{"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/19","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":19,"pages_in_order":139,"rows_per_page":100,"rows":[1801,1900],"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/18","next":"/method/position-wise-feed-forward-layer/papers/20","papers":[{"paper":null,"slug":"ultra-sparse-memory-network","title":"Ultra-Sparse Memory Network","date":"2024-11-19","arxiv_id":"2411.12364","n_code_links":0,"syntology":null},{"paper":"/paper/advacheck-at-genai-detection-task-1-ai","slug":"advacheck-at-genai-detection-task-1-ai","title":"Advacheck at GenAI Detection Task 1: AI Detection Powered by Domain-Aware Multi-Tasking","date":"2024-11-18","arxiv_id":"2411.11736","n_code_links":1,"syntology":null},{"paper":null,"slug":"chapter-7-review-of-data-driven-generative-ai","title":"Chapter 7 Review of Data-Driven Generative AI Models for Knowledge Extraction from Scientific Literature in Healthcare","date":"2024-11-18","arxiv_id":"2411.11635","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-decision-transformer-with-diffusion","title":"Enhancing Decision Transformer with Diffusion-Based Trajectory Branch Generation","date":"2024-11-18","arxiv_id":"2411.11327","n_code_links":0,"syntology":null},{"paper":null,"slug":"fcc-fully-connected-correlation-for-few-shot","title":"FCC: Fully Connected Correlation for Few-Shot Segmentation","date":"2024-11-18","arxiv_id":"2411.11917","n_code_links":0,"syntology":null},{"paper":null,"slug":"in-situ-melt-pool-characterization-via","title":"In-Situ Melt Pool Characterization via Thermal Imaging for Defect Detection in Directed Energy Deposition Using Vision Transformers","date":"2024-11-18","arxiv_id":"2411.12028","n_code_links":0,"syntology":null},{"paper":null,"slug":"lavin-dit-large-vision-diffusion-transformer","title":"LaVin-DiT: Large Vision Diffusion Transformer","date":"2024-11-18","arxiv_id":"2411.11505","n_code_links":0,"syntology":null},{"paper":null,"slug":"litformer-efficient-modeling-and-analysis-of","title":"LiTformer: Efficient Modeling and Analysis of High-Speed Link Transmitters Using Non-Autoregressive Transformer","date":"2024-11-18","arxiv_id":"2411.11699","n_code_links":0,"syntology":null},{"paper":"/paper/perfcodegen-improving-performance-of-llm","slug":"perfcodegen-improving-performance-of-llm","title":"PerfCodeGen: Improving Performance of LLM Generated Code with Execution Feedback","date":"2024-11-18","arxiv_id":"2412.03578","n_code_links":1,"syntology":{"ran":1,"of":3,"n_ran_checked":1,"n_instrument":0,"unverified":2,"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) · 2 unverified","official":{"repos":["SalesforceAIResearch/perfcodegen"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"popular-llms-amplify-race-and-gender","title":"Popular LLMs Amplify Race and Gender Disparities in Human Mobility","date":"2024-11-18","arxiv_id":"2411.14469","n_code_links":0,"syntology":null},{"paper":null,"slug":"st-tree-with-interpretability-for","title":"ST-Tree with Interpretability for Multivariate Time Series Classification","date":"2024-11-18","arxiv_id":"2411.11620","n_code_links":0,"syntology":null},{"paper":"/paper/timeformer-capturing-temporal-relationships","slug":"timeformer-capturing-temporal-relationships","title":"TimeFormer: Capturing Temporal Relationships of Deformable 3D Gaussians for Robust Reconstruction","date":"2024-11-18","arxiv_id":"2411.11941","n_code_links":1,"syntology":null},{"paper":"/paper/unveiling-the-inflexibility-of-adaptive","slug":"unveiling-the-inflexibility-of-adaptive","title":"Unveiling the Inflexibility of Adaptive Embedding in Traffic Forecasting","date":"2024-11-18","arxiv_id":"2411.11448","n_code_links":1,"syntology":null},{"paper":"/paper/exploiting-vlm-localizability-and-semantics","slug":"exploiting-vlm-localizability-and-semantics","title":"Exploiting VLM Localizability and Semantics for Open Vocabulary Action