{"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/attention/papers/6","list_of":"/method/attention","method":"Attention","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":6,"pages_in_order":316,"rows_per_page":100,"rows":[501,600],"of":31583,"counts":{"archive_papers_tagged":31583,"with_a_code_link":13473,"where_syntology_ran_a_sample":3998,"not_listed_spam_title":0,"listed":31583,"listed_where_code_ran":3998,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3366,"every_run_a_failure_of_syntologys_instrument":632,"listed_with_a_run_with_no_instrument_failure":3366,"listed_every_run_a_failure_of_syntologys_instrument":632,"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/attention","prev":"/method/attention/papers/5","next":"/method/attention/papers/7","papers":[{"paper":null,"slug":"absolute-coordinates-make-motion-generation","title":"Absolute Coordinates Make Motion Generation Easy","date":"2025-05-26","arxiv_id":"2505.19377","n_code_links":0,"syntology":null},{"paper":null,"slug":"accelerating-flow-matching-based-text-to","title":"Accelerating Flow-Matching-Based Text-to-Speech via Empirically Pruned Step Sampling","date":"2025-05-26","arxiv_id":"2505.19931","n_code_links":0,"syntology":null},{"paper":null,"slug":"accelerating-prefilling-for-long-context-llms","title":"Accelerating Prefilling for Long-Context LLMs via Sparse Pattern Sharing","date":"2025-05-26","arxiv_id":"2505.19578","n_code_links":0,"syntology":null},{"paper":null,"slug":"adatp-attention-debiased-token-pruning-for","title":"AdaTP: Attention-Debiased Token Pruning for Video Large Language Models","date":"2025-05-26","arxiv_id":"2505.20100","n_code_links":0,"syntology":null},{"paper":null,"slug":"aggregated-structural-representation-with","title":"Aggregated Structural Representation with Large Language Models for Human-Centric Layout Generation","date":"2025-05-26","arxiv_id":"2505.19554","n_code_links":0,"syntology":null},{"paper":"/paper/align-and-surpass-human-camouflaged","slug":"align-and-surpass-human-camouflaged","title":"Align and Surpass Human Camouflaged Perception: Visual Refocus Reinforcement Fine-Tuning","date":"2025-05-26","arxiv_id":"2505.19611","n_code_links":1,"syntology":null},{"paper":"/paper/amplehate-amplifying-the-attention-for","slug":"amplehate-amplifying-the-attention-for","title":"AmpleHate: Amplifying the Attention for Versatile Implicit Hate Detection","date":"2025-05-26","arxiv_id":"2505.19528","n_code_links":1,"syntology":null},{"paper":"/paper/amqa-an-adversarial-dataset-for-benchmarking","slug":"amqa-an-adversarial-dataset-for-benchmarking","title":"AMQA: An Adversarial Dataset for Benchmarking Bias of LLMs in Medicine and Healthcare","date":"2025-05-26","arxiv_id":"2505.19562","n_code_links":1,"syntology":null},{"paper":null,"slug":"anveshana-a-new-benchmark-dataset-for-cross","title":"Anveshana: A New Benchmark Dataset for Cross-Lingual Information Retrieval On English Queries and Sanskrit Documents","date":"2025-05-26","arxiv_id":"2505.19494","n_code_links":0,"syntology":null},{"paper":null,"slug":"automated-evaluation-of-children-s-speech","title":"Automated evaluation of children's speech fluency for low-resource languages","date":"2025-05-26","arxiv_id":"2505.19671","n_code_links":0,"syntology":null},{"paper":null,"slug":"balancing-computation-load-and-representation","title":"Balancing Computation Load and Representation Expressivity in Parallel Hybrid Neural Networks","date":"2025-05-26","arxiv_id":"2505.19472","n_code_links":0,"syntology":null},{"paper":"/paper/benchmarking-multimodal-knowledge-conflict","slug":"benchmarking-multimodal-knowledge-conflict","title":"Benchmarking