{"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/softmax/papers/7","list_of":"/method/softmax","method":"Softmax","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":7,"pages_in_order":375,"rows_per_page":100,"rows":[601,700],"of":37443,"counts":{"archive_papers_tagged":37443,"with_a_code_link":15869,"where_syntology_ran_a_sample":4578,"not_listed_spam_title":0,"listed":37443,"listed_where_code_ran":4578,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3835,"every_run_a_failure_of_syntologys_instrument":743,"listed_with_a_run_with_no_instrument_failure":3835,"listed_every_run_a_failure_of_syntologys_instrument":743,"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/softmax","prev":"/method/softmax/papers/6","next":"/method/softmax/papers/8","papers":[{"paper":null,"slug":"unigeo-taming-video-diffusion-for-unified","title":"UniGeo: Taming Video Diffusion for Unified Consistent Geometry Estimation","date":"2025-05-30","arxiv_id":"2505.24521","n_code_links":0,"syntology":null},{"paper":null,"slug":"visual-embodied-brain-let-multimodal-large","title":"Visual Embodied Brain: Let Multimodal Large Language Models See, Think, and Control in Spaces","date":"2025-05-30","arxiv_id":"2506.00123","n_code_links":0,"syntology":null},{"paper":null,"slug":"when-gpt-spills-the-tea-comprehensive","title":"When GPT Spills the Tea: Comprehensive Assessment of Knowledge File Leakage in GPTs","date":"2025-05-30","arxiv_id":"2506.00197","n_code_links":0,"syntology":null},{"paper":null,"slug":"2506-03177","title":"Deep Learning-Based Breast Cancer Detection in Mammography: A Multi-Center Validation Study in Thai Population","date":"2025-05-29","arxiv_id":"2506.03177","n_code_links":0,"syntology":null},{"paper":null,"slug":"accelerated-training-of-federated-learning","title":"Accelerated Training of Federated Learning via Second-Order Methods","date":"2025-05-29","arxiv_id":"2505.23588","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-semantic-and-label-perturbation","slug":"adversarial-semantic-and-label-perturbation","title":"Adversarial Semantic and Label Perturbation Attack for Pedestrian Attribute Recognition","date":"2025-05-29","arxiv_id":"2505.23313","n_code_links":2,"syntology":null},{"paper":"/paper/anchorattention-difference-aware-sparse","slug":"anchorattention-difference-aware-sparse","title":"AnchorAttention: Difference-Aware Sparse Attention with Stripe Granularity","date":"2025-05-29","arxiv_id":"2505.23520","n_code_links":1,"syntology":null},{"paper":null,"slug":"argus-vision-centric-reasoning-with-grounded","title":"Argus: Vision-Centric Reasoning with Grounded Chain-of-Thought","date":"2025-05-29","arxiv_id":"2505.23766","n_code_links":0,"syntology":null},{"paper":null,"slug":"atlas-learning-to-optimally-memorize-the","title":"ATLAS: Learning to Optimally Memorize the Context at Test Time","date":"2025-05-29","arxiv_id":"2505.23735","n_code_links":0,"syntology":null},{"paper":null,"slug":"bayesian-optimization-from-human-feedback","title":"Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds","date":"2025-05-29","arxiv_id":"2505.23673","n_code_links":0,"syntology":null},{"paper":null,"slug":"bounded-rationality-for-llms-satisficing","title":"Bounded Rationality for LLMs: Satisficing Alignment at Inference-Time","date":"2025-05-29","arxiv_id":"2505.23729","n_code_links":0,"syntology":null},{"paper":null,"slug":"bridging-geometric-and-semantic-foundation","title":"Bridging Geometric and Semantic Foundation Models for Generalized Monocular Depth Estimation","date":"2025-05-29","arxiv_id":"2505.23400","n_code_links":0,"syntology":null},{"paper":null,"slug":"bridging-the-gap-between-semantic-and-user","title":"Bridging the Gap Between Semantic and User Preference Spaces for Multi-modal Music Representation Learning","date":"2025-05-29","arxiv_id":"2505.23298","n_code_links":0,"syntology":null},{"paper":null,"slug":"cf-detr-coarse-to-fine-transformer-for-real","title":"CF-DETR: Coarse-to-Fine Transformer for Real-Time Object Detection","date":"2025-05-29","arxiv_id":"2505.23317","n_code_links":0,"syntology":null},{"paper":null,"slug":"characterizing-the-expressivity-of","title":"Characterizing the Expressivity of Transformer Language Models","date":"2025-05-29","arxiv_id":"2505.23623","n_code_links":0,"syntology":null},{"paper":null,"slug":"clac-at-semeval-2025-task-6-a-multi","title":"CLaC at SemEval-2025 Task 6: A Multi-Architecture Approach for Corporate Environmental Promise Verification","date":"2025-05-29","arxiv_id":"2505.23538","n_code_links":0,"syntology":null},{"paper":null,"slug":"clip-ae-clip-assisted-cross-view-audio-visual","title":"CLIP-AE: CLIP-assisted Cross-view Audio-Visual Enhancement for Unsupervised Temporal Action Localization","date":"2025-05-29","arxiv_id":"2505.23524","n_code_links":0,"syntology":null},{"paper":null,"slug":"continuous-chain-of-thought-enables-parallel","title":"Continuous Chain of Thought Enables Parallel Exploration and Reasoning","date":"2025-05-29","arxiv_id":"2505.23648","n_code_links":0,"syntology":null},{"paper":"/paper/cora-correspondence-aware-image-editing-using","slug":"cora-correspondence-aware-image-editing-using","title":"Cora: Correspondence-aware image editing using few step diffusion","date":"2025-05-29","arxiv_id":"2505.23907","n_code_links":1,"syntology":null},{"paper":null,"slug":"critical-batch-size-revisited-a-simple","title":"Critical Batch Size Revisited: A Simple Empirical Approach to Large-Batch Language Model Training","date":"2025-05-29","arxiv_id":"2505.23971","n_code_links":0,"syntology":null},{"paper":"/paper/da-vpt-semantic-guided-visual-prompt-tuning","slug":"da-vpt-semantic-guided-visual-prompt-tuning","title":"DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformers","date":"2025-05-29","arxiv_id":"2505.23694","n_code_links":1,"syntology":{"ran":4,"of":5,"n_ran_checked":4,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"4 ran (of which 4 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified; every one of the 4 samples that ran constructed an object rather than computing a result","official":{"repos":["noahsark/da-vpt"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"data-efficient-meta-models-for-evaluation-of","title":"Data-efficient Meta-models for Evaluation of Context-based Questions and Answers in LLMs","date":"2025-05-29","arxiv_id":"2505.23299","n_code_links":0,"syntology":null},{"paper":null,"slug":"datd3-depthwise-attention-twin-delayed-deep","title":"DATD3: Depthwise Attention Twin Delayed Deep Deterministic Policy Gradient For Model Free Reinforcement Learning Under Output Feedback Control","date":"2025-05-29","arxiv_id":"2505.23857","n_code_links":0,"syntology":null},{"paper":null,"slug":"daunce-data-attribution-through-uncertainty","title":"Daunce: Data Attribution through Uncertainty Estimation","date":"2025-05-29","arxiv_id":"2505.23223","n_code_links":0,"syntology":null},{"paper":null,"slug":"decom-renorm-merge-model-merging-on-the-right","title":"Decom-Renorm-Merge: Model Merging on the Right Space Improves Multitasking","date":"2025-05-29","arxiv_id":"2505.23117","n_code_links":0,"syntology":null},{"paper":"/paper/deep-modeling-and-optimization-of-medical","slug":"deep-modeling-and-optimization-of-medical","title":"Deep Modeling and Optimization of Medical Image Classification","date":"2025-05-29","arxiv_id":"2505.23040","n_code_links":1,"syntology":null},{"paper":null,"slug":"differential-gated-self-attention","title":"Differential Gated Self-Attention","date":"2025-05-29","arxiv_id":"2505.24054","n_code_links":0,"syntology":null},{"paper":null,"slug":"dimension-reduction-attack-video-generative","title":"Dimension-Reduction Attack! Video Generative Models are Experts on Controllable Image Synthesis","date":"2025-05-29","arxiv_id":"2505.23325","n_code_links":0,"syntology":null},{"paper":null,"slug":"dino-r1-incentivizing-reasoning-capability-in","title":"DINO-R1: Incentivizing Reasoning Capability in Vision Foundation Models","date":"2025-05-29","arxiv_id":"2505.24025","n_code_links":0,"syntology":null},{"paper":null,"slug":"does-machine-unlearning-truly-remove-model","title":"Does Machine Unlearning Truly Remove Model Knowledge? A Framework for Auditing Unlearning in LLMs","date":"2025-05-29","arxiv_id":"2505.23270","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-llm-based-code-generation-with","title":"Enhancing LLM-Based Code Generation with Complexity Metrics: A Feedback-Driven Approach","date":"2025-05-29","arxiv_id":"2505.23953","n_code_links":0,"syntology":null},{"paper":null,"slug":"equivariant-spherical-transformer-for","title":"Equivariant Spherical Transformer for Efficient Molecular Modeling","date":"2025-05-29","arxiv_id":"2505.23086","n_code_links":0,"syntology":null},{"paper":"/paper/evaluating-ai-capabilities-in-detecting","slug":"evaluating-ai-capabilities-in-detecting","title":"Evaluating AI capabilities in detecting conspiracy theories on YouTube","date":"2025-05-29","arxiv_id":"2505.23570","n_code_links":1,"syntology":null},{"paper":null,"slug":"from-images-to-signals-are-large-vision","title":"From Images to Signals: Are Large Vision Models Useful for Time Series Analysis?","date":"2025-05-29","arxiv_id":"2505.24030","n_code_links":0,"syntology":null},{"paper":null,"slug":"generating-fit-check-videos-with-a-handheld","title":"Generating Fit Check Videos with a Handheld Camera","date":"2025-05-29","arxiv_id":"2505.23886","n_code_links":0,"syntology":null},{"paper":null,"slug":"graph-positional-autoencoders-as-self","title":"Graph Positional Autoencoders as Self-supervised Learners","date":"2025-05-29","arxiv_id":"2505.23345","n_code_links":0,"syntology":null},{"paper":"/paper/grounded-reinforcement-learning-for-visual","slug":"grounded-reinforcement-learning-for-visual","title":"Grounded Reinforcement Learning for Visual Reasoning","date":"2025-05-29","arxiv_id":"2505.23678","n_code_links":1,"syntology":null},{"paper":null,"slug":"grower-in-the-loop-interactive-reinforcement","title":"Grower-in-the-Loop Interactive Reinforcement Learning for Greenhouse Climate Control","date":"2025-05-29","arxiv_id":"2505.23355","n_code_links":0,"syntology":null},{"paper":"/paper/how-does-response-length-affect-long-form","slug":"how-does-response-length-affect-long-form","title":"How Does Response Length Affect Long-Form Factuality","date":"2025-05-29","arxiv_id":"2505.23295","n_code_links":1,"syntology":null},{"paper":"/paper/hyperpointformer-multimodal-fusion-in-3d","slug":"hyperpointformer-multimodal-fusion-in-3d","title":"HyperPointFormer: Multimodal Fusion in 3D Space with Dual-Branch Cross-Attention Transformers","date":"2025-05-29","arxiv_id":"2505.23206","n_code_links":1,"syntology":null},{"paper":null,"slug":"identity-resolution-of-software-metadata","title":"Identity resolution of software metadata using Large Language Models","date":"2025-05-29","arxiv_id":"2505.23500","n_code_links":0,"syntology":null},{"paper":"/paper/improving-time-series-forecasting-via","slug":"improving-time-series-forecasting-via","title":"Improving Time Series Forecasting via Instance-aware Post-hoc Revision","date":"2025-05-29","arxiv_id":"2505.23583","n_code_links":0,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"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) · 1 unverified; every one of the 3 samples that ran constructed an object rather than computing a result","official":null}},{"paper":null,"slug":"interspeech-2025-urgent-speech-enhancement","title":"Interspeech 2025 URGENT Speech Enhancement Challenge","date":"2025-05-29","arxiv_id":"2505.23212","n_code_links":0,"syntology":null},{"paper":"/paper/kvzip-query-agnostic-kv-cache-compression","slug":"kvzip-query-agnostic-kv-cache-compression","title":"KVzip: Query-Agnostic KV Cache Compression with Context