Detection","date":"2024-11-17","arxiv_id":"2411.10922","n_code_links":1,"syntology":null},{"paper":null,"slug":"ive-enhanced-probabilistic-forecasting-of","title":"IVE: Enhanced Probabilistic Forecasting of Intraday Volume Ratio with Transformers","date":"2024-11-17","arxiv_id":"2411.10956","n_code_links":0,"syntology":null},{"paper":null,"slug":"knowledge-enhanced-transformer-for","title":"Knowledge-enhanced Transformer for Multivariate Long Sequence Time-series Forecasting","date":"2024-11-17","arxiv_id":"2411.11046","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-wearable-gait-monitoring-system-for-17-gait","title":"A Wearable Gait Monitoring System for 17 Gait Parameters Based on Computer Vision","date":"2024-11-16","arxiv_id":"2411.10739","n_code_links":0,"syntology":null},{"paper":null,"slug":"allrestorer-all-in-one-transformer-for-image","title":"AllRestorer: All-in-One Transformer for Image Restoration under Composite Degradations","date":"2024-11-16","arxiv_id":"2411.10708","n_code_links":0,"syntology":null},{"paper":"/paper/bag-of-design-choices-for-inference-of-high","slug":"bag-of-design-choices-for-inference-of-high","title":"Bag of Design Choices for Inference of High-Resolution Masked Generative Transformer","date":"2024-11-16","arxiv_id":"2411.10781","n_code_links":1,"syntology":null},{"paper":null,"slug":"intentgpt-few-shot-intent-discovery-with","title":"IntentGPT: Few-shot Intent Discovery with Large Language Models","date":"2024-11-16","arxiv_id":"2411.10670","n_code_links":0,"syntology":null},{"paper":"/paper/metala-unified-optimal-linear-approximation","slug":"metala-unified-optimal-linear-approximation","title":"MetaLA: Unified Optimal Linear Approximation to Softmax Attention Map","date":"2024-11-16","arxiv_id":"2411.10741","n_code_links":1,"syntology":{"ran":2,"of":3,"n_ran_checked":2,"n_instrument":0,"unverified":1,"pointer_only":3,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["BICLab/MetaLA"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/mpoxvlm-a-vision-language-model-for","slug":"mpoxvlm-a-vision-language-model-for","title":"MpoxVLM: A Vision-Language Model for Diagnosing Skin Lesions from Mpox Virus Infection","date":"2024-11-16","arxiv_id":"2411.10888","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-multi-scale-spatial-temporal-network-for","title":"A Multi-Scale Spatial-Temporal Network for Wireless Video Transmission","date":"2024-11-15","arxiv_id":"2411.09936","n_code_links":0,"syntology":null},{"paper":null,"slug":"building-6g-radio-foundation-models-with","title":"Building 6G Radio Foundation Models with Transformer Architectures","date":"2024-11-15","arxiv_id":"2411.09996","n_code_links":0,"syntology":null},{"paper":null,"slug":"cmath-cross-modality-augmented-transformer","title":"CMATH: Cross-Modality Augmented Transformer with Hierarchical Variational Distillation for Multimodal Emotion Recognition in Conversation","date":"2024-11-15","arxiv_id":"2411.10060","n_code_links":0,"syntology":null},{"paper":null,"slug":"dimodif-discourse-modality-information","title":"DiMoDif: Discourse Modality-information Differentiation for Audio-visual Deepfake Detection and Localization","date":"2024-11-15","arxiv_id":"2411.10193","n_code_links":0,"syntology":null},{"paper":null,"slug":"does-prompt-formatting-have-any-impact-on-llm","title":"Does Prompt Formatting Have Any Impact on LLM Performance?","date":"2024-11-15","arxiv_id":"2411.10541","n_code_links":0,"syntology":null},{"paper":null,"slug":"evidential-federated-learning-for-skin-lesion","title":"Evidential Federated Learning for Skin Lesion Image Classification","date":"2024-11-15","arxiv_id":"2411.10071","n_code_links":0,"syntology":null},{"paper":null,"slug":"lora-litee-a-computationally-efficient","title":"LoRA-LiteE: A Computationally Efficient Framework for Chatbot Preference-Tuning","date":"2024-11-15","arxiv_id":"2411.09947","n_code_links":0,"syntology":null},{"paper":null,"slug":"probabilistic-prior-driven-attention","title":"Probabilistic Prior Driven Attention Mechanism