{"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/focus/papers/16","list_of":"/method/focus","method":"Focus","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":16,"pages_in_order":154,"rows_per_page":100,"rows":[1501,1600],"of":15340,"counts":{"archive_papers_tagged":15340,"with_a_code_link":5193,"where_syntology_ran_a_sample":1419,"not_listed_spam_title":0,"listed":15340,"listed_where_code_ran":1419,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":1210,"every_run_a_failure_of_syntologys_instrument":209,"listed_with_a_run_with_no_instrument_failure":1210,"listed_every_run_a_failure_of_syntologys_instrument":209,"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/focus","prev":"/method/focus/papers/15","next":"/method/focus/papers/17","papers":[{"paper":null,"slug":"viclaim-a-multilingual-multilabel-dataset-for","title":"ViClaim: A Multilingual Multilabel Dataset for Automatic Claim Detection in Videos","date":"2025-04-17","arxiv_id":"2504.12882","n_code_links":0,"syntology":null},{"paper":null,"slug":"why-ask-one-when-you-can-ask-k-two-stage","title":"Why Ask One When You Can Ask $k$? Two-Stage Learning-to-Defer to the Top-$k$ Experts","date":"2025-04-17","arxiv_id":"2504.12988","n_code_links":0,"syntology":null},{"paper":null,"slug":"ai-safety-should-prioritize-the-future-of","title":"AI Safety Should Prioritize the Future of Work","date":"2025-04-16","arxiv_id":"2504.13959","n_code_links":0,"syntology":null},{"paper":"/paper/causality-enhanced-decision-making-for","slug":"causality-enhanced-decision-making-for","title":"Causality-enhanced Decision-Making for Autonomous Mobile Robots in Dynamic Environments","date":"2025-04-16","arxiv_id":"2504.11901","n_code_links":1,"syntology":null},{"paper":null,"slug":"clarifying-ambiguities-on-the-role-of","title":"Clarifying Ambiguities: on the Role of Ambiguity Types in Prompting Methods for Clarification Generation","date":"2025-04-16","arxiv_id":"2504.12113","n_code_links":0,"syntology":null},{"paper":null,"slug":"dg-mvp-3d-domain-generalization-via-multiple","title":"DG-MVP: 3D Domain Generalization via Multiple Views of Point Clouds for Classification","date":"2025-04-16","arxiv_id":"2504.12456","n_code_links":0,"syntology":null},{"paper":null,"slug":"diffusion-based-robust-lidar-place","title":"Diffusion Based Robust LiDAR Place Recognition","date":"2025-04-16","arxiv_id":"2504.12412","n_code_links":0,"syntology":null},{"paper":null,"slug":"dm-osvp-one-shot-view-planning-using-3d","title":"DM-OSVP++: One-Shot View Planning Using 3D Diffusion Models for Active RGB-Based Object Reconstruction","date":"2025-04-16","arxiv_id":"2504.11674","n_code_links":0,"syntology":null},{"paper":"/paper/evaluating-menu-ocr-and-translation-a","slug":"evaluating-menu-ocr-and-translation-a","title":"Evaluating Menu OCR and Translation: A Benchmark for Aligning Human and Automated Evaluations in Large Vision-Language Models","date":"2025-04-16","arxiv_id":"2504.13945","n_code_links":1,"syntology":null},{"paper":null,"slug":"finding-flawed-fictions-evaluating-complex","title":"Finding Flawed Fictions: Evaluating Complex Reasoning in Language Models via Plot Hole Detection","date":"2025-04-16","arxiv_id":"2504.11900","n_code_links":0,"syntology":null},{"paper":"/paper/focusedad-character-centric-movie-audio","slug":"focusedad-character-centric-movie-audio","title":"FocusedAD: Character-centric Movie Audio Description","date":"2025-04-16","arxiv_id":"2504.12157","n_code_links":1,"syntology":null},{"paper":"/paper/optimal-packing-of-attractor-states-in-neural","slug":"optimal-packing-of-attractor-states-in-neural","title":"Optimal packing of attractor states in neural representations","date":"2025-04-16","arxiv_id":"2504.12429","n_code_links":1,"syntology":null},{"paper":null,"slug":"optimizing-compound-retrieval-systems","title":"Optimizing