Multimodal Knowledge Conflict for Large Multimodal Models","date":"2025-05-26","arxiv_id":"2505.19509","n_code_links":1,"syntology":null},{"paper":null,"slug":"beyond-simple-concatenation-fairly-assessing","title":"Beyond Simple Concatenation: Fairly Assessing PLM Architectures for Multi-Chain Protein-Protein Interactions Prediction","date":"2025-05-26","arxiv_id":"2505.20036","n_code_links":0,"syntology":null},{"paper":null,"slug":"beyond-specialization-benchmarking-llms-for","title":"Beyond Specialization: Benchmarking LLMs for Transliteration of Indian Languages","date":"2025-05-26","arxiv_id":"2505.19851","n_code_links":0,"syntology":null},{"paper":null,"slug":"burst-image-super-resolution-via-multi-cross","title":"Burst Image Super-Resolution via Multi-Cross Attention Encoding and Multi-Scan State-Space Decoding","date":"2025-05-26","arxiv_id":"2505.19668","n_code_links":0,"syntology":null},{"paper":null,"slug":"ca3d-convolutional-attentional-3d-nets-for","title":"CA3D: Convolutional-Attentional 3D Nets for Efficient Video Activity Recognition on the Edge","date":"2025-05-26","arxiv_id":"2505.19928","n_code_links":0,"syntology":null},{"paper":"/paper/calibrating-pre-trained-language-classifiers","slug":"calibrating-pre-trained-language-classifiers","title":"Calibrating Pre-trained Language Classifiers on LLM-generated Noisy Labels via Iterative Refinement","date":"2025-05-26","arxiv_id":"2505.19675","n_code_links":1,"syntology":null},{"paper":null,"slug":"cardiopatternformer-pattern-guided-attention","title":"CardioPatternFormer: Pattern-Guided Attention for Interpretable ECG Classification with Transformer Architecture","date":"2025-05-26","arxiv_id":"2505.20481","n_code_links":0,"syntology":null},{"paper":"/paper/compliance-to-code-enhancing-financial","slug":"compliance-to-code-enhancing-financial","title":"Compliance-to-Code: Enhancing Financial Compliance Checking via Code Generation","date":"2025-05-26","arxiv_id":"2505.19804","n_code_links":1,"syntology":null},{"paper":null,"slug":"conversational-lexicography-querying","title":"Conversational Lexicography: Querying Lexicographic Data on Knowledge Graphs with SPARQL through Natural Language","date":"2025-05-26","arxiv_id":"2505.19971","n_code_links":0,"syntology":null},{"paper":null,"slug":"dependency-parsing-is-more-parameter","title":"Dependency Parsing is More Parameter-Efficient with Normalization","date":"2025-05-26","arxiv_id":"2505.20215","n_code_links":0,"syntology":null},{"paper":null,"slug":"detection-of-suicidal-risk-on-social-media-a","title":"Detection of Suicidal Risk on Social Media: A Hybrid Model","date":"2025-05-26","arxiv_id":"2505.23797","n_code_links":0,"syntology":null},{"paper":null,"slug":"dgrag-distributed-graph-based-retrieval","title":"DGRAG: Distributed Graph-based Retrieval-Augmented Generation in Edge-Cloud Systems","date":"2025-05-26","arxiv_id":"2505.19847","n_code_links":0,"syntology":null},{"paper":null,"slug":"doctorrag-medical-rag-fusing-knowledge-with","title":"DoctorRAG: Medical RAG Fusing Knowledge with Patient Analogy through Textual Gradients","date":"2025-05-26","arxiv_id":"2505.19538","n_code_links":0,"syntology":null},{"paper":null,"slug":"durep-dual-mode-speech-representation","title":"DuRep: Dual-Mode Speech Representation Learning via ASR-Aware Distillation","date":"2025-05-26","arxiv_id":"2505.19774","n_code_links":0,"syntology":null},{"paper":null,"slug":"electrolyzers-hsi-close-range-multi-scene","title":"Electrolyzers-HSI: Close-Range Multi-Scene Hyperspectral Imaging Benchmark