{"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/31","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":31,"pages_in_order":139,"rows_per_page":100,"rows":[3001,3100],"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/30","next":"/method/position-wise-feed-forward-layer/papers/32","papers":[{"paper":null,"slug":"2408-00329","title":"OTAD: An Optimal Transport-Induced Robust Model for Agnostic Adversarial Attack","date":"2024-08-01","arxiv_id":"2408.00329","n_code_links":0,"syntology":null},{"paper":null,"slug":"2408-00749","title":"Leaf Angle Estimation using Mask R-CNN and LETR Vision Transformer","date":"2024-08-01","arxiv_id":"2408.00749","n_code_links":0,"syntology":null},{"paper":"/paper/2408-00764","slug":"2408-00764","title":"AgentGen: Enhancing Planning Abilities for Large Language Model based Agent via Environment and Task Generation","date":"2024-08-01","arxiv_id":"2408.00764","n_code_links":1,"syntology":{"ran":5,"of":9,"n_ran_checked":5,"n_instrument":0,"unverified":4,"pointer_only":0,"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":["lazychih114/AgentGen-Reproduction"],"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":null,"slug":"2408-00914","title":"Granting GPT-4 License and Opportunity: Enhancing Accuracy and Confidence Estimation for Few-Shot Event Detection","date":"2024-08-01","arxiv_id":"2408.00914","n_code_links":0,"syntology":null},{"paper":"/paper/3d-u-kan-implementation-for-multi-modal-mri","slug":"3d-u-kan-implementation-for-multi-modal-mri","title":"UKAN-EP: Enhancing U-KAN with Efficient Attention and Pyramid Aggregation for 3D Multi-Modal MRI Brain Tumor Segmentation","date":"2024-08-01","arxiv_id":"2408.00273","n_code_links":1,"syntology":null},{"paper":"/paper/advancing-medical-image-segmentation","slug":"advancing-medical-image-segmentation","title":"Advancing Medical Image Segmentation: Morphology-Driven Learning with Diffusion Transformer","date":"2024-08-01","arxiv_id":"2408.00347","n_code_links":1,"syntology":null},{"paper":"/paper/dntextspotter-arbitrary-shaped-scene-text","slug":"dntextspotter-arbitrary-shaped-scene-text","title":"DNTextSpotter: Arbitrary-Shaped Scene Text Spotting via Improved Denoising Training","date":"2024-08-01","arxiv_id":"2408.00355","n_code_links":1,"syntology":null},{"paper":null,"slug":"empowering-snapshot-compressive-imaging","title":"Cross-Scan Mamba with Masked Training for Robust Spectral Imaging","date":"2024-08-01","arxiv_id":"2408.00629","n_code_links":0,"syntology":null},{"paper":null,"slug":"hybrid-querying-over-relational-databases-and","title":"Hybrid Querying Over Relational Databases and Large Language Models","date":"2024-08-01","arxiv_id":"2408.00884","n_code_links":0,"syntology":null},{"paper":"/paper/segstitch-multidimensional-transformer-for","slug":"segstitch-multidimensional-transformer-for","title":"SegStitch: Multidimensional Transformer for Robust and Efficient Medical Imaging Segmentation","date":"2024-08-01","arxiv_id":"2408.00496","n_code_links":1,"syntology":null},{"paper":null,"slug":"2407-21276","title":"Multi-Level Querying using A Knowledge Pyramid","date":"2024-07-31","arxiv_id":"2407.21276","n_code_links":0,"syntology":null},{"paper":null,"slug":"2407-21328","title":"Knowledge-Guided Prompt Learning for Lifespan Brain MR Image Segmentation","date":"2024-07-31","arxiv_id":"2407.21328","n_code_links":0,"syntology":null},{"paper":null,"slug":"2407-21507","title":"FSSC: Federated Learning of Transformer Neural Networks for Semantic Image Communication","date":"2024-07-31","arxiv_id":"2407.21507","n_code_links":0,"syntology":null},{"paper":null,"slug":"2407-21512","title":"Interpreting and learning voice commands with a Large Language Model for a robot system","date":"2024-07-31","arxiv_id":"2407.21512","n_code_links":0,"syntology":null},{"paper":null,"slug":"2407-21531","title":"Can LLMs \"Reason\" in Music? An Evaluation