Compound Retrieval Systems","date":"2025-04-16","arxiv_id":"2504.12063","n_code_links":0,"syntology":null},{"paper":null,"slug":"prognosis-of-lithium-ion-battery-health-with","title":"Prognosis Of Lithium-Ion Battery Health with Hybrid EKF-CNN+LSTM Model Using Differential Capacity","date":"2025-04-16","arxiv_id":"2504.13956","n_code_links":0,"syntology":null},{"paper":null,"slug":"recent-advance-in-3d-object-and-scene","title":"Recent Advance in 3D Object and Scene Generation: A Survey","date":"2025-04-16","arxiv_id":"2504.11734","n_code_links":0,"syntology":null},{"paper":null,"slug":"salad-improving-robustness-and-generalization","title":"SALAD: Improving Robustness and Generalization through Contrastive Learning with Structure-Aware and LLM-Driven Augmented Data","date":"2025-04-16","arxiv_id":"2504.12185","n_code_links":0,"syntology":null},{"paper":null,"slug":"selective-demonstration-retrieval-for","title":"Selective Demonstration Retrieval for Improved Implicit Hate Speech Detection","date":"2025-04-16","arxiv_id":"2504.12082","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-a-general-purpose-zero-shot-synthetic","title":"Towards a General-Purpose Zero-Shot Synthetic Low-Light Image and Video Pipeline","date":"2025-04-16","arxiv_id":"2504.12169","n_code_links":0,"syntology":null},{"paper":null,"slug":"trend-filtered-mixture-of-experts-for","title":"Trend Filtered Mixture of Experts for Automated Gating of High-Frequency Flow Cytometry Data","date":"2025-04-16","arxiv_id":"2504.12287","n_code_links":0,"syntology":null},{"paper":null,"slug":"unveiling-hidden-collaboration-within-mixture","title":"Unveiling Hidden Collaboration within Mixture-of-Experts in Large Language Models","date":"2025-04-16","arxiv_id":"2504.12359","n_code_links":0,"syntology":null},{"paper":"/paper/zooming-in-on-fakes-a-novel-dataset-for","slug":"zooming-in-on-fakes-a-novel-dataset-for","title":"Zooming In on Fakes: A Novel Dataset for Localized AI-Generated Image Detection with Forgery Amplification Approach","date":"2025-04-16","arxiv_id":"2504.11922","n_code_links":1,"syntology":null},{"paper":"/paper/3d-wavelet-convolutions-with-extended","slug":"3d-wavelet-convolutions-with-extended","title":"3D Wavelet Convolutions with Extended Receptive Fields for Hyperspectral Image Classification","date":"2025-04-15","arxiv_id":"2504.10795","n_code_links":1,"syntology":null},{"paper":"/paper/a-minimalist-approach-to-llm-reasoning-from","slug":"a-minimalist-approach-to-llm-reasoning-from","title":"A Minimalist Approach to LLM Reasoning: from Rejection Sampling to Reinforce","date":"2025-04-15","arxiv_id":"2504.11343","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":["rlhflow/minimal-rl"],"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/a-real-time-anomaly-detection-method-for","slug":"a-real-time-anomaly-detection-method-for","title":"A real-time anomaly detection method for robots based on a flexible and sparse latent space","date":"2025-04-15","arxiv_id":"2504.11170","n_code_links":1,"syntology":null},{"paper":"/paper/adaptive-decision-boundary-for-few-shot-class","slug":"adaptive-decision-boundary-for-few-shot-class","title":"Adaptive Decision Boundary for Few-Shot Class-Incremental Learning","date":"2025-04-15","arxiv_id":"2504.10976","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":["yongzhang-tan/adbs"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":"/paper/afire-anatomy-driven-self-supervised-learning","slug":"afire-anatomy-driven-self-supervised-learning","title":"AFiRe: Anatomy-Driven Self-Supervised Learning for Fine-Grained Representation in Radiographic Images","date":"2025-04-15","arxiv_id":"2504.10972","n_code_links":1,"syntology":null},{"paper":null,"slug":"agentpolyp-accurate-polyp-segmentation-via","title":"AgentPolyp: Accurate Polyp Segmentation via Image Enhancement