Dataset","date":"2025-05-26","arxiv_id":"2505.20507","n_code_links":0,"syntology":null},{"paper":null,"slug":"emotion-classification-in-context-in-spanish","title":"Emotion Classification In-Context in Spanish","date":"2025-05-26","arxiv_id":"2505.20571","n_code_links":0,"syntology":null},{"paper":null,"slug":"equivariant-representation-learning-for-1","title":"Equivariant Representation Learning for Symmetry-Aware Inference with Guarantees","date":"2025-05-26","arxiv_id":"2505.19809","n_code_links":0,"syntology":null},{"paper":null,"slug":"eslm-risk-averse-selective-language-modeling","title":"ESLM: Risk-Averse Selective Language Modeling for Efficient Pretraining","date":"2025-05-26","arxiv_id":"2505.19893","n_code_links":0,"syntology":null},{"paper":"/paper/flowcut-rethinking-redundancy-via-information","slug":"flowcut-rethinking-redundancy-via-information","title":"FlowCut: Rethinking Redundancy via Information Flow for Efficient Vision-Language Models","date":"2025-05-26","arxiv_id":"2505.19536","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["tungchintao/flowcut"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/golf-nrt-integrating-global-context-and-local","slug":"golf-nrt-integrating-global-context-and-local","title":"GoLF-NRT: Integrating Global Context and Local Geometry for Few-Shot View Synthesis","date":"2025-05-26","arxiv_id":"2505.19813","n_code_links":1,"syntology":{"ran":15,"of":24,"n_ran_checked":9,"n_instrument":6,"unverified":9,"pointer_only":24,"phrase":"15 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 1 honoured, 0 violated, 8 with no contract checked; 6 where Syntology's instrument failed) · 9 unverified","official":{"repos":["klmav-cuc/golf-nrt"],"state":"official (archive's flag): 15 ran","n_ran":15,"n_constructed":0,"n_ran_no_instrument_failure":9,"n_unverified":9,"ran_from_kinds":["official"]}}},{"paper":"/paper/grokking-explaind-unifying-model-data-and","slug":"grokking-explaind-unifying-model-data-and","title":"Grokking ExPLAIND: Unifying Model, Data, and Training Attribution to Study Model Behavior","date":"2025-05-26","arxiv_id":"2505.20076","n_code_links":1,"syntology":{"ran":3,"of":5,"n_ran_checked":3,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"3 ran (of which 3 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":{"repos":["mainlp/explaind"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":3,"n_ran_no_instrument_failure":3,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":"/paper/hierarchical-masked-autoregressive-models","slug":"hierarchical-masked-autoregressive-models","title":"Hierarchical Masked Autoregressive Models with Low-Resolution Token Pivots","date":"2025-05-26","arxiv_id":"2505.20288","n_code_links":1,"syntology":null},{"paper":null,"slug":"hierarchical-tree-search-based-user-lifelong","title":"Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Model","date":"2025-05-26","arxiv_id":"2505.19505","n_code_links":0,"syntology":null},{"paper":null,"slug":"how-syntax-specialization-emerges-in-language","title":"How Syntax Specialization Emerges in Language Models","date":"2025-05-26","arxiv_id":"2505.19548","n_code_links":0,"syntology":null},{"paper":null,"slug":"improvement-strategies-for-few-shot-learning","title":"Improvement Strategies for Few-Shot Learning in OCT Image Classification of Rare Retinal Diseases","date":"2025-05-26","arxiv_id":"2505.20149","n_code_links":0,"syntology":null},{"paper":"/paper/improving-speech-emotion-recognition-through-1","slug":"improving-speech-emotion-recognition-through-1","title":"Improving Speech Emotion Recognition Through Cross Modal Attention Alignment and Balanced Stacking