of LLMs' Capability of Music Understanding and Generation","date":"2024-07-31","arxiv_id":"2407.21531","n_code_links":0,"syntology":null},{"paper":null,"slug":"2407-21571","title":"PMoE: Progressive Mixture of Experts with Asymmetric Transformer for Continual Learning","date":"2024-07-31","arxiv_id":"2407.21571","n_code_links":0,"syntology":null},{"paper":null,"slug":"2407-21687","title":"Dynamic Object Queries for Transformer-based Incremental Object Detection","date":"2024-07-31","arxiv_id":"2407.21687","n_code_links":0,"syntology":null},{"paper":null,"slug":"2408-00118","title":"Gemma 2: Improving Open Language Models at a Practical Size","date":"2024-07-31","arxiv_id":"2408.00118","n_code_links":0,"syntology":null},{"paper":null,"slug":"2408-00197","title":"Automated Software Vulnerability Static Code Analysis Using Generative Pre-Trained Transformer Models","date":"2024-07-31","arxiv_id":"2408.00197","n_code_links":0,"syntology":null},{"paper":"/paper/a-simple-low-bit-quantization-framework-for","slug":"a-simple-low-bit-quantization-framework-for","title":"A Simple Low-bit Quantization Framework for Video Snapshot Compressive Imaging","date":"2024-07-31","arxiv_id":"2407.21517","n_code_links":1,"syntology":null},{"paper":"/paper/beat-this-accurate-beat-tracking-without-dbn","slug":"beat-this-accurate-beat-tracking-without-dbn","title":"Beat this! Accurate beat tracking without DBN postprocessing","date":"2024-07-31","arxiv_id":"2407.21658","n_code_links":1,"syntology":null},{"paper":null,"slug":"cc-sam-sam-with-cross-feature-attention-and","title":"CC-SAM: SAM with Cross-feature Attention and Context for Ultrasound Image Segmentation","date":"2024-07-31","arxiv_id":"2408.00181","n_code_links":0,"syntology":null},{"paper":"/paper/mart-multiscale-relational-transformer","slug":"mart-multiscale-relational-transformer","title":"MART: MultiscAle Relational Transformer Networks for Multi-agent Trajectory Prediction","date":"2024-07-31","arxiv_id":"2407.21635","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-fly-point-feature-representation-for","title":"On-the-fly Point Feature Representation for Point Clouds Analysis","date":"2024-07-31","arxiv_id":"2407.21335","n_code_links":0,"syntology":null},{"paper":"/paper/roadformer-delivering-rgb-x-scene-parsing","slug":"roadformer-delivering-rgb-x-scene-parsing","title":"RoadFormer+: Delivering RGB-X Scene Parsing through Scale-Aware Information Decoupling and Advanced Heterogeneous Feature Fusion","date":"2024-07-31","arxiv_id":"2407.21631","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantic-successive-refinement-a-generative","title":"Semantic Successive Refinement: A Generative AI-aided Semantic Communication Framework","date":"2024-07-31","arxiv_id":"2408.05112","n_code_links":0,"syntology":null},{"paper":"/paper/the-llama-3-herd-of-models","slug":"the-llama-3-herd-of-models","title":"The Llama 3 Herd of Models","date":"2024-07-31","arxiv_id":"2407.21783","n_code_links":5,"syntology":{"ran":9,"of":9,"n_ran_checked":8,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 1 violated, 7 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":null}},{"paper":"/paper/tora-trajectory-oriented-diffusion","slug":"tora-trajectory-oriented-diffusion","title":"Tora: Trajectory-oriented Diffusion Transformer for Video Generation","date":"2024-07-31","arxiv_id":"2407.21705","n_code_links":1,"syntology":{"ran":9,"of":12,"n_ran_checked":7,"n_instrument":2,"unverified":3,"pointer_only":0,"phrase":"9 ran (of which 4 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 1 violated, 6 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["alibaba/Tora"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":4,"n_ran_no_instrument_failure":7,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/2407-21124","slug":"2407-21124","title":"Zero Shot Health Trajectory Prediction Using