Agent","date":"2025-04-15","arxiv_id":"2504.10978","n_code_links":0,"syntology":null},{"paper":null,"slug":"atlasd-automatic-local-symmetry-discovery","title":"AtlasD: Automatic Local Symmetry Discovery","date":"2025-04-15","arxiv_id":"2504.10777","n_code_links":0,"syntology":null},{"paper":"/paper/cancer-myth-evaluating-ai-chatbot-on-patient","slug":"cancer-myth-evaluating-ai-chatbot-on-patient","title":"Cancer-Myth: Evaluating AI Chatbot on Patient Questions with False Presuppositions","date":"2025-04-15","arxiv_id":"2504.11373","n_code_links":1,"syntology":null},{"paper":null,"slug":"csplade-learned-sparse-retrieval-with-causal","title":"CSPLADE: Learned Sparse Retrieval with Causal Language Models","date":"2025-04-15","arxiv_id":"2504.10816","n_code_links":0,"syntology":null},{"paper":null,"slug":"defending-against-frequency-based-attacks","title":"Defending Against Frequency-Based Attacks with Diffusion Models","date":"2025-04-15","arxiv_id":"2504.11034","n_code_links":0,"syntology":null},{"paper":"/paper/emergence-of-goal-directed-behaviors-via","slug":"emergence-of-goal-directed-behaviors-via","title":"Emergence of Goal-Directed Behaviors via Active Inference with Self-Prior","date":"2025-04-15","arxiv_id":"2504.11075","n_code_links":1,"syntology":null},{"paper":null,"slug":"exploring-the-role-of-kg-based-rag-in","title":"Exploring the Role of Knowledge Graph-Based RAG in Japanese Medical Question Answering with Small-Scale LLMs","date":"2025-04-15","arxiv_id":"2504.10982","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-gaze-to-insight-bridging-human-visual","title":"From Gaze to Insight: Bridging Human Visual Attention and Vision Language Model Explanation for Weakly-Supervised Medical Image Segmentation","date":"2025-04-15","arxiv_id":"2504.11368","n_code_links":0,"syntology":null},{"paper":null,"slug":"from-misleading-queries-to-accurate-answers-a","title":"From Misleading Queries to Accurate Answers: A Three-Stage Fine-Tuning Method for LLMs","date":"2025-04-15","arxiv_id":"2504.11277","n_code_links":0,"syntology":null},{"paper":"/paper/influence-maximization-in-temporal-social","slug":"influence-maximization-in-temporal-social","title":"Influence Maximization in Temporal Social Networks with a Cold-Start Problem: A Supervised Approach","date":"2025-04-15","arxiv_id":"2504.11245","n_code_links":1,"syntology":null},{"paper":"/paper/masculine-defaults-via-gendered-discourse-in","slug":"masculine-defaults-via-gendered-discourse-in","title":"Masculine Defaults via Gendered Discourse in Podcasts and Large Language Models","date":"2025-04-15","arxiv_id":"2504.11431","n_code_links":1,"syntology":null},{"paper":null,"slug":"measures-of-variability-for-risk-averse","title":"Measures of Variability for Risk-averse Policy Gradient","date":"2025-04-15","arxiv_id":"2504.11412","n_code_links":0,"syntology":null},{"paper":"/paper/mscrs-multi-modal-semantic-graph-prompt","slug":"mscrs-multi-modal-semantic-graph-prompt","title":"MSCRS: Multi-modal Semantic Graph Prompt Learning Framework for Conversational Recommender Systems","date":"2025-04-15","arxiv_id":"2504.10921","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-device-watermarking-a-socio-technical","title":"On-Device Watermarking: A Socio-Technical Imperative For Authenticity In The Age of Generative AI","date":"2025-04-15","arxiv_id":"2504.13205","n_code_links":0,"syntology":null},{"paper":null,"slug":"patfinger-prompt-adapted-transferable","title":"PATFinger: Prompt-Adapted Transferable Fingerprinting against Unauthorized Multimodal Dataset Usage","date":"2025-04-15","arxiv_id":"2504.11509","n_code_links":0,"syntology":null},{"paper":null,"slug":"patrolvision-automated-license-plate","title":"PatrolVision: Automated License Plate Recognition in the