataset Pruning for Instance Segmentation","date":"2025-03-02","arxiv_id":"2503.00828","n_code_links":1,"syntology":{"ran":5,"of":8,"n_ran_checked":1,"n_instrument":4,"unverified":3,"pointer_only":8,"phrase":"5 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; 4 where Syntology's instrument failed) · 3 unverified","official":{"repos":["he-y/dataset-pruning-for-instance-segmentation"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"unmasking-digital-falsehoods-a-comparative","title":"Unmasking Digital Falsehoods: A Comparative Analysis of LLM-Based Misinformation Detection Strategies","date":"2025-03-02","arxiv_id":"2503.00724","n_code_links":0,"syntology":null},{"paper":"/paper/2503-00455","slug":"2503-00455","title":"PodAgent: A Comprehensive Framework for Podcast Generation","date":"2025-03-01","arxiv_id":"2503.00455","n_code_links":1,"syntology":null},{"paper":null,"slug":"cross-attention-fusion-of-mri-and-jacobian","title":"Cross-Attention Fusion of MRI and Jacobian Maps for Alzheimer's Disease Diagnosis","date":"2025-03-01","arxiv_id":"2503.00586","n_code_links":0,"syntology":null},{"paper":null,"slug":"psychological-counseling-ability-of-large","title":"Psychological Counseling Ability of Large Language Models","date":"2025-03-01","arxiv_id":"2503.07627","n_code_links":0,"syntology":null},{"paper":null,"slug":"using-machine-learning-for-move-sequence","title":"Using Machine Learning for move sequence visualization and generation in climbing","date":"2025-03-01","arxiv_id":"2503.00458","n_code_links":0,"syntology":null},{"paper":"/paper/2502-21309","slug":"2502-21309","title":"FANformer: Improving Large Language Models Through Effective Periodicity Modeling","date":"2025-02-28","arxiv_id":"2502.21309","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":0,"n_instrument":2,"unverified":1,"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) · 1 unverified","official":{"repos":["yihongdong/fanformer"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/a-novel-fourier-adjacency-transformer-for","slug":"a-novel-fourier-adjacency-transformer-for","title":"A novel Fourier Adjacency Transformer for advanced EEG emotion recognition","date":"2025-02-28","arxiv_id":"2503.13465","n_code_links":1,"syntology":{"ran":11,"of":14,"n_ran_checked":11,"n_instrument":0,"unverified":3,"pointer_only":0,"phrase":"11 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 1 honoured, 0 violated, 10 with no contract checked; 0 where Syntology's instrument failed) · 3 unverified","official":{"repos":["YanhaoHuang23/FAT"],"state":"official (archive's flag): 11 ran","n_ran":11,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/bst-badminton-stroke-type-transformer-for","slug":"bst-badminton-stroke-type-transformer-for","title":"BST: Badminton Stroke-type Transformer for Skeleton-based Action Recognition in Racket Sports","date":"2025-02-28","arxiv_id":"2502.21085","n_code_links":1,"syntology":null},{"paper":"/paper/faster-focal-token-acquiring-and-scaling","slug":"faster-focal-token-acquiring-and-scaling","title":"FASTer: Focal Token Acquiring-and-Scaling Transformer for Long-term 3D Object Detection","date":"2025-02-28","arxiv_id":"2503.01899","n_code_links":1,"syntology":null},{"paper":"/paper/jitter-jigsaw-temporal-transformer-for-event","slug":"jitter-jigsaw-temporal-transformer-for-event","title":"JiTTER: Jigsaw Temporal Transformer for Event Reconstruction for Self-Supervised Sound Event Detection","date":"2025-02-28","arxiv_id":"2502.20857","n_code_links":1,"syntology":null},{"paper":null,"slug":"solar-multimodal-transformer-intraday-solar","title":"Solar Multimodal Transformer: Intraday Solar Irradiance Predictor using Public Cameras and Time Series","date":"2025-02-28","arxiv_id":"2503.00250","n_code_links":0,"syntology":null},{"paper":null,"slug":"spiking-transformer-introducing-accurate","title":"Spiking Transformer:Introducing