Transformer","date":"2024-07-30","arxiv_id":"2407.21124","n_code_links":1,"syntology":{"ran":3,"of":6,"n_ran_checked":3,"n_instrument":0,"unverified":3,"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) · 3 unverified","official":{"repos":["ipolharvard/ethos-paper"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/2407-21191","slug":"2407-21191","title":"GenRec: Generative Sequential Recommendation with Large Language Models","date":"2024-07-30","arxiv_id":"2407.21191","n_code_links":1,"syntology":null},{"paper":null,"slug":"be-aware-of-overfitting-by-hyperparameter","title":"Be aware of overfitting by hyperparameter optimization!","date":"2024-07-30","arxiv_id":"2407.20786","n_code_links":0,"syntology":null},{"paper":null,"slug":"bert-and-llms-based-avgfp-brightness","title":"BERT and LLMs-Based avGFP Brightness Prediction and Mutation Design","date":"2024-07-30","arxiv_id":"2407.20534","n_code_links":0,"syntology":null},{"paper":null,"slug":"breaking-agents-compromising-autonomous-llm","title":"Breaking Agents: Compromising Autonomous LLM Agents Through Malfunction Amplification","date":"2024-07-30","arxiv_id":"2407.20859","n_code_links":0,"syntology":null},{"paper":"/paper/effectively-leveraging-clip-for-generating","slug":"effectively-leveraging-clip-for-generating","title":"Effectively Leveraging CLIP for Generating Situational Summaries of Images and Videos","date":"2024-07-30","arxiv_id":"2407.20642","n_code_links":1,"syntology":null},{"paper":null,"slug":"enhancing-agricultural-machinery-management","title":"Enhancing Agricultural Machinery Management through Advanced LLM Integration","date":"2024-07-30","arxiv_id":"2407.20588","n_code_links":0,"syntology":null},{"paper":"/paper/handdagt-a-denoising-adaptive-graph","slug":"handdagt-a-denoising-adaptive-graph","title":"HandDAGT: A Denoising Adaptive Graph Transformer for 3D Hand Pose Estimation","date":"2024-07-30","arxiv_id":"2407.20542","n_code_links":1,"syntology":null},{"paper":null,"slug":"mimicking-the-mavens-agent-based-opinion","title":"Mimicking the Mavens: Agent-based Opinion Synthesis and Emotion Prediction for Social Media Influencers","date":"2024-07-30","arxiv_id":"2407.20668","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-load-prediction-of-power-network","title":"Robust Load Prediction of Power Network Clusters Based on Cloud-Model-Improved Transformer","date":"2024-07-30","arxiv_id":"2407.20817","n_code_links":0,"syntology":null},{"paper":null,"slug":"spotformer-multi-scale-spatio-temporal","title":"SpotFormer: Multi-Scale Spatio-Temporal Transformer for Facial Expression Spotting","date":"2024-07-30","arxiv_id":"2407.20799","n_code_links":0,"syntology":null},{"paper":"/paper/synthvlm-high-efficiency-and-high-quality","slug":"synthvlm-high-efficiency-and-high-quality","title":"SynthVLM: High-Efficiency and High-Quality Synthetic Data for Vision Language Models","date":"2024-07-30","arxiv_id":"2407.20756","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-unified-graph-transformer-for-overcoming","title":"A Unified Graph Transformer for Overcoming Isolations in Multi-modal Recommendation","date":"2024-07-29","arxiv_id":"2407.19886","n_code_links":0,"syntology":null},{"paper":"/paper/alen-a-dual-approach-for-uniform-and-non","slug":"alen-a-dual-approach-for-uniform-and-non","title":"ALEN: A Dual-Approach for Uniform and Non-Uniform Low-Light Image Enhancement","date":"2024-07-29","arxiv_id":"2407.19708","n_code_links":1,"syntology":null},{"paper":"/paper/cross-layer-feature-pyramid-transformer-for","slug":"cross-layer-feature-pyramid-transformer-for","title":"Cross-Layer Feature Pyramid Transformer for Small Object Detection in Aerial Images","date":"2024-07-29","arxiv_id":"2407.19696","n_code_links":1,"syntology":null},{"paper":"/paper/efficient-face-super-resolution-via-wavelet","slug":"efficient-face-super-resolution-via-wavelet","title":"Efficient Face Super-Resolution via