Based on Diffusion Model for Imaging Through Atmospheric Turbulence","date":"2024-11-15","arxiv_id":"2411.10321","n_code_links":0,"syntology":null},{"paper":"/paper/retr-multi-view-radar-detection-transformer","slug":"retr-multi-view-radar-detection-transformer","title":"RETR: Multi-View Radar Detection Transformer for Indoor Perception","date":"2024-11-15","arxiv_id":"2411.10293","n_code_links":1,"syntology":{"ran":9,"of":13,"n_ran_checked":9,"n_instrument":0,"unverified":4,"pointer_only":13,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 2 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":{"repos":["merlresearch/radar-detection-transformer"],"state":"official (archive's flag): 9 ran","n_ran":9,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"scaling-law-for-post-training-after-model","title":"P$^2$ Law: Scaling Law for Post-Training After Model Pruning","date":"2024-11-15","arxiv_id":"2411.10272","n_code_links":0,"syntology":null},{"paper":null,"slug":"ultra-unveiling-latent-token-interpretability","title":"ULTra: Unveiling Latent Token Interpretability in Transformer Based Understanding","date":"2024-11-15","arxiv_id":"2411.12589","n_code_links":0,"syntology":null},{"paper":null,"slug":"adopting-rag-for-llm-aided-future-vehicle","title":"Adopting RAG for LLM-Aided Future Vehicle Design","date":"2024-11-14","arxiv_id":"2411.09590","n_code_links":0,"syntology":null},{"paper":null,"slug":"automating-autograding-large-language-models","title":"Automating Autograding: Large Language Models as Test Suite Generators for Introductory Programming","date":"2024-11-14","arxiv_id":"2411.09261","n_code_links":0,"syntology":null},{"paper":null,"slug":"babylm-challenge-exploring-the-effect-of","title":"BabyLM Challenge: Exploring the Effect of Variation Sets on Language Model Training Efficiency","date":"2024-11-14","arxiv_id":"2411.09587","n_code_links":0,"syntology":null},{"paper":null,"slug":"dscformer-a-dual-branch-network-integrating","title":"DSCformer: A Dual-Branch Network Integrating Enhanced Dynamic Snake Convolution and SegFormer for Crack Segmentation","date":"2024-11-14","arxiv_id":"2411.09371","n_code_links":0,"syntology":null},{"paper":null,"slug":"dt-jrd-deep-transformer-based-just","title":"DT-JRD: Deep Transformer based Just Recognizable Difference Prediction Model for Video Coding for Machines","date":"2024-11-14","arxiv_id":"2411.09308","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-gender-bias-in-large-language-1","title":"Evaluating Gender Bias in Large Language Models","date":"2024-11-14","arxiv_id":"2411.09826","n_code_links":0,"syntology":null},{"paper":null,"slug":"local-deployment-of-large-scale-music-ai","title":"Local deployment of large-scale music AI models on commodity hardware","date":"2024-11-14","arxiv_id":"2411.09625","n_code_links":0,"syntology":null},{"paper":"/paper/mm-eval-a-hierarchical-benchmark-for-modern","slug":"mm-eval-a-hierarchical-benchmark-for-modern","title":"MM-Eval: A Hierarchical Benchmark for Modern Mongolian Evaluation in LLMs","date":"2024-11-14","arxiv_id":"2411.09492","n_code_links":1,"syntology":null},{"paper":"/paper/opengemm-a-high-utilization-gemm-accelerator","slug":"opengemm-a-high-utilization-gemm-accelerator","title":"OpenGeMM: A High-Utilization GeMM Accelerator Generator with Lightweight RISC-V Control and Tight Memory Coupling","date":"2024-11-14","arxiv_id":"2411.09543","n_code_links":1,"syntology":null},{"paper":null,"slug":"partial-multi-view-clustering-via-meta","title":"Partial Multi-View Clustering via Meta-Learning and Contrastive Feature Alignment","date":"2024-11-14","arxiv_id":"2411.09758","n_code_links":0,"syntology":null},{"paper":null,"slug":"re-parameterization-of-lightweight","title":"Re-Parameterization of Lightweight Transformer for On-Device Speech Emotion Recognition","date":"2024-11-14","arxiv_id":"2411.09339","n_code_links":0,"syntology":null},{"paper":"/paper/sag-vit-a-scale-aware-high-fidelity-patching","slug":"sag-vit-a-scale-aware-high-fidelity-patching","title":"SAG-ViT: A Scale-Aware, High-Fidelity Patching Approach with Graph Attention for Vision Transformers","date":"2024-11-14","arxiv_id":"2411.09420","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-transformer-based-visual-piano","title":"A Transformer-Based Visual Piano Transcription Algorithm","date":"2024-11-13","arxiv_id":"2411.09037","n_code_links":0,"syntology":null},{"paper":null,"slug":"continuous-gnn-based-anomaly-detection-on","title":"Continuous GNN-based Anomaly Detection on Edge using Efficient Adaptive Knowledge Graph Learning","date":"2024-11-13","arxiv_id":"2411.09072","n_code_links":0,"syntology":null},{"paper":null,"slug":"sad-time-a-spatiotemporal-fused-network-for","title":"SAD-TIME: a Spatiotemporal-fused network for depression detection with Automated multi-scale Depth-wise and TIME-interval-related common feature extractor","date":"2024-11-13","arxiv_id":"2411.08521","n_code_links":0,"syntology":null},{"paper":"/paper/trace-transformer-based-risk-assessment-for","slug":"trace-transformer-based-risk-assessment-for","title":"TRACE: Transformer-based Risk Assessment for Clinical Evaluation","date":"2024-11-13","arxiv_id":"2411.08701","n_code_links":1,"syntology":null},{"paper":null,"slug":"uiformer-a-unified-transformer-based","title":"UIFormer: A Unified Transformer-based Framework for Incremental Few-Shot Object Detection and Instance Segmentation","date":"2024-11-13","arxiv_id":"2411.08569","n_code_links":0,"syntology":null},{"paper":"/paper/xiyan-sql-a-multi-generator-ensemble","slug":"xiyan-sql-a-multi-generator-ensemble","title":"A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL","date":"2024-11-13","arxiv_id":"2411.08599","n_code_links":5,"syntology":null},{"paper":"/paper/breaking-the-low-rank-dilemma-of-linear","slug":"breaking-the-low-rank-dilemma-of-linear","title":"Breaking the Low-Rank Dilemma of Linear Attention","date":"2024-11-12","arxiv_id":"2411.07635","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["qhfan/rala"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"budgetmlagent-a-cost-effective-llm-multi","title":"BudgetMLAgent: A Cost-Effective LLM Multi-Agent system for Automating Machine Learning Tasks","date":"2024-11-12","arxiv_id":"2411.07464","n_code_links":0,"syntology":null},{"paper":null,"slug":"can-adversarial-attacks-by-large-language","title":"Can adversarial attacks by large language models be attributed?","date":"2024-11-12","arxiv_id":"2411.08003","n_code_links":0,"syntology":null},{"paper":null,"slug":"circuit-complexity-bounds-for-rope-based","title":"Circuit Complexity Bounds for RoPE-based Transformer Architecture","date":"2024-11-12","arxiv_id":"2411.07602","n_code_links":0,"syntology":null},{"paper":"/paper/controlled-evaluation-of-syntactic-knowledge","slug":"controlled-evaluation-of-syntactic-knowledge","title":"Controlled Evaluation of Syntactic Knowledge in Multilingual Language Models","date":"2024-11-12","arxiv_id":"2411.07474","n_code_links":1,"syntology":null},{"paper":null,"slug":"efficient-federated-finetuning-of-tiny","title":"Efficient Federated Finetuning of Tiny Transformers with Resource-Constrained Devices","date":"2024-11-12","arxiv_id":"2411.07826","n_code_links":0,"syntology":null},{"paper":"/paper/evaluating-chatgpt-3-5-efficiency-in-solving","slug":"evaluating-chatgpt-3-5-efficiency-in-solving","title":"Evaluating ChatGPT-3.5 Efficiency in Solving Coding Problems of Different Complexity Levels: An Empirical Analysis","date":"2024-11-12","arxiv_id":"2411.07529","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-grapheme-to-phoneme-conversion","title":"Improving Grapheme-to-Phoneme Conversion through In-Context Knowledge Retrieval with Large Language Models","date":"2024-11-12","arxiv_id":"2411.07563","n_code_links":0,"syntology":null},{"paper":"/paper/large-language-models-can-self-improve-in","slug":"large-language-models-can-self-improve-in","title":"Large Language Models Can