Model","date":"2025-05-26","arxiv_id":"2505.20007","n_code_links":1,"syntology":null},{"paper":null,"slug":"in-context-brush-zero-shot-customized-subject","title":"In-Context Brush: Zero-shot Customized Subject Insertion with Context-Aware Latent Space Manipulation","date":"2025-05-26","arxiv_id":"2505.20271","n_code_links":0,"syntology":null},{"paper":"/paper/inference-time-alignment-in-continuous-space","slug":"inference-time-alignment-in-continuous-space","title":"Inference-time Alignment in Continuous Space","date":"2025-05-26","arxiv_id":"2505.20081","n_code_links":1,"syntology":null},{"paper":"/paper/knowtrace-bootstrapping-iterative-retrieval","slug":"knowtrace-bootstrapping-iterative-retrieval","title":"KnowTrace: Bootstrapping Iterative Retrieval-Augmented Generation with Structured Knowledge Tracing","date":"2025-05-26","arxiv_id":"2505.20245","n_code_links":1,"syntology":null},{"paper":null,"slug":"large-language-models-reasoning-stalls-an","title":"Large Language Models' Reasoning Stalls: An Investigation into the Capabilities of Frontier Models","date":"2025-05-26","arxiv_id":"2505.19676","n_code_links":0,"syntology":null},{"paper":null,"slug":"lecode-a-benchmark-dataset-for-interactive","title":"LeCoDe: A Benchmark Dataset for Interactive Legal Consultation Dialogue Evaluation","date":"2025-05-26","arxiv_id":"2505.19667","n_code_links":0,"syntology":null},{"paper":null,"slug":"llamaseg-image-segmentation-via","title":"LlamaSeg: Image Segmentation via Autoregressive Mask Generation","date":"2025-05-26","arxiv_id":"2505.19422","n_code_links":0,"syntology":null},{"paper":null,"slug":"long-context-state-space-video-world-models","title":"Long-Context State-Space Video World Models","date":"2025-05-26","arxiv_id":"2505.20171","n_code_links":0,"syntology":null},{"paper":null,"slug":"lung-nodule-segmentation-exploring-data","title":"Lung Nodule Segmentation: Exploring Data Efficiency and Advanced Architectures","date":"2025-05-26","arxiv_id":null,"n_code_links":0,"syntology":null},{"paper":null,"slug":"ma-rag-multi-agent-retrieval-augmented","title":"MA-RAG: Multi-Agent Retrieval-Augmented Generation via Collaborative Chain-of-Thought Reasoning","date":"2025-05-26","arxiv_id":"2505.20096","n_code_links":0,"syntology":null},{"paper":"/paper/memory-efficient-visual-autoregressive","slug":"memory-efficient-visual-autoregressive","title":"Memory-Efficient Visual Autoregressive Modeling with Scale-Aware KV Cache Compression","date":"2025-05-26","arxiv_id":"2505.19602","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: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["stargazerx0/scalekv"],"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":"metastnet-multimodal-meta-learning-for","title":"MetaSTNet: Multimodal Meta-learning for Cellular Traffic Conformal Prediction","date":"2025-05-26","arxiv_id":"2505.21553","n_code_links":0,"syntology":null},{"paper":null,"slug":"minimalist-softmax-attention-provably-learns","title":"Minimalist Softmax Attention Provably Learns Constrained Boolean Functions","date":"2025-05-26","arxiv_id":"2505.19531","n_code_links":0,"syntology":null},{"paper":"/paper/multi-modal-brain-encoding-models-for-multi","slug":"multi-modal-brain-encoding-models-for-multi","title":"Multi-modal brain encoding models for multi-modal stimuli","date":"2025-05-26","arxiv_id":"2505.20027","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":3,"n_instrument":0,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 3 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["subbareddy248/multi-modal-brain-stimuli"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"multi-timescale-motion-decoupled-spiking","title":"Multi-Timescale Motion-Decoupled