Reconstruction","date":"2025-05-29","arxiv_id":"2505.23416","n_code_links":1,"syntology":{"ran":9,"of":12,"n_ran_checked":4,"n_instrument":5,"unverified":3,"pointer_only":1,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 4 with no instrument failure: 0 honoured, 0 violated, 4 with no contract checked; 5 where Syntology's instrument failed) · 3 unverified","official":{"repos":["snu-mllab/kvzip"],"state":"official (archive's flag): 4 ran","n_ran":4,"n_constructed":0,"n_ran_no_instrument_failure":4,"n_unverified":3,"ran_from_kinds":["community","official","unlocated"]}}},{"paper":null,"slug":"layerpeeler-autoregressive-peeling-for-layer","title":"LayerPeeler: Autoregressive Peeling for Layer-wise Image Vectorization","date":"2025-05-29","arxiv_id":"2505.23740","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-to-regulate-a-new-event-level","title":"Learning to Regulate: A New Event-Level Dataset of Capital Control Measures","date":"2025-05-29","arxiv_id":"2505.23025","n_code_links":0,"syntology":null},{"paper":"/paper/lemore-learn-more-details-for-lightweight","slug":"lemore-learn-more-details-for-lightweight","title":"LeMoRe: Learn More Details for Lightweight Semantic Segmentation","date":"2025-05-29","arxiv_id":"2505.23093","n_code_links":1,"syntology":null},{"paper":null,"slug":"let-s-reason-formally-natural-formal-hybrid","title":"Let's Reason Formally: Natural-Formal Hybrid Reasoning Enhances LLM's Math Capability","date":"2025-05-29","arxiv_id":"2505.23703","n_code_links":0,"syntology":null},{"paper":null,"slug":"lola-low-rank-linear-attention-with-sparse","title":"LoLA: Low-Rank Linear Attention With Sparse Caching","date":"2025-05-29","arxiv_id":"2505.23666","n_code_links":0,"syntology":null},{"paper":null,"slug":"mangoleafvit-leveraging-lightweight-vision","title":"MangoLeafViT: Leveraging Lightweight Vision Transformer with Runtime Augmentation for Efficient Mango Leaf Disease Classification","date":"2025-05-29","arxiv_id":"2505.23961","n_code_links":0,"syntology":null},{"paper":null,"slug":"matryoshka-model-learning-for-improved","title":"Matryoshka Model Learning for Improved Elastic Student Models","date":"2025-05-29","arxiv_id":"2505.23337","n_code_links":0,"syntology":null},{"paper":null,"slug":"mcfnet-a-multimodal-collaborative-fusion","title":"MCFNet: A Multimodal Collaborative Fusion Network for Fine-Grained Semantic Classification","date":"2025-05-29","arxiv_id":"2505.23365","n_code_links":0,"syntology":null},{"paper":null,"slug":"mcp-safety-training-learning-to-refuse","title":"MCP Safety Training: Learning to Refuse Falsely Benign MCP Exploits using Improved Preference Alignment","date":"2025-05-29","arxiv_id":"2505.23634","n_code_links":0,"syntology":null},{"paper":null,"slug":"measuring-participant-contributions-in","title":"Measuring Participant Contributions in Decentralized Federated Learning","date":"2025-05-29","arxiv_id":"2505.23246","n_code_links":0,"syntology":null},{"paper":"/paper/mmgt-motion-mask-guided-two-stage-network-for","slug":"mmgt-motion-mask-guided-two-stage-network-for","title":"MMGT: Motion Mask Guided Two-Stage Network for Co-Speech Gesture Video Generation","date":"2025-05-29","arxiv_id":"2505.23120","n_code_links":1,"syntology":null},{"paper":null,"slug":"movi-training-free-text-conditioned-multi","title":"MOVi: Training-free Text-conditioned Multi-Object Video Generation","date":"2025-05-29","arxiv_id":"2505.22980","n_code_links":0,"syntology":null},{"paper":null,"slug":"mrag-elucidating-the-design-space-of-multi","title":"mRAG: Elucidating the Design Space of Multi-modal Retrieval-Augmented Generation","date":"2025-05-29","arxiv_id":"2505.24073","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-group-proportional-representation-for","title":"Multi-Group Proportional Representation for Text-to-Image Models","date":"2025-05-29","arxiv_id":"2505.24023","n_code_links":0,"syntology":null},{"paper":"/paper/multi-sourced-compositional-generalization-in","slug":"multi-sourced-compositional-generalization-in","title":"Multi-Sourced