Wavelet-based Feature Enhancement Network","date":"2024-07-29","arxiv_id":"2407.19768","n_code_links":1,"syntology":null},{"paper":"/paper/emotion-driven-melody-harmonization-via","slug":"emotion-driven-melody-harmonization-via","title":"Emotion-Driven Melody Harmonization via Melodic Variation and Functional Representation","date":"2024-07-29","arxiv_id":"2407.20176","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-retrieval-augmented-language-model","title":"Improving Retrieval Augmented Language Model with Self-Reasoning","date":"2024-07-29","arxiv_id":"2407.19813","n_code_links":0,"syntology":null},{"paper":null,"slug":"legal-minds-algorithmic-decisions-how-llms","title":"Legal Minds, Algorithmic Decisions: How LLMs Apply Constitutional Principles in Complex Scenarios","date":"2024-07-29","arxiv_id":"2407.19760","n_code_links":0,"syntology":null},{"paper":"/paper/mixture-of-nested-experts-adaptive-processing","slug":"mixture-of-nested-experts-adaptive-processing","title":"Mixture of Nested Experts: Adaptive Processing of Visual Tokens","date":"2024-07-29","arxiv_id":"2407.19985","n_code_links":1,"syntology":{"ran":8,"of":14,"n_ran_checked":7,"n_instrument":1,"unverified":6,"pointer_only":0,"phrase":"8 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 1 where Syntology's instrument failed) · 6 unverified","official":null}},{"paper":null,"slug":"ml-mamba-efficient-multi-modal-large-language","title":"ML-Mamba: Efficient Multi-Modal Large Language Model Utilizing Mamba-2","date":"2024-07-29","arxiv_id":"2407.19832","n_code_links":0,"syntology":null},{"paper":null,"slug":"revolutionizing-urban-safety-perception","title":"Revolutionizing Urban Safety Perception Assessments: Integrating Multimodal Large Language Models with Street View Images","date":"2024-07-29","arxiv_id":"2407.19719","n_code_links":0,"syntology":null},{"paper":null,"slug":"sentiment-analysis-of-lithuanian-online","title":"Sentiment Analysis of Lithuanian Online Reviews Using Large Language Models","date":"2024-07-29","arxiv_id":"2407.19914","n_code_links":0,"syntology":null},{"paper":null,"slug":"survey-and-taxonomy-the-role-of-data-centric","title":"Survey and Taxonomy: The Role of Data-Centric AI in Transformer-Based Time Series Forecasting","date":"2024-07-29","arxiv_id":"2407.19784","n_code_links":0,"syntology":null},{"paper":null,"slug":"to-accept-or-not-to-accept-an-irt-toe","title":"To accept or not to accept? An IRT-TOE Framework to Understand Educators' Resistance to Generative AI in Higher Education","date":"2024-07-29","arxiv_id":"2407.20130","n_code_links":0,"syntology":null},{"paper":null,"slug":"what-if-red-can-talk-dynamic-dialogue","title":"What if Red Can Talk? Dynamic Dialogue Generation Using Large Language Models","date":"2024-07-29","arxiv_id":"2407.20382","n_code_links":0,"syntology":null},{"paper":"/paper/depth-wise-convolutions-in-vision","slug":"depth-wise-convolutions-in-vision","title":"Depth-Wise Convolutions in Vision Transformers for Efficient Training on Small Datasets","date":"2024-07-28","arxiv_id":"2407.19394","n_code_links":1,"syntology":{"ran":13,"of":16,"n_ran_checked":11,"n_instrument":2,"unverified":3,"pointer_only":16,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 11 with no instrument failure: 1 honoured, 2 violated, 8 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["ztx-100/efficient_vit_with_dw"],"state":"official (archive's flag): 13 ran","n_ran":13,"n_constructed":0,"n_ran_no_instrument_failure":11,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"exploring-the-adversarial-robustness-of-clip","title":"Exploring the Adversarial Robustness of CLIP for AI-generated Image Detection","date":"2024-07-28","arxiv_id":"2407.19553","n_code_links":0,"syntology":null},{"paper":null,"slug":"look-hear-gaze-prediction-for-speech-directed","title":"Look Hear: Gaze Prediction for Speech-directed Human