Spiking Transformer for Audio-Visual Zero-Shot Learning","date":"2025-05-26","arxiv_id":"2505.19938","n_code_links":0,"syntology":null},{"paper":null,"slug":"multimodal-machine-translation-with-visual","title":"Multimodal Machine Translation with Visual Scene Graph Pruning","date":"2025-05-26","arxiv_id":"2505.19507","n_code_links":0,"syntology":null},{"paper":"/paper/neusym-rag-hybrid-neural-symbolic-retrieval","slug":"neusym-rag-hybrid-neural-symbolic-retrieval","title":"NeuSym-RAG: Hybrid Neural Symbolic Retrieval with Multiview Structuring for PDF Question Answering","date":"2025-05-26","arxiv_id":"2505.19754","n_code_links":1,"syntology":null},{"paper":"/paper/one-surrogate-to-fool-them-all-universal","slug":"one-surrogate-to-fool-them-all-universal","title":"One Surrogate to Fool Them All: Universal, Transferable, and Targeted Adversarial Attacks with CLIP","date":"2025-05-26","arxiv_id":"2505.19840","n_code_links":1,"syntology":null},{"paper":null,"slug":"pangu-light-weight-re-initialization-for","title":"Pangu Light: Weight Re-Initialization for Pruning and Accelerating LLMs","date":"2025-05-26","arxiv_id":"2505.20155","n_code_links":0,"syntology":null},{"paper":"/paper/phi-bridging-domain-shift-in-long-term-action","slug":"phi-bridging-domain-shift-in-long-term-action","title":"PHI: Bridging Domain Shift in Long-Term Action Quality Assessment via Progressive Hierarchical Instruction","date":"2025-05-26","arxiv_id":"2505.19972","n_code_links":1,"syntology":{"ran":5,"of":6,"n_ran_checked":5,"n_instrument":0,"unverified":1,"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) · 1 unverified","official":{"repos":["zhoukanglei/phi_aqa"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"private-mev-protection-rpcs-benchmark-stud","title":"Private MEV Protection RPCs: Benchmark Stud","date":"2025-05-26","arxiv_id":"2505.19708","n_code_links":0,"syntology":null},{"paper":"/paper/rearank-reasoning-re-ranking-agent-via","slug":"rearank-reasoning-re-ranking-agent-via","title":"REARANK: Reasoning Re-ranking Agent via Reinforcement Learning","date":"2025-05-26","arxiv_id":"2505.20046","n_code_links":1,"syntology":{"ran":12,"of":18,"n_ran_checked":10,"n_instrument":2,"unverified":6,"pointer_only":4,"phrase":"12 ran (of which 0 constructed an object rather than computing a result; 10 with no instrument failure: 0 honoured, 0 violated, 10 with no contract checked; 2 where Syntology's instrument failed) · 6 unverified","official":{"repos":["lezhang7/rearank"],"state":"official (archive's flag): 12 ran","n_ran":12,"n_constructed":0,"n_ran_no_instrument_failure":10,"n_unverified":6,"ran_from_kinds":["official"]}}},{"paper":"/paper/reasonplan-unified-scene-prediction-and","slug":"reasonplan-unified-scene-prediction-and","title":"ReasonPlan: Unified Scene Prediction and Decision Reasoning for Closed-loop Autonomous Driving","date":"2025-05-26","arxiv_id":"2505.20024","n_code_links":1,"syntology":null},{"paper":null,"slug":"regularized-personalization-of-text-to-image","title":"Regularized Personalization of Text-to-Image Diffusion Models without Distributional Drift","date":"2025-05-26","arxiv_id":"2505.19519","n_code_links":0,"syntology":null},{"paper":null,"slug":"research-on-feature-fusion-and-multimodal","title":"Research on feature fusion and multimodal patent text based on graph attention network","date":"2025-05-26","arxiv_id":"2505.20188","n_code_links":0,"syntology":null},{"paper":"/paper/rethinking-text-based-protein-understanding","slug":"rethinking-text-based-protein-understanding","title":"Rethinking Text-based Protein Understanding: Retrieval or