wild","date":"2025-04-15","arxiv_id":"2504.10810","n_code_links":0,"syntology":null},{"paper":null,"slug":"perceptions-of-agentic-ai-in-organizations","title":"Perceptions of Agentic AI in Organizations: Implications for Responsible AI and ROI","date":"2025-04-15","arxiv_id":"2504.11564","n_code_links":0,"syntology":null},{"paper":null,"slug":"power-scaled-bayesian-inference-with-score","title":"Power-scaled Bayesian Inference with Score-based Generative Models","date":"2025-04-15","arxiv_id":"2504.10807","n_code_links":0,"syntology":null},{"paper":"/paper/propaganda-via-ai-a-study-on-semantic","slug":"propaganda-via-ai-a-study-on-semantic","title":"Propaganda via AI? A Study on Semantic Backdoors in Large Language Models","date":"2025-04-15","arxiv_id":"2504.12344","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":["naymyatmin/raven"],"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":["found_in_text","official"]}}},{"paper":null,"slug":"protflow-fast-protein-sequence-design-via","title":"ProtFlow: Fast Protein Sequence Design via Flow Matching on Compressed Protein Language Model Embeddings","date":"2025-04-15","arxiv_id":"2504.10983","n_code_links":0,"syntology":null},{"paper":null,"slug":"raid-an-in-training-defense-against-attribute","title":"RAID: An In-Training Defense against Attribute Inference Attacks in Recommender Systems","date":"2025-04-15","arxiv_id":"2504.11510","n_code_links":0,"syntology":null},{"paper":"/paper/reinforcing-compositional-retrieval","slug":"reinforcing-compositional-retrieval","title":"Reinforcing Compositional Retrieval: Retrieving Step-by-Step for Composing Informative Contexts","date":"2025-04-15","arxiv_id":"2504.11420","n_code_links":1,"syntology":null},{"paper":null,"slug":"revealing-covert-attention-by-analyzing-human","title":"Revealing Covert Attention by Analyzing Human and Reinforcement Learning Agent Gameplay","date":"2025-04-15","arxiv_id":"2504.11118","n_code_links":0,"syntology":null},{"paper":null,"slug":"rezero-enhancing-llm-search-ability-by-trying","title":"ReZero: Enhancing LLM search ability by trying one-more-time","date":"2025-04-15","arxiv_id":"2504.11001","n_code_links":0,"syntology":null},{"paper":null,"slug":"s-2-teacher-step-by-step-teacher-for-sparsely","title":"S$^2$Teacher: Step-by-step Teacher for Sparsely Annotated Oriented Object Detection","date":"2025-04-15","arxiv_id":"2504.11111","n_code_links":0,"syntology":null},{"paper":null,"slug":"single-input-multi-output-model-merging","title":"Single-Input Multi-Output Model Merging: Leveraging Foundation Models for Dense Multi-Task Learning","date":"2025-04-15","arxiv_id":"2504.11268","n_code_links":0,"syntology":null},{"paper":"/paper/towards-efficient-partially-relevant-video","slug":"towards-efficient-partially-relevant-video","title":"Towards Efficient Partially Relevant Video Retrieval with Active Moment Discovering","date":"2025-04-15","arxiv_id":"2504.10920","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":1,"n_instrument":0,"unverified":0,"pointer_only":1,"phrase":"1 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified","official":{"repos":["songpipi/amdnet"],"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":"vimo-a-generative-visual-gui-world-model-for","title":"ViMo: A Generative Visual GUI World Model for App Agents","date":"2025-04-15","arxiv_id":"2504.13936","n_code_links":0,"syntology":null},{"paper":"/paper/visual-re-ranking-with-non-visual-side","slug":"visual-re-ranking-with-non-visual-side","title":"Visual Re-Ranking with Non-Visual Side Information","date":"2025-04-15","arxiv_id":"2504.11134","n_code_links":1,"syntology":null},{"paper":null,"slug":"augmented-relevance-datasets-with-fine-tuned","title":"Augmented Relevance Datasets with Fine-Tuned Small LLMs","date":"2025-04-14","arxiv_id":"2504.09816","n_code_links":0,"syntology":null},{"paper":"/paper/beyond-degradation-redundancy-contrastive","slug":"beyond-degradation-redundancy-contrastive","title":"Beyond