Attention","date":"2024-07-28","arxiv_id":"2407.19605","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-modal-imaging-genomics-transformer","title":"Multi-modal Imaging Genomics Transformer: Attentive Integration of Imaging with Genomic Biomarkers for Schizophrenia Classification","date":"2024-07-28","arxiv_id":"2407.19385","n_code_links":0,"syntology":null},{"paper":null,"slug":"nvc-1b-a-large-neural-video-coding-model","title":"NVC-1B: A Large Neural Video Coding Model","date":"2024-07-28","arxiv_id":"2407.19402","n_code_links":0,"syntology":null},{"paper":null,"slug":"official-nv-a-news-video-dataset-for","title":"Official-NV: An LLM-Generated News Video Dataset for Multimodal Fake News Detection","date":"2024-07-28","arxiv_id":"2407.19493","n_code_links":0,"syntology":null},{"paper":null,"slug":"aresnet-vit-a-hybrid-cnn-transformer-network","title":"AResNet-ViT: A Hybrid CNN-Transformer Network for Benign and Malignant Breast Nodule Classification in Ultrasound Images","date":"2024-07-27","arxiv_id":"2407.19316","n_code_links":0,"syntology":null},{"paper":null,"slug":"channel-boosted-cnn-transformer-based-multi","title":"Channel Boosted CNN-Transformer-based Multi-Level and Multi-Scale Nuclei Segmentation","date":"2024-07-27","arxiv_id":"2407.19186","n_code_links":0,"syntology":null},{"paper":null,"slug":"fine-grained-scene-graph-generation-via","title":"Fine-Grained Scene Graph Generation via Sample-Level Bias Prediction","date":"2024-07-27","arxiv_id":"2407.19259","n_code_links":0,"syntology":null},{"paper":null,"slug":"integrating-large-language-models-into-a-tri","title":"Integrating Large Language Models into a Tri-Modal Architecture for Automated Depression Classification on the DAIC-WOZ","date":"2024-07-27","arxiv_id":"2407.19340","n_code_links":0,"syntology":null},{"paper":"/paper/matrrec-uniting-mamba-and-transformer-for","slug":"matrrec-uniting-mamba-and-transformer-for","title":"MaTrRec: Uniting Mamba and Transformer for Sequential Recommendation","date":"2024-07-27","arxiv_id":"2407.19239","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["unintelligentmumu/matrrec"],"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":"bctr-bidirectional-conditioning-transformer","title":"BCTR: Bidirectional Conditioning Transformer for Scene Graph Generation","date":"2024-07-26","arxiv_id":"2407.18715","n_code_links":0,"syntology":null},{"paper":null,"slug":"deep-companion-learning-enhancing","title":"Deep Companion Learning: Enhancing Generalization Through Historical Consistency","date":"2024-07-26","arxiv_id":"2407.18821","n_code_links":0,"syntology":null},{"paper":"/paper/gpt-deciphering-fedspeak-quantifying-dissent","slug":"gpt-deciphering-fedspeak-quantifying-dissent","title":"GPT Deciphering Fedspeak: Quantifying Dissent Among Hawks and Doves","date":"2024-07-26","arxiv_id":"2407.19110","n_code_links":1,"syntology":null},{"paper":"/paper/multimodal-emotion-recognition-using-audio","slug":"multimodal-emotion-recognition-using-audio","title":"Multimodal Emotion Recognition using Audio-Video Transformer Fusion with Cross Attention","date":"2024-07-26","arxiv_id":"2407.18552","n_code_links":1,"syntology":null},{"paper":"/paper/officebench-benchmarking-language-agents","slug":"officebench-benchmarking-language-agents","title":"OfficeBench: Benchmarking Language Agents across Multiple Applications for Office Automation","date":"2024-07-26","arxiv_id":"2407.19056","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":{"repos":["zlwang-cs/OfficeBench"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"paper":null,"slug":"qt-tdm-planning-with-transformer-dynamics","title":"QT-TDM: Planning With Transformer Dynamics Model and Autoregressive Q-Learning","date":"2024-07-26","arxiv_id":"2407.18841","n_code_links":0,"syntology":null},{"paper":null,"slug":"skin-cancer-detection-utilizing-deep-learning","title":"Skin Cancer Detection utilizing Deep Learning: Classification of Skin Lesion Images using a Vision Transformer","date":"2024-07-26","arxiv_id":"2407.18554","n_code_links":0,"syntology":null},{"paper":null,"slug":"tagify-llm-powered-tagging-interface-for","title":"TAGIFY: LLM-powered Tagging Interface for Improved Data Findability on OGD portals","date":"2024-07-26","arxiv_id":"2407.18764","n_code_links":0,"syntology":null},{"paper":"/paper/towards-a-transformer-based-pre-trained-model","slug":"towards-a-transformer-based-pre-trained-model","title":"Towards a Transformer-Based Pre-trained Model for IoT Traffic Classification","date":"2024-07-26","arxiv_id":"2407.19051","n_code_links":1,"syntology":null},{"paper":null,"slug":"using-gpt-4-to-guide-causal-machine-learning","title":"Using GPT-4 to guide causal machine learning","date":"2024-07-26","arxiv_id":"2407.18607","n_code_links":0,"syntology":null},{"paper":null,"slug":"using-large-language-models-for-the","title":"Using Large Language Models for the Interpretation of Building Regulations","date":"2024-07-26","arxiv_id":"2407.21060","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-robust-decision-transformer","slug":"adversarial-robust-decision-transformer","title":"Adversarially Robust Decision Transformer","date":"2024-07-25","arxiv_id":"2407.18414","n_code_links":1,"syntology":{"ran":0,"of":1,"n_ran_checked":0,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"0 ran · 1 unverified","official":{"repos":["xiaohangt/ardt"],"state":"official: harvested, nothing ran","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":[]}}},{"paper":"/paper/cost-effective-instruction-learning-for","slug":"cost-effective-instruction-learning-for","title":"Cost-effective Instruction Learning for Pathology Vision and Language Analysis","date":"2024-07-25","arxiv_id":"2407.17734","n_code_links":1,"syntology":null},{"paper":"/paper/cswin-unet-transformer-unet-with-cross-shaped","slug":"cswin-unet-transformer-unet-with-cross-shaped","title":"CSWin-UNet: Transformer UNet with Cross-Shaped Windows for Medical Image Segmentation","date":"2024-07-25","arxiv_id":"2407.18070","n_code_links":1,"syntology":null},{"paper":"/paper/detection-of-manatee-vocalisations-using-the","slug":"detection-of-manatee-vocalisations-using-the","title":"Detection of manatee vocalisations using the Audio Spectrogram Transformer","date":"2024-07-25","arxiv_id":"2407.18083","n_code_links":1,"syntology":null},{"paper":null,"slug":"hg-pipe-vision-transformer-acceleration-with","title":"HG-PIPE: Vision Transformer Acceleration with Hybrid-Grained Pipeline","date":"2024-07-25","arxiv_id":"2407.17879","n_code_links":0,"syntology":null},{"paper":null,"slug":"is-the-digital-forensics-and-incident","title":"Is the Digital Forensics and Incident Response Pipeline Ready for Text-Based Threats in LLM Era?","date":"2024-07-25","arxiv_id":"2407.17870","n_code_links":0,"syntology":null},{"paper":null,"slug":"keep-the-cost-down-a-review-on-methods-to","title":"Keep the Cost Down: A Review on Methods to Optimize LLM' s KV-Cache Consumption","date":"2024-07-25","arxiv_id":"2407.18003","n_code_links":0,"syntology":null},{"paper":"/paper/personagym-evaluating-persona-agents-and-llms","slug":"personagym-evaluating-persona-agents-and-llms","title":"PersonaGym: Evaluating Persona Agents and LLMs","date":"2024-07-25","arxiv_id":"2407.18416","n_code_links":1,"syntology":null},{"paper":"/paper/self-training-with-direct-preference","slug":"self-training-with-direct-preference","title":"Self-Training with Direct Preference Optimization Improves Chain-of-Thought Reasoning","date":"2024-07-25","arxiv_id":"2407.18248","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":0,"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) · 0 unverified","official":{"repos":["tianduowang/dpo-st"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"trajectory-aligned-space-time-tokens-for-few","title":"Trajectory-aligned