Compositional Generalization in Visual Question Answering","date":"2025-05-29","arxiv_id":"2505.23045","n_code_links":1,"syntology":null},{"paper":"/paper/neural-interpretable-pdes-harmonizing-fourier","slug":"neural-interpretable-pdes-harmonizing-fourier","title":"Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics Discovery","date":"2025-05-29","arxiv_id":"2505.23106","n_code_links":1,"syntology":null},{"paper":null,"slug":"on-the-validity-of-head-motion-patterns-as","title":"On the Validity of Head Motion Patterns as Generalisable Depression Biomarkers","date":"2025-05-29","arxiv_id":"2505.23427","n_code_links":0,"syntology":null},{"paper":null,"slug":"pan-crafter-learning-modality-consistent","title":"PAN-Crafter: Learning Modality-Consistent Alignment for PAN-Sharpening","date":"2025-05-29","arxiv_id":"2505.23367","n_code_links":0,"syntology":null},{"paper":null,"slug":"parameter-free-bio-inspired-channel-attention","title":"Parameter-Free Bio-Inspired Channel Attention for Enhanced Cardiac MRI Reconstruction","date":"2025-05-29","arxiv_id":"2505.23872","n_code_links":0,"syntology":null},{"paper":null,"slug":"patient-domain-supervised-contrastive","title":"Patient Domain Supervised Contrastive Learning for Lung Sound Classification Using Mobile Phone","date":"2025-05-29","arxiv_id":"2505.23132","n_code_links":0,"syntology":null},{"paper":null,"slug":"probing-association-biases-in-llm-moderation","title":"Probing Association Biases in LLM Moderation Over-Sensitivity","date":"2025-05-29","arxiv_id":"2505.23914","n_code_links":0,"syntology":null},{"paper":null,"slug":"query-routing-for-retrieval-augmented","title":"Query Routing for Retrieval-Augmented Language Models","date":"2025-05-29","arxiv_id":"2505.23052","n_code_links":0,"syntology":null},{"paper":"/paper/qwen-look-again-guiding-vision-language","slug":"qwen-look-again-guiding-vision-language","title":"Qwen Look Again: Guiding Vision-Language Reasoning Models to Re-attention Visual Information","date":"2025-05-29","arxiv_id":"2505.23558","n_code_links":1,"syntology":null},{"paper":null,"slug":"reducing-latency-in-llm-based-natural","title":"Reducing Latency in LLM-Based Natural Language Commands Processing for Robot Navigation","date":"2025-05-29","arxiv_id":"2506.00075","n_code_links":0,"syntology":null},{"paper":null,"slug":"rethinking-regularization-methods-for","title":"Rethinking Regularization Methods for Knowledge Graph Completion","date":"2025-05-29","arxiv_id":"2505.23442","n_code_links":0,"syntology":null},{"paper":null,"slug":"safecomm-what-about-safety-alignment-in-fine","title":"SafeCOMM: What about Safety Alignment in Fine-Tuned Telecom Large Language Models?","date":"2025-05-29","arxiv_id":"2506.00062","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantics-aware-human-motion-generation-from","title":"Semantics-Aware Human Motion Generation from Audio Instructions","date":"2025-05-29","arxiv_id":"2505.23465","n_code_links":0,"syntology":null},{"paper":"/paper/sentinel-attention-probing-of-proxy-models","slug":"sentinel-attention-probing-of-proxy-models","title":"Sentinel: Attention Probing of Proxy Models for LLM Context Compression with an Understanding Perspective","date":"2025-05-29","arxiv_id":"2505.23277","n_code_links":1,"syntology":null},{"paper":"/paper/table-r1-inference-time-scaling-for-table","slug":"table-r1-inference-time-scaling-for-table","title":"Table-R1: Inference-Time Scaling for Table Reasoning","date":"2025-05-29","arxiv_id":"2505.23621","n_code_links":1,"syntology":null},{"paper":"/paper/the-warmup-dilemma-how-learning-rate","slug":"the-warmup-dilemma-how-learning-rate","title":"The Warmup Dilemma: How Learning Rate Strategies Impact Speech-to-Text Model Convergence","date":"2025-05-29","arxiv_id":"2505.23420","n_code_links":1,"syntology":null},{"paper":"/paper/threading-the-needle-reweaving-chain-of","slug":"threading-the-needle-reweaving-chain-of","title":"Threading