LLM?","date":"2025-05-26","arxiv_id":"2505.20354","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":0,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 0 with no instrument failure: 0 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["IDEA-XL/RAPM"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/rotation-equivariant-self-supervised-method","slug":"rotation-equivariant-self-supervised-method","title":"Rotation-Equivariant Self-Supervised Method in Image Denoising","date":"2025-05-26","arxiv_id":"2505.19618","n_code_links":1,"syntology":{"ran":8,"of":10,"n_ran_checked":6,"n_instrument":2,"unverified":2,"pointer_only":10,"phrase":"8 ran (of which 5 constructed an object rather than computing a result; 6 with no instrument failure: 1 honoured, 0 violated, 5 with no contract checked; 2 where Syntology's instrument failed) · 2 unverified","official":{"repos":["liuhanze623/adarenet"],"state":"official (archive's flag): 8 ran","n_ran":8,"n_constructed":5,"n_ran_no_instrument_failure":6,"n_unverified":2,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"sesamo-symmetry-enforcing-stochastic","title":"SESaMo: Symmetry-Enforcing Stochastic Modulation for Normalizing Flows","date":"2025-05-26","arxiv_id":"2505.19619","n_code_links":0,"syntology":null},{"paper":null,"slug":"small-language-models-architectures","title":"Small Language Models: Architectures, Techniques, Evaluation, Problems and Future Adaptation","date":"2025-05-26","arxiv_id":"2505.19529","n_code_links":0,"syntology":null},{"paper":null,"slug":"sparse2dgs-sparse-view-surface-reconstruction","title":"Sparse2DGS: Sparse-View Surface Reconstruction using 2D Gaussian Splatting with Dense Point Cloud","date":"2025-05-26","arxiv_id":"2505.19854","n_code_links":0,"syntology":null},{"paper":null,"slug":"structured-initialization-for-vision","title":"Structured Initialization for Vision Transformers","date":"2025-05-26","arxiv_id":"2505.19985","n_code_links":0,"syntology":null},{"paper":"/paper/syftr-pareto-optimal-generative-ai","slug":"syftr-pareto-optimal-generative-ai","title":"syftr: Pareto-Optimal Generative AI","date":"2025-05-26","arxiv_id":"2505.20266","n_code_links":1,"syntology":null},{"paper":"/paper/synthetic-time-series-forecasting-with","slug":"synthetic-time-series-forecasting-with","title":"Synthetic Time Series Forecasting with Transformer Architectures: Extensive Simulation Benchmarks","date":"2025-05-26","arxiv_id":"2505.20048","n_code_links":1,"syntology":null},{"paper":null,"slug":"tensorization-is-a-powerful-but-underexplored","title":"Tensorization is a powerful but underexplored tool for compression and interpretability of neural networks","date":"2025-05-26","arxiv_id":"2505.20132","n_code_links":0,"syntology":null},{"paper":"/paper/the-avengers-a-simple-recipe-for-uniting","slug":"the-avengers-a-simple-recipe-for-uniting","title":"The Avengers: A Simple Recipe for Uniting Smaller Language Models to Challenge Proprietary Giants","date":"2025-05-26","arxiv_id":"2505.19797","n_code_links":1,"syntology":null},{"paper":"/paper/the-missing-point-in-vision-transformers-for","slug":"the-missing-point-in-vision-transformers-for","title":"The Missing Point in Vision Transformers for Universal Image Segmentation","date":"2025-05-26","arxiv_id":"2505.19795","n_code_links":1,"syntology":null},{"paper":null,"slug":"training-llm-based-agents-with-synthetic-self","title":"Training LLM-Based Agents with Synthetic Self-Reflected Trajectories and Partial Masking","date":"2025-05-26","arxiv_id":"2505.20023","n_code_links":0,"syntology":null},{"paper":null,"slug":"transformer-in-protein-a-survey","title":"Transformers in Protein: A