Self-Improve in Long-context Reasoning","date":"2024-11-12","arxiv_id":"2411.08147","n_code_links":1,"syntology":{"ran":6,"of":6,"n_ran_checked":5,"n_instrument":1,"unverified":0,"pointer_only":6,"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) · 0 unverified","official":{"repos":["sihengli99/sealong"],"state":"official (archive's flag): 6 ran","n_ran":6,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"unraveling-the-gradient-descent-dynamics-of","title":"Unraveling the Gradient Descent Dynamics of Transformers","date":"2024-11-12","arxiv_id":"2411.07538","n_code_links":0,"syntology":null},{"paper":"/paper/verbosity-neq-veracity-demystify-verbosity","slug":"verbosity-neq-veracity-demystify-verbosity","title":"Verbosity $\\neq$ Veracity: Demystify Verbosity Compensation Behavior of Large Language Models","date":"2024-11-12","arxiv_id":"2411.07858","n_code_links":1,"syntology":null},{"paper":"/paper/storyteller-improving-long-video-description","slug":"storyteller-improving-long-video-description","title":"StoryTeller: Improving Long Video Description through Global Audio-Visual Character Identification","date":"2024-11-11","arxiv_id":"2411.07076","n_code_links":1,"syntology":null},{"paper":null,"slug":"treecoders-trees-of-transformers","title":"TreeCoders: Trees of Transformers","date":"2024-11-11","arxiv_id":"2411.07218","n_code_links":0,"syntology":null},{"paper":"/paper/white-box-diffusion-transformer-for-single","slug":"white-box-diffusion-transformer-for-single","title":"White-Box Diffusion Transformer for single-cell RNA-seq generation","date":"2024-11-11","arxiv_id":"2411.06785","n_code_links":1,"syntology":null},{"paper":null,"slug":"emotion-aware-interaction-design-in","title":"Emotion-Aware Interaction Design in Intelligent User Interface Using Multi-Modal Deep Learning","date":"2024-11-10","arxiv_id":"2411.06326","n_code_links":0,"syntology":null},{"paper":"/paper/feature-fusion-transferability-aware","slug":"feature-fusion-transferability-aware","title":"Feature Fusion Transferability Aware Transformer for Unsupervised Domain Adaptation","date":"2024-11-10","arxiv_id":"2411.07794","n_code_links":2,"syntology":null},{"paper":null,"slug":"few-shot-semantic-learning-for-robust-multi","title":"Few-shot Semantic Learning for Robust Multi-Biome 3D Semantic Mapping in Off-Road Environments","date":"2024-11-10","arxiv_id":"2411.06632","n_code_links":0,"syntology":null},{"paper":"/paper/local-implicit-wavelet-transformer-for","slug":"local-implicit-wavelet-transformer-for","title":"Local Implicit Wavelet Transformer for Arbitrary-Scale Super-Resolution","date":"2024-11-10","arxiv_id":"2411.06442","n_code_links":1,"syntology":null},{"paper":null,"slug":"ai-s-spatial-intelligence-evaluating-ai-s","title":"AI's Spatial Intelligence: Evaluating AI's Understanding of Spatial Transformations in PSVT:R and Augmented Reality","date":"2024-11-09","arxiv_id":"2411.06269","n_code_links":0,"syntology":null},{"paper":null,"slug":"neureg-domain-invariant-3d-image-registration","title":"NeuReg: Domain-invariant 3D Image Registration on Human and Mouse Brains","date":"2024-11-09","arxiv_id":"2411.06315","n_code_links":0,"syntology":null},{"paper":null,"slug":"pattern-integration-and-enhancement-vision","title":"Pattern Integration and Enhancement Vision Transformer for Self-Supervised Learning in Remote Sensing","date":"2024-11-09","arxiv_id":"2411.06091","n_code_links":0,"syntology":null},{"paper":null,"slug":"selective-state-space-model-for-monaural","title":"Selective State Space Model for Monaural Speech Enhancement","date":"2024-11-09","arxiv_id":"2411.06217","n_code_links":0,"syntology":null},{"paper":null,"slug":"vitoc-vision-transformer-and-object-aware","title":"ViTOC: Vision Transformer and Object-aware Captioner","date":"2024-11-09","arxiv_id":"2411.07265","n_code_links":0,"syntology":null},{"paper":"/paper/autoregressive-adaptive-hypergraph","slug":"autoregressive-adaptive-hypergraph","title":"Autoregressive Adaptive