Accurate Addition-Only Spiking Self-Attention for Transformer","date":"2025-02-28","arxiv_id":"2503.00226","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-integrated-deep-learning-framework","title":"An Integrated Deep Learning Framework Leveraging NASNet and Vision Transformer with MixProcessing for Accurate and Precise Diagnosis of Lung Diseases","date":"2025-02-27","arxiv_id":"2502.20570","n_code_links":0,"syntology":null},{"paper":"/paper/cirt-global-subseasonal-to-seasonal","slug":"cirt-global-subseasonal-to-seasonal","title":"CirT: Global Subseasonal-to-Seasonal Forecasting with Geometry-inspired Transformer","date":"2025-02-27","arxiv_id":"2502.19750","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":["compasszzn/CirT"],"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":"cnsum-automatic-summarization-for-chinese","title":"CNsum:Automatic Summarization for Chinese News Text","date":"2025-02-27","arxiv_id":"2502.19723","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-3d-gaze-estimation-in-the-wild","title":"Enhancing 3D Gaze Estimation in the Wild using Weak Supervision with Gaze Following Labels","date":"2025-02-27","arxiv_id":"2502.20249","n_code_links":0,"syntology":null},{"paper":null,"slug":"minds-on-the-move-decoding-trajectory","title":"Minds on the Move: Decoding Trajectory Prediction in Autonomous Driving with Cognitive Insights","date":"2025-02-27","arxiv_id":"2502.20084","n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-representation-alignment-for-image","slug":"multimodal-representation-alignment-for-image","title":"Multimodal Representation Alignment for Image Generation: Text-Image Interleaved Control Is Easier Than You Think","date":"2025-02-27","arxiv_id":"2502.20172","n_code_links":1,"syntology":null},{"paper":null,"slug":"qort-former-query-optimized-real-time","title":"QORT-Former: Query-optimized Real-time Transformer for Understanding Two Hands Manipulating Objects","date":"2025-02-27","arxiv_id":"2502.19769","n_code_links":0,"syntology":null},{"paper":null,"slug":"regional-climate-projections-using-a-deep","title":"Regional climate projections using a deep-learning-based model-ranking and downscaling framework: Application to European climate zones","date":"2025-02-27","arxiv_id":"2502.20132","n_code_links":0,"syntology":null},{"paper":null,"slug":"revisit-the-stability-of-vanilla-federated","title":"Revisit the Stability of Vanilla Federated Learning Under Diverse Conditions","date":"2025-02-27","arxiv_id":"2502.19849","n_code_links":0,"syntology":null},{"paper":null,"slug":"thinking-slow-fast-scaling-inference-compute","title":"Thinking Slow, Fast: Scaling Inference Compute with Distilled Reasoners","date":"2025-02-27","arxiv_id":"2502.20339","n_code_links":0,"syntology":null},{"paper":"/paper/walnutdata-a-uav-remote-sensing-dataset-of","slug":"walnutdata-a-uav-remote-sensing-dataset-of","title":"WalnutData: A UAV Remote Sensing Dataset of Green Walnuts and Model Evaluation","date":"2025-02-27","arxiv_id":"2502.20092","n_code_links":1,"syntology":null},{"paper":"/paper/a-sliding-layer-merging-method-for-efficient","slug":"a-sliding-layer-merging-method-for-efficient","title":"A Sliding Layer Merging Method for Efficient Depth-Wise Pruning in LLMs","date":"2025-02-26","arxiv_id":"2502.19159","n_code_links":1,"syntology":null},{"paper":"/paper/akdt-adaptive-kernel-dilation-transformer-for","slug":"akdt-adaptive-kernel-dilation-transformer-for","title":"AKDT: Adaptive Kernel Dilation Transformer for Effective Image Denoising","date":"2025-02-26","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"brain-inspired-analogical-mixture-prototypes","title":"Brain-inspired analogical mixture prototypes for few-shot class-incremental learning","date":"2025-02-26","arxiv_id":"2502.18923","n_code_links":0,"syntology":null},{"paper":null,"slug":"clip-tts-contrastive-text-content-and-mel","title":"Clip-TTS: Contrastive Text-content and Mel-spectrogram, A High-Quality Text-to-Speech Method based on Contextual Semantic Understanding","date":"2025-02-26","arxiv_id":"2502.18889","n_code_links":0,"syntology":null},{"paper":null,"slug":"cs-dialogue-a-104-hour-dataset-of-spontaneous","title":"CS-Dialogue: A 104-Hour Dataset of Spontaneous Mandarin-English Code-Switching Dialogues for Speech Recognition","date":"2025-02-26","arxiv_id":"2502.18913","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhanced-transformer-based-tracking-for","title":"Enhanced Transformer-Based Tracking for Skiing Events: Overcoming Multi-Camera Challenges, Scale Variations and Rapid Motion -- SkiTB Visual Tracking Challenge 2025","date":"2025-02-26","arxiv_id":"2502.18867","n_code_links":0,"syntology":null},{"paper":null,"slug":"genotype-to-phenotype-prediction-in-rice-with","title":"Genotype-to-Phenotype Prediction in Rice with High-Dimensional Nonlinear Features","date":"2025-02-26","arxiv_id":"2502.18758","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-to-align-multi-faceted-evaluation-a","title":"Learning to Align Multi-Faceted Evaluation: A Unified and Robust Framework","date":"2025-02-26","arxiv_id":"2502.18874","n_code_links":0,"syntology":null},{"paper":null,"slug":"mebench-benchmarking-large-language-models","title":"MEBench: Benchmarking Large Language Models for Cross-Document Multi-Entity Question Answering","date":"2025-02-26","arxiv_id":"2502.18993","n_code_links":0,"syntology":null},{"paper":null,"slug":"reimagining-personal-data-unlocking-the","title":"Reimagining Personal Data: Unlocking the Potential of AI-Generated Images in Personal Data Meaning-Making","date":"2025-02-26","arxiv_id":"2502.18853","n_code_links":0,"syntology":null},{"paper":null,"slug":"weaker-llms-opinions-also-matter-mixture-of","title":"Weaker LLMs' Opinions Also Matter: Mixture of Opinions Enhances LLM's Mathematical Reasoning","date":"2025-02-26","arxiv_id":"2502.19622","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-fusion-model-for-art-style-and-author","title":"A Fusion Model for Art Style and Author Recognition Based on Convolutional Neural Networks and Transformers","date":"2025-02-25","arxiv_id":"2502.18083","n_code_links":0,"syntology":null},{"paper":"/paper/art-anonymous-region-transformer-for-variable","slug":"art-anonymous-region-transformer-for-variable","title":"ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image Generation","date":"2025-02-25","arxiv_id":"2502.18364","n_code_links":1,"syntology":{"ran":13,"of":14,"n_ran_checked":12,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"13 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; 1 where Syntology's instrument failed) · 1 unverified","official":null}},{"paper":null,"slug":"assessing-large-language-models-in-agentic","title":"Assessing Large Language Models in Agentic Multilingual National Bias","date":"2025-02-25","arxiv_id":"2502.17945","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-vehicle-detection-using-detr-a","title":"Automatic Vehicle Detection using DETR: A Transformer-Based Approach for Navigating Treacherous Roads","date":"2025-02-25","arxiv_id":"2502.17843","n_code_links":0,"syntology":null},{"paper":null,"slug":"bayesian-optimization-for-controlled-image","title":"Bayesian Optimization for Controlled Image Editing via LLMs","date":"2025-02-25","arxiv_id":"2502.18116","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-speech-quality-through-the","title":"Enhancing Speech Quality through the Integration of BGRU and Transformer Architectures","date":"2025-02-25","arxiv_id":"2502.17911","n_code_links":0,"syntology":null},{"paper":null,"slug":"examining-the-threat-landscape-foundation","title":"Examining the Threat Landscape: Foundation Models and Model Stealing","date":"2025-02-25","arxiv_id":"2502.18077","n_code_links":0,"syntology":null},{"paper":null,"slug":"h-fltn-a-privacy-preserving-hierarchical","title":"H-FLTN: A Privacy-Preserving Hierarchical Framework for Electric Vehicle Spatio-Temporal Charge Prediction","date":"2025-02-25","arxiv_id":"2502.18697","n_code_links":0,"syntology":null},{"paper":null,"slug":"lam-large-avatar-model-for-one-shot","title":"LAM: Large Avatar Model for One-shot Animatable Gaussian Head","date":"2025-02-25","arxiv_id":"2502.17796","n_code_links":0,"syntology":null},{"paper":"/paper/learning-structure-supporting-dependencies","slug":"learning-structure-supporting-dependencies","title":"Learning Structure-Supporting Dependencies via Keypoint Interactive Transformer for General Mammal Pose Estimation","date":"2025-02-25","arxiv_id":"2502.18214","n_code_links":1,"syntology":null},{"paper":null,"slug":"self-adjust-softmax","title":"Self-Adjust Softmax","date":"2025-02-25","arxiv_id":"2502.18277","n_code_links":0,"syntology":null},{"paper":null,"slug":"stackelberg-game-preference-optimization-for","title":"Stackelberg Game Preference Optimization for Data-Efficient Alignment of Language Models","date":"2025-02-25","arxiv_id":"2502.18099","n_code_links":0,"syntology":null},{"paper":null,"slug":"applying-llms-to-active-learning-towards-cost","title":"Applying LLMs to Active Learning: Towards Cost-Efficient Cross-Task Text Classification without Manually Labeled Data","date":"2025-02-24","arxiv_id":"2502.16892","n_code_links":0,"syntology":null},{"paper":null,"slug":"are-large-language-models-good-data","title":"Are Large Language Models Good Data Preprocessors?","date":"2025-02-24","arxiv_id":"2502.16790","n_code_links":0,"syntology":null},{"paper":null,"slug":"atten-transformer-a-deep-learning-framework","title":"Atten-Transformer: A Deep Learning Framework for User App Usage Prediction","date":"2025-02-24","arxiv_id":"2502.16957","n_code_links":0,"syntology":null},{"paper":"/paper/calibrefine-deep-learning-based-online","slug":"calibrefine-deep-learning-based-online","title":"CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-Refinement","date":"2025-02-24","arxiv_id":"2502.17648","n_code_links":1,"syntology":null},{"paper":"/paper/cipherprune-efficient-and-scalable-private","slug":"cipherprune-efficient-and-scalable-private","title":"CipherPrune: Efficient and Scalable Private Transformer Inference","date":"2025-02-24","arxiv_id":"2502.16782","n_code_links":1,"syntology":{"ran":3,"of":9,"n_ran_checked":3,"n_instrument":0,"unverified":6,"pointer_only":9,"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) · 6 unverified","official":{"repos":["ucf-lou-lab-pet/cipher-prune-inference"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":6,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"dimitra-audio-driven-diffusion-model-for","title":"Dimitra: Audio-driven Diffusion model for Expressive Talking Head Generation","date":"2025-02-24","arxiv_id":"2502.17198","n_code_links":0,"syntology":null},{"paper":null,"slug":"disentangling-visual-transformers-patch-level","title":"Disentangling Visual Transformers: Patch-level Interpretability for Image Classification","date":"2025-02-24","arxiv_id":"2502.17196","n_code_links":0,"syntology":null},{"paper":null,"slug":"enact-heart-ensemble-based-assessment-using","title":"ENACT-Heart -- ENsemble-based Assessment Using CNN and Transformer on Heart Sounds","date":"2025-02-24","arxiv_id":"2502.16914","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-image-matting-in-real-world-scenes","title":"Enhancing Image Matting in Real-World Scenes with Mask-Guided Iterative Refinement","date":"2025-02-24","arxiv_id":"2502.17093","n_code_links":0,"syntology":null},{"paper":null,"slug":"gaussianflowocc-sparse-and-weakly-supervised","title":"GaussianFlowOcc: Sparse and Weakly Supervised Occupancy Estimation using Gaussian Splatting and Temporal