Survey","date":"2025-05-26","arxiv_id":"2505.20098","n_code_links":0,"syntology":null},{"paper":"/paper/translation-equivariance-of-normalization","slug":"translation-equivariance-of-normalization","title":"Translation-Equivariance of Normalization Layers and Aliasing in Convolutional Neural Networks","date":"2025-05-26","arxiv_id":"2505.19805","n_code_links":1,"syntology":null},{"paper":null,"slug":"uncertainty-aware-attention-heads-efficient","title":"Uncertainty-Aware Attention Heads: Efficient Unsupervised Uncertainty Quantification for LLMs","date":"2025-05-26","arxiv_id":"2505.20045","n_code_links":0,"syntology":null},{"paper":null,"slug":"understanding-transformer-from-the","title":"Understanding Transformer from the Perspective of Associative Memory","date":"2025-05-26","arxiv_id":"2505.19488","n_code_links":0,"syntology":null},{"paper":null,"slug":"underwater-diffusion-attention-network-with","title":"Underwater Diffusion Attention Network with Contrastive Language-Image Joint Learning for Underwater Image Enhancement","date":"2025-05-26","arxiv_id":"2505.19895","n_code_links":0,"syntology":null},{"paper":"/paper/vader-a-human-evaluated-benchmark-for","slug":"vader-a-human-evaluated-benchmark-for","title":"VADER: A Human-Evaluated Benchmark for Vulnerability Assessment, Detection, Explanation, and Remediation","date":"2025-05-26","arxiv_id":"2505.19395","n_code_links":1,"syntology":null},{"paper":"/paper/viscra-a-visual-chain-reasoning-attack-for","slug":"viscra-a-visual-chain-reasoning-attack-for","title":"VisCRA: A Visual Chain Reasoning Attack for Jailbreaking Multimodal Large Language Models","date":"2025-05-26","arxiv_id":"2505.19684","n_code_links":0,"syntology":{"ran":9,"of":12,"n_ran_checked":8,"n_instrument":1,"unverified":3,"pointer_only":2,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 1 where Syntology's instrument failed) · 3 unverified","official":null}},{"paper":"/paper/vscbench-bridging-the-gap-in-vision-language","slug":"vscbench-bridging-the-gap-in-vision-language","title":"VSCBench: Bridging the Gap in Vision-Language Model Safety Calibration","date":"2025-05-26","arxiv_id":"2505.20362","n_code_links":1,"syntology":null},{"paper":"/paper/weatheredit-controllable-weather-editing-with","slug":"weatheredit-controllable-weather-editing-with","title":"WeatherEdit: Controllable Weather Editing with 4D Gaussian Field","date":"2025-05-26","arxiv_id":"2505.20471","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-smart-healthcare-system-for-monkeypox-skin","title":"A Smart Healthcare System for Monkeypox Skin Lesion Detection and Tracking","date":"2025-05-25","arxiv_id":"2505.19023","n_code_links":0,"syntology":null},{"paper":"/paper/adgsyn-dual-stream-learning-for-efficient","slug":"adgsyn-dual-stream-learning-for-efficient","title":"ADGSyn: Dual-Stream Learning for Efficient Anticancer Drug Synergy Prediction","date":"2025-05-25","arxiv_id":"2505.19144","n_code_links":1,"syntology":null},{"paper":null,"slug":"ai4math-a-native-spanish-benchmark-for","title":"AI4Math: A Native Spanish Benchmark for University-Level Mathematical Reasoning in Large Language Models","date":"2025-05-25","arxiv_id":"2505.18978","n_code_links":0,"syntology":null},{"paper":null,"slug":"aspo-adaptive-sentence-level-preference","title":"ASPO: Adaptive Sentence-Level Preference Optimization for Fine-Grained Multimodal Reasoning","date":"2025-05-25","arxiv_id":"2505.19100","n_code_links":0,"syntology":null},{"paper":"/paper/assistant-guided-mitigation-of-teacher","slug":"assistant-guided-mitigation-of-teacher","title":"Assistant-Guided Mitigation of Teacher Preference Bias in