Space-time Tokens for Few-shot Action Recognition","date":"2024-07-25","arxiv_id":"2407.18249","n_code_links":0,"syntology":null},{"paper":null,"slug":"trust-or-escalate-llm-judges-with-provable","title":"Trust or Escalate: LLM Judges with Provable Guarantees for Human Agreement","date":"2024-07-25","arxiv_id":"2407.18370","n_code_links":0,"syntology":null},{"paper":null,"slug":"bailicai-a-domain-optimized-retrieval","title":"Bailicai: A Domain-Optimized Retrieval-Augmented Generation Framework for Medical Applications","date":"2024-07-24","arxiv_id":"2407.21055","n_code_links":0,"syntology":null},{"paper":"/paper/case-enhanced-vision-transformer-improving","slug":"case-enhanced-vision-transformer-improving","title":"Case-Enhanced Vision Transformer: Improving Explanations of Image Similarity with a ViT-based Similarity Metric","date":"2024-07-24","arxiv_id":"2407.16981","n_code_links":1,"syntology":null},{"paper":"/paper/dependency-transformer-grammars-integrating","slug":"dependency-transformer-grammars-integrating","title":"Dependency Transformer Grammars: Integrating Dependency Structures into Transformer Language Models","date":"2024-07-24","arxiv_id":"2407.17406","n_code_links":1,"syntology":null},{"paper":"/paper/dynamic-graph-transformer-with-correlated","slug":"dynamic-graph-transformer-with-correlated","title":"Dynamic Graph Transformer with Correlated Spatial-Temporal Positional Encoding","date":"2024-07-24","arxiv_id":"2407.16959","n_code_links":1,"syntology":null},{"paper":"/paper/embedding-free-transformer-with-inference","slug":"embedding-free-transformer-with-inference","title":"Embedding-Free Transformer with Inference Spatial Reduction for Efficient Semantic Segmentation","date":"2024-07-24","arxiv_id":"2407.17261","n_code_links":1,"syntology":null},{"paper":"/paper/i-could-ve-asked-that-reformulating","slug":"i-could-ve-asked-that-reformulating","title":"I Could've Asked That: Reformulating Unanswerable Questions","date":"2024-07-24","arxiv_id":"2407.17469","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-icd-coding-using-chapter-based","title":"Improving ICD coding using Chapter based Named Entities and Attentional Models","date":"2024-07-24","arxiv_id":"2407.17230","n_code_links":0,"syntology":null},{"paper":"/paper/loformer-local-frequency-transformer-for","slug":"loformer-local-frequency-transformer-for","title":"LoFormer: Local Frequency Transformer for Image Deblurring","date":"2024-07-24","arxiv_id":"2407.16993","n_code_links":2,"syntology":null},{"paper":"/paper/must-multi-scale-transformers-for-surgical","slug":"must-multi-scale-transformers-for-surgical","title":"MuST: Multi-Scale Transformers for Surgical Phase Recognition","date":"2024-07-24","arxiv_id":"2407.17361","n_code_links":1,"syntology":null},{"paper":null,"slug":"testing-large-language-models-on-driving","title":"Testing Large Language Models on Driving Theory Knowledge and Skills for Connected Autonomous Vehicles","date":"2024-07-24","arxiv_id":"2407.17211","n_code_links":0,"syntology":null},{"paper":null,"slug":"artificial-intelligence-in-extracting","title":"Artificial Intelligence in Extracting Diagnostic Data from Dental Records","date":"2024-07-23","arxiv_id":"2407.21050","n_code_links":0,"syntology":null},{"paper":"/paper/channel-partitioned-windowed-attention-and","slug":"channel-partitioned-windowed-attention-and","title":"Channel-Partitioned Windowed Attention And Frequency Learning for Single Image Super-Resolution","date":"2024-07-23","arxiv_id":"2407.16232","n_code_links":0,"syntology":null},{"paper":null,"slug":"diffusion-transformer-captures-spatial","title":"Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data","date":"2024-07-23","arxiv_id":"2407.16134","n_code_links":0,"syntology":null}],"record_sha256":"17c131ef1913a4ec821b01c2056012882f60bad971c8f51863af4dc21a2e553b","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}