Flow","date":"2025-02-24","arxiv_id":"2502.17288","n_code_links":0,"syntology":null},{"paper":null,"slug":"llm-inference-acceleration-via-efficient","title":"LLM Inference Acceleration via Efficient Operation Fusion","date":"2025-02-24","arxiv_id":"2502.17728","n_code_links":0,"syntology":null},{"paper":null,"slug":"logic-haystacks-probing-llms-long-context","title":"Logic Haystacks: Probing LLMs Long-Context Logical Reasoning (Without Easily Identifiable Unrelated Padding)","date":"2025-02-24","arxiv_id":"2502.17169","n_code_links":0,"syntology":null},{"paper":"/paper/maxglavit-a-novel-lightweight-vision","slug":"maxglavit-a-novel-lightweight-vision","title":"MaxGlaViT: A novel lightweight vision transformer-based approach for early diagnosis of glaucoma stages from fundus images","date":"2025-02-24","arxiv_id":"2502.17154","n_code_links":1,"syntology":null},{"paper":null,"slug":"mdn-mamba-driven-dualstream-network-for","title":"MDN: Mamba-Driven Dualstream Network For Medical Hyperspectral Image Segmentation","date":"2025-02-24","arxiv_id":"2502.17255","n_code_links":0,"syntology":null},{"paper":"/paper/unraveling-the-geometry-of-visual-relational","slug":"unraveling-the-geometry-of-visual-relational","title":"Unraveling the geometry of visual relational reasoning","date":"2025-02-24","arxiv_id":"2502.17382","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-split-window-transformer-for-multi-model","title":"A Split-Window Transformer for Multi-Model Sequence Spammer Detection using Multi-Model Variational Autoencoder","date":"2025-02-23","arxiv_id":"2502.16483","n_code_links":0,"syntology":null},{"paper":"/paper/aeroreformer-aerial-referring-transformer-for","slug":"aeroreformer-aerial-referring-transformer-for","title":"AeroReformer: Aerial Referring Transformer for UAV-based Referring Image Segmentation","date":"2025-02-23","arxiv_id":"2502.16680","n_code_links":1,"syntology":null},{"paper":"/paper/co-mtp-a-cooperative-trajectory-prediction","slug":"co-mtp-a-cooperative-trajectory-prediction","title":"Co-MTP: A Cooperative Trajectory Prediction Framework with Multi-Temporal Fusion for Autonomous Driving","date":"2025-02-23","arxiv_id":"2502.16589","n_code_links":1,"syntology":null},{"paper":"/paper/gs-transunet-integrated-2d-gaussian-splatting","slug":"gs-transunet-integrated-2d-gaussian-splatting","title":"GS-TransUNet: Integrated 2D Gaussian Splatting and Transformer UNet for Accurate Skin Lesion Analysis","date":"2025-02-23","arxiv_id":"2502.16748","n_code_links":1,"syntology":null},{"paper":"/paper/pmat-optimizing-action-generation-order-in","slug":"pmat-optimizing-action-generation-order-in","title":"PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement Learning","date":"2025-02-23","arxiv_id":"2502.16496","n_code_links":1,"syntology":null},{"paper":"/paper/vpnext-rethinking-dense-decoding-for-plain","slug":"vpnext-rethinking-dense-decoding-for-plain","title":"VPNeXt -- Rethinking Dense Decoding for Plain Vision Transformer","date":"2025-02-23","arxiv_id":"2502.16654","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-llms-for-identifying-and","title":"Enhancing LLMs for Identifying and Prioritizing Important Medical Jargons from Electronic Health Record Notes Utilizing Data Augmentation","date":"2025-02-22","arxiv_id":"2502.16022","n_code_links":0,"syntology":null},{"paper":null,"slug":"uncertainty-aware-fusion-an-ensemble","title":"Uncertainty-Aware Fusion: An Ensemble Framework for Mitigating Hallucinations in Large Language Models","date":"2025-02-22","arxiv_id":"2503.05757","n_code_links":0,"syntology":null},{"paper":null,"slug":"auto-bench-an-automated-benchmark-for","title":"Auto-Bench: An Automated Benchmark for Scientific Discovery in LLMs","date":"2025-02-21","arxiv_id":"2502.15224","n_code_links":0,"syntology":null}],"record_sha256":"1eef1077495ab6fed9036cccae4621d2528b7affa19098abd7047d0056c019d3","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}