the Needle: Reweaving Chain-of-Thought Reasoning to Explain Human Label Variation","date":"2025-05-29","arxiv_id":"2505.23368","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["mainlp/cot2el"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"towards-disentangling-the-contributions-of","title":"Towards disentangling the contributions of articulation and acoustics in multimodal phoneme recognition","date":"2025-05-29","arxiv_id":"2505.24059","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-robust-overlapping-speech-detection-a","title":"Towards Robust Overlapping Speech Detection: A Speaker-Aware Progressive Approach Using WavLM","date":"2025-05-29","arxiv_id":"2505.23207","n_code_links":0,"syntology":null},{"paper":"/paper/vf-eval-evaluating-multimodal-llms-for","slug":"vf-eval-evaluating-multimodal-llms-for","title":"VF-Eval: Evaluating Multimodal LLMs for Generating Feedback on AIGC Videos","date":"2025-05-29","arxiv_id":"2505.23693","n_code_links":1,"syntology":null},{"paper":"/paper/viton-drr-details-retention-virtual-try-on","slug":"viton-drr-details-retention-virtual-try-on","title":"VITON-DRR: Details Retention Virtual Try-on via Non-rigid Registration","date":"2025-05-29","arxiv_id":"2505.23439","n_code_links":1,"syntology":null},{"paper":"/paper/zero-to-hero-zero-shot-initialization","slug":"zero-to-hero-zero-shot-initialization","title":"Zero-to-Hero: Zero-Shot Initialization Empowering Reference-Based Video Appearance Editing","date":"2025-05-29","arxiv_id":"2505.23134","n_code_links":1,"syntology":null},{"paper":"/paper/zpressor-bottleneck-aware-compression-for","slug":"zpressor-bottleneck-aware-compression-for","title":"ZPressor: Bottleneck-Aware Compression for Scalable Feed-Forward 3DGS","date":"2025-05-29","arxiv_id":"2505.23734","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":3,"n_instrument":0,"unverified":1,"pointer_only":0,"phrase":"3 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 0 honoured, 0 violated, 3 with no contract checked; 0 where Syntology's instrument failed) · 1 unverified","official":{"repos":["ziplab/ZPressor"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"agent-unirag-a-trainable-open-source-llm","title":"Agent-UniRAG: A Trainable Open-Source LLM Agent Framework for Unified Retrieval-Augmented Generation Systems","date":"2025-05-28","arxiv_id":"2505.22571","n_code_links":0,"syntology":null},{"paper":null,"slug":"are-classical-deep-neural-networks-weakly","title":"Are classical deep neural networks weakly adversarially robust?","date":"2025-05-28","arxiv_id":"2506.02016","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-enhanced-prompt-decision","title":"Attention-Enhanced Prompt Decision Transformers for UAV-Assisted Communications with AoI","date":"2025-05-28","arxiv_id":"2505.22170","n_code_links":0,"syntology":null},{"paper":"/paper/bayesian-attention-mechanism-a-probabilistic","slug":"bayesian-attention-mechanism-a-probabilistic","title":"Bayesian Attention Mechanism: A Probabilistic Framework for Positional Encoding and Context Length Extrapolation","date":"2025-05-28","arxiv_id":"2505.22842","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":2,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["ArthurSBianchessi/BAM"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"breaking-the-cloak-unveiling-chinese-cloaked","title":"Breaking the Cloak! Unveiling Chinese Cloaked Toxicity with Homophone Graph and Toxic Lexicon","date":"2025-05-28","arxiv_id":"2505.22184","n_code_links":0,"syntology":null},{"paper":"/paper/climate-finance-bench","slug":"climate-finance-bench","title":"Climate Finance Bench","date":"2025-05-28","arxiv_id":"2505.22752","n_code_links":1,"syntology":null},{"paper":null,"slug":"contextual-memory-intelligence-a-foundational","title":"Contextual Memory Intelligence -- A Foundational Paradigm for Human-AI