Degradation Redundancy: Contrastive Prompt Learning for All-in-One Image Restoration","date":"2025-04-14","arxiv_id":"2504.09973","n_code_links":1,"syntology":null},{"paper":null,"slug":"beyond-worst-case-online-classification-vc","title":"Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks","date":"2025-04-14","arxiv_id":"2504.10598","n_code_links":0,"syntology":null},{"paper":null,"slug":"camerabench-benchmarking-visual-reasoning-in","title":"CameraBench: Benchmarking Visual Reasoning in MLLMs via Photography","date":"2025-04-14","arxiv_id":"2504.10090","n_code_links":0,"syntology":null},{"paper":"/paper/can-llms-generate-tabular-summaries-of","slug":"can-llms-generate-tabular-summaries-of","title":"Can LLMs Generate Tabular Summaries of Science Papers? Rethinking the Evaluation Protocol","date":"2025-04-14","arxiv_id":"2504.10284","n_code_links":1,"syntology":null},{"paper":null,"slug":"finger-content-aware-fine-grained-evaluation","title":"FingER: Content Aware Fine-grained Evaluation with Reasoning for AI-Generated Videos","date":"2025-04-14","arxiv_id":"2504.10358","n_code_links":0,"syntology":null},{"paper":"/paper/focus-on-local-finding-reliable-1","slug":"focus-on-local-finding-reliable-1","title":"Focus on Local: Finding Reliable Discriminative Regions for Visual Place Recognition","date":"2025-04-14","arxiv_id":"2504.09881","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":0,"phrase":"3 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["chenshunpeng/FoL"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"gradient-modelling-of-memristive-systems","title":"Gradient modelling of memristive systems","date":"2025-04-14","arxiv_id":"2504.10093","n_code_links":0,"syntology":null},{"paper":null,"slug":"igl-dt-iterative-global-local-feature","title":"IGL-DT: Iterative Global-Local Feature Learning with Dual-Teacher Semantic Segmentation Framework under Limited Annotation Scheme","date":"2025-04-14","arxiv_id":"2504.09797","n_code_links":0,"syntology":null},{"paper":null,"slug":"mimu-mitigating-multiple-shortcut-learning","title":"MiMu: Mitigating Multiple Shortcut Learning Behavior of Transformers","date":"2025-04-14","arxiv_id":"2504.10551","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-precomputation-and-caching-in-information","title":"On Precomputation and Caching in Information Retrieval Experiments with Pipeline Architectures","date":"2025-04-14","arxiv_id":"2504.09984","n_code_links":0,"syntology":null},{"paper":null,"slug":"physical-scales-matter-the-role-of-receptive","title":"Physical Scales Matter: The Role of Receptive Fields and Advection in Satellite-Based Thunderstorm Nowcasting with Convolutional Neural Networks","date":"2025-04-14","arxiv_id":"2504.09994","n_code_links":0,"syntology":null},{"paper":null,"slug":"progressive-transfer-learning-for-multi-pass","title":"Progressive Transfer Learning for Multi-Pass Fundus Image Restoration","date":"2025-04-14","arxiv_id":"2504.10025","n_code_links":0,"syntology":null},{"paper":"/paper/relation-rich-visual-document-generator-for","slug":"relation-rich-visual-document-generator-for","title":"Relation-Rich Visual Document Generator for Visual Information Extraction","date":"2025-04-14","arxiv_id":"2504.10659","n_code_links":1,"syntology":null},{"paper":null,"slug":"relative-illumination-fields-learning-medium","title":"Relative Illumination Fields: Learning Medium and Light Independent Underwater Scenes","date":"2025-04-14","arxiv_id":"2504.10024","n_code_links":0,"syntology":null},{"paper":null,"slug":"rhythm-generation-robustness-and-control-in","title":"Rhythm Generation, Robustness, and Control in Stick Insect Locomotion: Modeling and Analysis","date":"2025-04-14","arxiv_id":"2504.11494","n_code_links":0,"syntology":null},{"paper":null,"slug":"sidecar-a-structure-preserving-framework-for","title":"Sidecar: A Structure-Preserving Framework for Solving Partial Differential Equations with Neural Networks","date":"2025-04-14","arxiv_id":"2504.10273","n_code_links":0,"syntology":null},{"paper":"/paper/silvar-med-a-speech-driven-visual-language","slug":"silvar-med-a-speech-driven-visual-language","title":"SilVar-Med: A Speech-Driven Visual Language Model for Explainable Abnormality Detection in Medical Imaging","date":"2025-04-14","arxiv_id":"2504.10642","n_code_links":1,"syntology":null},{"paper":"/paper/vibrantleaves-a-principled-parametric-image","slug":"vibrantleaves-a-principled-parametric-image","title":"VibrantLeaves: A principled parametric image generator for training deep restoration models","date":"2025-04-14","arxiv_id":"2504.10201","n_code_links":1,"syntology":null},{"paper":"/paper/weight-of-thought-reasoning-exploring-neural","slug":"weight-of-thought-reasoning-exploring-neural","title":"Weight-of-Thought Reasoning: Exploring Neural Network Weights for Enhanced LLM Reasoning","date":"2025-04-14","arxiv_id":"2504.10646","n_code_links":1,"syntology":null},{"paper":null,"slug":"will-ai-shape-the-way-we-speak-the-emerging","title":"Will AI shape the way we speak? The emerging sociolinguistic influence of synthetic voices","date":"2025-04-14","arxiv_id":"2504.10650","n_code_links":0,"syntology":null},{"paper":"/paper/a-survey-on-efficient-vision-language-models","slug":"a-survey-on-efficient-vision-language-models","title":"A Survey on Efficient Vision-Language Models","date":"2025-04-13","arxiv_id":"2504.09724","n_code_links":1,"syntology":null},{"paper":null,"slug":"cheatagent-attacking-llm-empowered","title":"CheatAgent: Attacking LLM-Empowered Recommender Systems via LLM Agent","date":"2025-04-13","arxiv_id":"2504.13192","n_code_links":0,"syntology":null},{"paper":null,"slug":"distilling-transitional-pattern-to-large","title":"Distilling Transitional Pattern to Large Language Models for Multimodal Session-based Recommendation","date":"2025-04-13","arxiv_id":"2504.10538","n_code_links":0,"syntology":null},{"paper":null,"slug":"erl-mpp-evolutionary-reinforcement-learning","title":"ERL-MPP: Evolutionary Reinforcement Learning with Multi-head Puzzle Perception for Solving Large-scale Jigsaw Puzzles of Eroded Gaps","date":"2025-04-13","arxiv_id":"2504.09608","n_code_links":0,"syntology":null},{"paper":"/paper/grpo-lead-a-difficulty-aware-reinforcement-1","slug":"grpo-lead-a-difficulty-aware-reinforcement-1","title":"GRPO-LEAD: A Difficulty-Aware Reinforcement Learning Approach for Concise Mathematical Reasoning in Language Models","date":"2025-04-13","arxiv_id":"2504.09696","n_code_links":1,"syntology":{"ran":1,"of":2,"n_ran_checked":1,"n_instrument":0,"unverified":1,"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) · 1 unverified","official":{"repos":["aeroplanepaper/GRPO-LEAD"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"iterative-self-training-for-code-generation","title":"Iterative Self-Training for Code Generation via Reinforced Re-Ranking","date":"2025-04-13","arxiv_id":"2504.09643","n_code_links":0,"syntology":null},{"paper":null,"slug":"mlrc-bench-can-language-agents-solve-machine","title":"MLRC-Bench: Can Language Agents Solve Machine Learning Research Challenges?","date":"2025-04-13","arxiv_id":"2504.09702","n_code_links":0,"syntology":null},{"paper":null,"slug":"omnimamba4d-spatio-temporal-mamba-for","title":"OmniMamba4D: Spatio-temporal Mamba for longitudinal CT lesion segmentation","date":"2025-04-13","arxiv_id":"2504.09655","n_code_links":0,"syntology":null},{"paper":"/paper/revisiting-self-attentive-sequential","slug":"revisiting-self-attentive-sequential","title":"Revisiting Self-Attentive Sequential