{"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/36","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":36,"pages_in_order":375,"rows_per_page":100,"rows":[3501,3600],"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/35","next":"/method/softmax/papers/37","papers":[{"paper":null,"slug":"evaluating-the-generalizability-of-llms-in","title":"Evaluating the Generalizability of LLMs in Automated Program Repair","date":"2025-03-12","arxiv_id":"2503.09217","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-visual-explanations-of-attention","title":"Evaluating Visual Explanations of Attention Maps for Transformer-based Medical Imaging","date":"2025-03-12","arxiv_id":"2503.09535","n_code_links":0,"syntology":null},{"paper":null,"slug":"fcas-fine-grained-cardiac-image-synthesis","title":"FCaS: Fine-grained Cardiac Image Synthesis based on 3D Template Conditional Diffusion Model","date":"2025-03-12","arxiv_id":"2503.09560","n_code_links":0,"syntology":null},{"paper":null,"slug":"finding-the-muses-identifying-coresets","title":"Finding the Muses: Identifying Coresets through Loss Trajectories","date":"2025-03-12","arxiv_id":"2503.09721","n_code_links":0,"syntology":null},{"paper":null,"slug":"genome-evolution-in-and-endangered-freshwater","title":"Genome evolution in an endangered freshwater mussel","date":"2025-03-12","arxiv_id":"2503.09711","n_code_links":0,"syntology":null},{"paper":null,"slug":"gigp-a-global-information-interacting-and","title":"GIGP: A Global Information Interacting and Geometric Priors Focusing Framework for Semi-supervised Medical Image Segmentation","date":"2025-03-12","arxiv_id":"2503.09355","n_code_links":0,"syntology":null},{"paper":"/paper/how-to-protect-yourself-from-5g-radiation","slug":"how-to-protect-yourself-from-5g-radiation","title":"How to Protect Yourself from 5G Radiation? Investigating LLM Responses to Implicit Misinformation","date":"2025-03-12","arxiv_id":"2503.09598","n_code_links":1,"syntology":null},{"paper":null,"slug":"incomplete-multi-view-clustering-via-2","title":"Incomplete Multi-view Clustering via Diffusion Contrastive Generation","date":"2025-03-12","arxiv_id":"2503.09185","n_code_links":0,"syntology":null},{"paper":null,"slug":"mapping-fmri-signal-and-image-stimuli-in-an","title":"Mapping fMRI Signal and Image Stimuli in an Artificial Neural Network Latent Space: Bringing Artificial and Natural Minds Together","date":"2025-03-12","arxiv_id":"2503.19923","n_code_links":0,"syntology":null},{"paper":null,"slug":"memory-enhanced-retrieval-augmentation-for","title":"Memory-enhanced Retrieval Augmentation for Long Video Understanding","date":"2025-03-12","arxiv_id":"2503.09149","n_code_links":0,"syntology":null},{"paper":"/paper/minimal-time-series-transformer","slug":"minimal-time-series-transformer","title":"Minimal Time Series Transformer","date":"2025-03-12","arxiv_id":"2503.09791","n_code_links":1,"syntology":null},{"paper":"/paper/moc-mixtures-of-text-chunking-learners-for","slug":"moc-mixtures-of-text-chunking-learners-for","title":"MoC: Mixtures of Text Chunking Learners for Retrieval-Augmented Generation System","date":"2025-03-12","arxiv_id":"2503.09600","n_code_links":1,"syntology":null},{"paper":"/paper/motion-blender-gaussian-splatting-for-dynamic","slug":"motion-blender-gaussian-splatting-for-dynamic","title":"Motion Blender Gaussian Splatting for Dynamic Scene Reconstruction","date":"2025-03-12","arxiv_id":"2503.09040","n_code_links":1,"syntology":null},{"paper":"/paper/multimodal-language-modeling-for-high","slug":"multimodal-language-modeling-for-high","title":"Language-Enhanced Representation Learning for Single-Cell Transcriptomics","date":"2025-03-12","arxiv_id":"2503.09427","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":["syr-cn/scmmgpt"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["unlocated"]}}},{"paper":null,"slug":"n2c2-nearest-neighbor-enhanced-confidence","title":"N2C2: Nearest Neighbor Enhanced Confidence Calibration for Cross-Lingual In-Context Learning","date":"2025-03-12","arxiv_id":"2503.09218","n_code_links":0,"syntology":null},{"paper":null,"slug":"nami-efficient-image-generation-via","title":"NAMI: Efficient Image Generation via Progressive Rectified Flow Transformers","date":"2025-03-12","arxiv_id":"2503.09242","n_code_links":0,"syntology":null},{"paper":null,"slug":"neuro-informed-adaptive-learning-nial","title":"Neuro-Informed Adaptive Learning (NIAL) Algorithm: A Hybrid Deep Learning Approach for ECG Signal Classification","date":"2025-03-12","arxiv_id":"2503.20789","n_code_links":0,"syntology":null},{"paper":null,"slug":"object-aware-dino-oh-a-dino-enhancing-self","title":"Object-Aware DINO (Oh-A-Dino): Enhancing Self-Supervised Representations for Multi-Object Instance Retrieval","date":"2025-03-12","arxiv_id":"2503.09867","n_code_links":0,"syntology":null},{"paper":null,"slug":"other-vehicle-trajectories-are-also-needed-a","title":"Other Vehicle Trajectories Are Also Needed: A Driving World Model Unifies Ego-Other Vehicle Trajectories in Video Latant Space","date":"2025-03-12","arxiv_id":"2503.09215","n_code_links":0,"syntology":null},{"paper":null,"slug":"performance-modeling-for-correlation-based","title":"Performance Modeling for Correlation-based Neural Decoding of Auditory Attention to