Hypergraph Transformer for Skeleton-based Activity Recognition","date":"2024-11-08","arxiv_id":"2411.05692","n_code_links":1,"syntology":null},{"paper":"/paper/cascaded-dual-vision-transformer-for-accurate","slug":"cascaded-dual-vision-transformer-for-accurate","title":"Cascaded Dual Vision Transformer for Accurate Facial Landmark Detection","date":"2024-11-08","arxiv_id":"2411.07167","n_code_links":1,"syntology":null},{"paper":null,"slug":"classification-of-adventitious-sounds","title":"Classification of Adventitious Sounds Combining Cochleogram and Vision Transformers","date":"2024-11-08","arxiv_id":"2411.05955","n_code_links":0,"syntology":null},{"paper":"/paper/efficient-self-supervised-barlow-twins-from","slug":"efficient-self-supervised-barlow-twins-from","title":"Efficient Self-Supervised Barlow Twins from Limited Tissue Slide Cohorts for Colonic Pathology Diagnostics","date":"2024-11-08","arxiv_id":"2411.05959","n_code_links":1,"syntology":null},{"paper":null,"slug":"emotional-images-assessing-emotions-in-images","title":"Emotional Images: Assessing Emotions in Images and Potential Biases in Generative Models","date":"2024-11-08","arxiv_id":"2411.05985","n_code_links":0,"syntology":null},{"paper":null,"slug":"gci-vital-gradual-confidence-improvement-with","title":"GCI-ViTAL: Gradual Confidence Improvement with Vision Transformers for Active Learning on Label Noise","date":"2024-11-08","arxiv_id":"2411.05939","n_code_links":0,"syntology":null},{"paper":null,"slug":"image-inpainting-enhancement-by-replacing-the","title":"Image inpainting enhancement by replacing the original mask with a self-attended region from the input image","date":"2024-11-08","arxiv_id":"2411.05705","n_code_links":0,"syntology":null},{"paper":null,"slug":"improving-molecular-graph-generation-with","title":"Improving Molecular Graph Generation with Flow Matching and Optimal Transport","date":"2024-11-08","arxiv_id":"2411.05676","n_code_links":0,"syntology":null},{"paper":"/paper/online-lora-task-free-online-continual","slug":"online-lora-task-free-online-continual","title":"Online-LoRA: Task-free Online Continual Learning via Low Rank Adaptation","date":"2024-11-08","arxiv_id":"2411.05663","n_code_links":1,"syntology":null},{"paper":null,"slug":"saswise-ue-segmentation-and-synthesis-with","title":"SASWISE-UE: Segmentation and Synthesis with Interpretable Scalable Ensembles for Uncertainty Estimation","date":"2024-11-08","arxiv_id":"2411.05324","n_code_links":0,"syntology":null},{"paper":null,"slug":"smile-upon-the-face-but-sadness-in-the-eyes","title":"Smile upon the Face but Sadness in the Eyes: Emotion Recognition based on Facial Expressions and Eye Behaviors","date":"2024-11-08","arxiv_id":"2411.05879","n_code_links":0,"syntology":null},{"paper":"/paper/using-language-models-to-disambiguate-lexical","slug":"using-language-models-to-disambiguate-lexical","title":"Using Language Models to Disambiguate Lexical Choices in Translation","date":"2024-11-08","arxiv_id":"2411.05781","n_code_links":1,"syntology":null},{"paper":null,"slug":"vit-enhanced-privacy-preserving-secure","title":"ViT Enhanced Privacy-Preserving Secure Medical Data Sharing and Classification","date":"2024-11-08","arxiv_id":"2411.05901","n_code_links":0,"syntology":null},{"paper":null,"slug":"dancefusion-a-spatio-temporal-skeleton","title":"DanceFusion: A Spatio-Temporal Skeleton Diffusion Transformer for Audio-Driven Dance Motion Reconstruction","date":"2024-11-07","arxiv_id":"2411.04646","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-low-light-images-with-kolmogorov","slug":"enhancing-low-light-images-with-kolmogorov","title":"Enhancing Low-Light Images with Kolmogorov–Arnold Networks in Transformer Attention","date":"2024-11-07","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"esc-misr-enhancing-spatial-correlations-for","title":"ESC-MISR: Enhancing Spatial Correlations for Multi-Image Super-Resolution in Remote