Recommendation","date":"2025-04-13","arxiv_id":"2504.09596","n_code_links":2,"syntology":null},{"paper":null,"slug":"sd-reid-view-aware-stable-diffusion-for","title":"SD-ReID: View-aware Stable Diffusion for Aerial-Ground Person Re-Identification","date":"2025-04-13","arxiv_id":"2504.09549","n_code_links":0,"syntology":null},{"paper":null,"slug":"slow-thinking-for-sequential-recommendation","title":"Slow Thinking for Sequential Recommendation","date":"2025-04-13","arxiv_id":"2504.09627","n_code_links":0,"syntology":null},{"paper":"/paper/the-structural-safety-generalization-problem","slug":"the-structural-safety-generalization-problem","title":"The Structural Safety Generalization Problem","date":"2025-04-13","arxiv_id":"2504.09712","n_code_links":1,"syntology":null},{"paper":null,"slug":"an-enhanced-iterative-deepening-search","title":"An Enhanced Iterative Deepening Search Algorithm for the Unrestricted Container Rehandling Problem","date":"2025-04-12","arxiv_id":"2504.09046","n_code_links":0,"syntology":null},{"paper":"/paper/brainprompt-multi-level-brain-prompt","slug":"brainprompt-multi-level-brain-prompt","title":"BrainPrompt: Multi-Level Brain Prompt Enhancement for Neurological Condition Identification","date":"2025-04-12","arxiv_id":"2504.16096","n_code_links":1,"syntology":null},{"paper":null,"slug":"efficient-implementation-of-reinforcement","title":"Efficient Implementation of Reinforcement Learning over Homomorphic Encryption","date":"2025-04-12","arxiv_id":"2504.09335","n_code_links":0,"syntology":null},{"paper":null,"slug":"fairace-achieving-degree-fairness-in-graph","title":"FairACE: Achieving Degree Fairness in Graph Neural Networks via Contrastive and Adversarial Group-Balanced Training","date":"2025-04-12","arxiv_id":"2504.09210","n_code_links":0,"syntology":null},{"paper":null,"slug":"notes-bank-benchmarking-neural-transcription","title":"NoTeS-Bank: Benchmarking Neural Transcription and Search for Scientific Notes Understanding","date":"2025-04-12","arxiv_id":"2504.09249","n_code_links":0,"syntology":null},{"paper":null,"slug":"probability-distribution-alignment-and-low","title":"Probability Distribution Alignment and Low-Rank Weight Decomposition for Source-Free Domain Adaptive Brain Decoding","date":"2025-04-12","arxiv_id":"2504.09109","n_code_links":0,"syntology":null},{"paper":null,"slug":"sample-efficient-algorithms-for-linear-system","title":"Sample Efficient Algorithms for Linear System Identification under Noisy Observations","date":"2025-04-12","arxiv_id":"2504.09057","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-explainable-partial-aigc-image","title":"Towards Explainable Partial-AIGC Image Quality Assessment","date":"2025-04-12","arxiv_id":"2504.09291","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-more-efficient-robust-instance","title":"Towards More Efficient, Robust, Instance-adaptive, and Generalizable Sequential Decision making","date":"2025-04-12","arxiv_id":"2504.09192","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-knowledge-guided-adversarial-defense-for","title":"A Knowledge-guided Adversarial Defense for Resisting Malicious Visual Manipulation","date":"2025-04-11","arxiv_id":"2504.08411","n_code_links":0,"syntology":null},{"paper":"/paper/boosting-the-class-incremental-learning-in-3d","slug":"boosting-the-class-incremental-learning-in-3d","title":"Boosting the Class-Incremental Learning in 3D Point Clouds via Zero-Collection-Cost Basic Shape Pre-Training","date":"2025-04-11","arxiv_id":"2504.08412","n_code_links":1,"syntology":null},{"paper":null,"slug":"code-craft-hierarchical-graph-based-code","title":"Code-Craft: Hierarchical Graph-Based Code Summarization for Enhanced Context Retrieval","date":"2025-04-11","arxiv_id":"2504.08975","n_code_links":0,"syntology":null}],"record_sha256":"92477d4ea3a92e8308c9ee754170ff976db5a1f23012bb0c218f3c31c2266573","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}