LLM-as-a-Judge","date":"2025-05-25","arxiv_id":"2505.19176","n_code_links":1,"syntology":null},{"paper":null,"slug":"bayesian-sparse-modeling-for-interpretable","title":"Bayesian sparse modeling for interpretable prediction of hydroxide ion conductivity in anion-conductive polymer membranes","date":"2025-05-25","arxiv_id":"2505.19044","n_code_links":0,"syntology":null},{"paper":null,"slug":"benchmarking-large-language-models-for-6","title":"Benchmarking Large Language Models for Cyberbullying Detection in Real-World YouTube Comments","date":"2025-05-25","arxiv_id":"2505.18927","n_code_links":0,"syntology":null},{"paper":"/paper/cdpdnet-integrating-text-guidance-with-hybrid","slug":"cdpdnet-integrating-text-guidance-with-hybrid","title":"CDPDNet: Integrating Text Guidance with Hybrid Vision Encoders for Medical Image Segmentation","date":"2025-05-25","arxiv_id":"2505.18958","n_code_links":1,"syntology":null},{"paper":"/paper/communication-efficient-multi-device","slug":"communication-efficient-multi-device","title":"Communication-Efficient Multi-Device Inference Acceleration for Transformer Models","date":"2025-05-25","arxiv_id":"2505.19342","n_code_links":1,"syntology":null},{"paper":"/paper/conventional-contrastive-learning-often-falls","slug":"conventional-contrastive-learning-often-falls","title":"Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data","date":"2025-05-25","arxiv_id":"2505.19274","n_code_links":1,"syntology":null},{"paper":null,"slug":"creatidesign-a-unified-multi-conditional","title":"CreatiDesign: A Unified Multi-Conditional Diffusion Transformer for Creative Graphic Design","date":"2025-05-25","arxiv_id":"2505.19114","n_code_links":0,"syntology":null},{"paper":null,"slug":"curvature-dynamic-black-box-attack-revisiting","title":"Curvature Dynamic Black-box Attack: revisiting adversarial robustness via dynamic curvature estimation","date":"2025-05-25","arxiv_id":"2505.19194","n_code_links":0,"syntology":null},{"paper":null,"slug":"disentangled-human-body-representation-based","title":"Disentangled Human Body Representation Based on Unsupervised Semantic-Aware Learning","date":"2025-05-25","arxiv_id":"2505.19049","n_code_links":0,"syntology":null},{"paper":"/paper/dlf-enhancing-explicit-implicit-interaction","slug":"dlf-enhancing-explicit-implicit-interaction","title":"DLF: Enhancing Explicit-Implicit Interaction via Dynamic Low-Order-Aware Fusion for CTR Prediction","date":"2025-05-25","arxiv_id":"2505.19182","n_code_links":1,"syntology":null},{"paper":"/paper/dream-drafting-with-refined-target-features","slug":"dream-drafting-with-refined-target-features","title":"DREAM: Drafting with Refined Target Features and Entropy-Adaptive Cross-Attention Fusion for Multimodal Speculative Decoding","date":"2025-05-25","arxiv_id":"2505.19201","n_code_links":1,"syntology":null},{"paper":null,"slug":"drivex-omni-scene-modeling-for-learning","title":"DriveX: Omni Scene Modeling for Learning Generalizable World Knowledge in Autonomous Driving","date":"2025-05-25","arxiv_id":"2505.19239","n_code_links":0,"syntology":null},{"paper":null,"slug":"eventegohands-event-based-egocentric-3d-hand","title":"EventEgoHands: Event-based Egocentric 3D Hand Mesh Reconstruction","date":"2025-05-25","arxiv_id":"2505.19169","n_code_links":0,"syntology":null},{"paper":null,"slug":"exploring-magnitude-preservation-and-rotation","title":"Exploring Magnitude Preservation and Rotation Modulation in Diffusion Transformers","date":"2025-05-25","arxiv_id":"2505.19122","n_code_links":0,"syntology":null}],"record_sha256":"e24ad65ce0aaa9f4fd1fa1117a69d9e07338bebd59869f52aa130a60d7cd56d4","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}