Collaboration and Reflective Generative AI Systems","date":"2025-05-28","arxiv_id":"2506.05370","n_code_links":0,"syntology":null},{"paper":"/paper/cross-modal-rag-sub-dimensional-retrieval","slug":"cross-modal-rag-sub-dimensional-retrieval","title":"Cross-modal RAG: Sub-dimensional Retrieval-Augmented Text-to-Image Generation","date":"2025-05-28","arxiv_id":"2505.21956","n_code_links":1,"syntology":null},{"paper":"/paper/curse-of-high-dimensionality-issue-in","slug":"curse-of-high-dimensionality-issue-in","title":"Curse of High Dimensionality Issue in Transformer for Long-context Modeling","date":"2025-05-28","arxiv_id":"2505.22107","n_code_links":1,"syntology":{"ran":5,"of":8,"n_ran_checked":0,"n_instrument":5,"unverified":3,"pointer_only":8,"phrase":"5 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; 5 where Syntology's instrument failed) · 3 unverified","official":{"repos":["bolixinyu/dynamicgroupattention"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":"/paper/hidream-i1-a-high-efficient-image-generative","slug":"hidream-i1-a-high-efficient-image-generative","title":"HiDream-I1: A High-Efficient Image Generative Foundation Model with Sparse Diffusion Transformer","date":"2025-05-28","arxiv_id":"2505.22705","n_code_links":2,"syntology":{"ran":2,"of":3,"n_ran_checked":1,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["hidream-ai/hidream-e1","hidream-ai/hidream-i1"],"state":"official (archive's flag): 2 ran","n_ran":2,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":"/paper/hierarchical-material-recognition-from-local","slug":"hierarchical-material-recognition-from-local","title":"Hierarchical Material Recognition from Local Appearance","date":"2025-05-28","arxiv_id":"2505.22911","n_code_links":0,"syntology":null},{"paper":"/paper/hydranet-momentum-driven-state-space-duality","slug":"hydranet-momentum-driven-state-space-duality","title":"HydraNet: Momentum-Driven State Space Duality for Multi-Granularity Tennis Tournaments Analysis","date":"2025-05-28","arxiv_id":"2505.21882","n_code_links":1,"syntology":null},{"paper":null,"slug":"improving-qa-efficiency-with-distilbert-fine","title":"Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs","date":"2025-05-28","arxiv_id":"2505.22937","n_code_links":0,"syntology":null},{"paper":null,"slug":"judging-llms-on-a-simplex","title":"Judging LLMs on a Simplex","date":"2025-05-28","arxiv_id":"2505.21972","n_code_links":0,"syntology":null},{"paper":"/paper/large-language-models-for-depression","slug":"large-language-models-for-depression","title":"Large Language Models for Depression Recognition in Spoken Language Integrating Psychological Knowledge","date":"2025-05-28","arxiv_id":"2505.22863","n_code_links":1,"syntology":null},{"paper":null,"slug":"mitigating-audiovisual-mismatch-in-visual","title":"Mitigating Audiovisual Mismatch in Visual-Guide Audio Captioning","date":"2025-05-28","arxiv_id":"2505.22045","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-mllm-knowledge-distillation-for-out-of","title":"Multi-MLLM Knowledge Distillation for Out-of-Context News Detection","date":"2025-05-28","arxiv_id":"2505.22517","n_code_links":0,"syntology":null},{"paper":null,"slug":"multiformer-a-multi-person-pose-estimation","title":"MultiFormer: A Multi-Person Pose Estimation System Based on CSI and Attention Mechanism","date":"2025-05-28","arxiv_id":"2505.22555","n_code_links":0,"syntology":null},{"paper":"/paper/mustafar-promoting-unstructured-sparsity-for","slug":"mustafar-promoting-unstructured-sparsity-for","title":"Mustafar: Promoting Unstructured Sparsity for KV Cache Pruning in LLM Inference","date":"2025-05-28","arxiv_id":"2505.22913","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":["dhjoo98/mustafar"],"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"]}}}],"record_sha256":"e14699091fdd6957b1ffe35e42b40cde8130bd16a887d4bf4819a55ae8fa389e","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}