Sensing","date":"2024-11-07","arxiv_id":"2411.04706","n_code_links":0,"syntology":null},{"paper":"/paper/hourvideo-1-hour-video-language-understanding","slug":"hourvideo-1-hour-video-language-understanding","title":"HourVideo: 1-Hour Video-Language Understanding","date":"2024-11-07","arxiv_id":"2411.04998","n_code_links":1,"syntology":{"ran":14,"of":16,"n_ran_checked":13,"n_instrument":1,"unverified":2,"pointer_only":1,"phrase":"14 ran (of which 0 constructed an object rather than computing a result; 13 with no instrument failure: 0 honoured, 0 violated, 13 with no contract checked; 1 where Syntology's instrument failed) · 2 unverified","official":{"repos":["keshik6/HourVideo"],"state":"official (archive's flag): 14 ran","n_ran":14,"n_constructed":0,"n_ran_no_instrument_failure":13,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/llm2clip-powerful-language-model-unlock","slug":"llm2clip-powerful-language-model-unlock","title":"LLM2CLIP: Powerful Language Model Unlocks Richer Visual Representation","date":"2024-11-07","arxiv_id":"2411.04997","n_code_links":1,"syntology":null},{"paper":null,"slug":"measure-to-measure-interpolation-using","title":"Measure-to-measure interpolation using Transformers","date":"2024-11-07","arxiv_id":"2411.04551","n_code_links":0,"syntology":null},{"paper":"/paper/measuring-short-form-factuality-in-large","slug":"measuring-short-form-factuality-in-large","title":"Measuring short-form factuality in large language models","date":"2024-11-07","arxiv_id":"2411.04368","n_code_links":1,"syntology":null},{"paper":null,"slug":"multi-temporal-crack-segmentation-in-concrete","title":"Multi-temporal crack segmentation in concrete structure using deep learning approaches","date":"2024-11-07","arxiv_id":"2411.04620","n_code_links":0,"syntology":null},{"paper":null,"slug":"pose2trajectory-using-transformers-on-body","title":"Pose2Trajectory: Using Transformers on Body Pose to Predict Tennis Player's Trajectory","date":"2024-11-07","arxiv_id":"2411.04501","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-comparative-study-of-recent-large-language","title":"A Comparative Study of Recent Large Language Models on Generating Hospital Discharge Summaries for Lung Cancer Patients","date":"2024-11-06","arxiv_id":"2411.03805","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-contrastive-self-supervised-learning-scheme","title":"A Contrastive Self-Supervised Learning scheme for beat tracking amenable to few-shot learning","date":"2024-11-06","arxiv_id":"2411.04152","n_code_links":0,"syntology":null},{"paper":"/paper/bio-xlstm-generative-modeling-representation","slug":"bio-xlstm-generative-modeling-representation","title":"Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences","date":"2024-11-06","arxiv_id":"2411.04165","n_code_links":3,"syntology":{"ran":27,"of":29,"n_ran_checked":25,"n_instrument":2,"unverified":2,"pointer_only":1,"phrase":"27 ran (of which 0 constructed an object rather than computing a result; 25 with no instrument failure: 0 honoured, 1 violated, 24 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["ml-jku/chem-xlstm","ml-jku/dna-xlstm","ml-jku/prot-xlstm"],"state":"official (archive's flag): 27 ran","n_ran":27,"n_constructed":0,"n_ran_no_instrument_failure":25,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/customized-multiple-clustering-via-multi","slug":"customized-multiple-clustering-via-multi","title":"Customized Multiple Clustering via Multi-Modal Subspace Proxy Learning","date":"2024-11-06","arxiv_id":"2411.03978","n_code_links":1,"syntology":{"ran":3,"of":5,"n_ran_checked":0,"n_instrument":3,"unverified":2,"pointer_only":5,"phrase":"3 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; 3 where Syntology's instrument failed) · 2 unverified","official":{"repos":["alexander-yao/multi-sub"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":2,"ran_from_kinds":["official"]}}}],"record_sha256":"595511ee825891987b0a7cd0b1ee9e30520bfc2901c8899fd1902ffcca453f84","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}