Speech","date":"2025-03-12","arxiv_id":"2503.09349","n_code_links":0,"syntology":null},{"paper":null,"slug":"pig-behavior-dataset-and-spatial-temporal","title":"Pig behavior dataset and Spatial-temporal perception and enhancement networks based on the attention mechanism for pig behavior recognition","date":"2025-03-12","arxiv_id":"2503.09378","n_code_links":0,"syntology":null},{"paper":null,"slug":"post-interactive-multimodal-trajectory","title":"Post-interactive Multimodal Trajectory Prediction for Autonomous Driving","date":"2025-03-12","arxiv_id":"2503.09366","n_code_links":0,"syntology":null},{"paper":null,"slug":"rethinking-prompt-based-debiasing-in-large","title":"Rethinking Prompt-based Debiasing in Large Language Models","date":"2025-03-12","arxiv_id":"2503.09219","n_code_links":0,"syntology":null},{"paper":"/paper/robust-multimodal-survival-prediction-with","slug":"robust-multimodal-survival-prediction-with","title":"Robust Multimodal Survival Prediction with the Latent Differentiation Conditional Variational AutoEncoder","date":"2025-03-12","arxiv_id":"2503.09496","n_code_links":1,"syntology":{"ran":6,"of":6,"n_ran_checked":4,"n_instrument":2,"unverified":0,"pointer_only":6,"phrase":"6 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["JJ-ZHOU-Code/RobustMultiModel"],"state":"official (archive's flag): 5 ran","n_ran":5,"n_constructed":4,"n_ran_no_instrument_failure":4,"n_unverified":0,"ran_from_kinds":["official","unlocated"]}}},{"paper":"/paper/scope-dti-semi-inductive-dataset-construction","slug":"scope-dti-semi-inductive-dataset-construction","title":"SCOPE-DTI: Semi-Inductive Dataset Construction and Framework Optimization for Practical Usability Enhancement in Deep Learning-Based Drug Target Interaction Prediction","date":"2025-03-12","arxiv_id":"2503.09251","n_code_links":1,"syntology":null},{"paper":null,"slug":"se-3-equivariant-robot-learning-and-control-a","title":"SE(3)-Equivariant Robot Learning and Control: A Tutorial Survey","date":"2025-03-12","arxiv_id":"2503.09829","n_code_links":0,"syntology":null},{"paper":"/paper/search-r1-training-llms-to-reason-and","slug":"search-r1-training-llms-to-reason-and","title":"Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning","date":"2025-03-12","arxiv_id":"2503.09516","n_code_links":3,"syntology":{"ran":2,"of":2,"n_ran_checked":0,"n_instrument":2,"unverified":0,"pointer_only":1,"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":["petergriffinjin/search-r1"],"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","unlocated"]}}},{"paper":"/paper/simlingo-vision-only-closed-loop-autonomous","slug":"simlingo-vision-only-closed-loop-autonomous","title":"SimLingo: Vision-Only Closed-Loop Autonomous Driving with Language-Action Alignment","date":"2025-03-12","arxiv_id":"2503.09594","n_code_links":1,"syntology":{"ran":11,"of":14,"n_ran_checked":8,"n_instrument":3,"unverified":3,"pointer_only":0,"phrase":"11 ran (of which 8 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 3 where Syntology's instrument failed) · 3 unverified","official":null}},{"paper":"/paper/swapanyone-consistent-and-realistic-video","slug":"swapanyone-consistent-and-realistic-video","title":"SwapAnyone: Consistent and Realistic Video Synthesis for Swapping Any Person into Any Video","date":"2025-03-12","arxiv_id":"2503.09154","n_code_links":1,"syntology":null},{"paper":null,"slug":"ta-v2a-textually-assisted-video-to-audio","title":"TA-V2A: Textually Assisted Video-to-Audio Generation","date":"2025-03-12","arxiv_id":"2503.10700","n_code_links":0,"syntology":null},{"paper":null,"slug":"tabnsa-native-sparse-attention-for-efficient","title":"TabNSA: Native Sparse Attention for Efficient Tabular Data Learning","date":"2025-03-12","arxiv_id":"2503.09850","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-graph-foundation-models-a","title":"Towards Graph Foundation Models: A Transferability Perspective","date":"2025-03-12","arxiv_id":"2503.09363","n_code_links":0,"syntology":null},{"paper":"/paper/towards-quantifying-long-range-interactions","slug":"towards-quantifying-long-range-interactions","title":"Towards Quantifying Long-Range Interactions in Graph Machine Learning: a Large Graph Dataset and a Measurement","date":"2025-03-12","arxiv_id":"2503.09008","n_code_links":1,"syntology":{"ran":3,"of":3,"n_ran_checked":1,"n_instrument":2,"unverified":0,"pointer_only":3,"phrase":"3 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; 2 where Syntology's instrument failed) · 0 unverified","official":{"repos":["leonresearch/city-networks"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"trace-real-time-multimodal-common-ground","title":"TRACE: Real-Time Multimodal Common Ground Tracking in Situated Collaborative Dialogues","date":"2025-03-12","arxiv_id":"2503.09511","n_code_links":0,"syntology":null},{"paper":null,"slug":"un-straightening-generative-ai-how-queer","title":"Un-Straightening Generative AI: How Queer Artists Surface and Challenge the Normativity of Generative AI Models","date":"2025-03-12","arxiv_id":"2503.09805","n_code_links":0,"syntology":null},{"paper":"/paper/unicombine-unified-multi-conditional","slug":"unicombine-unified-multi-conditional","title":"UniCombine: Unified Multi-Conditional Combination with Diffusion Transformer","date":"2025-03-12","arxiv_id":"2503.09277","n_code_links":0,"syntology":{"ran":1,"of":3,"n_ran_checked":0,"n_instrument":1,"unverified":2,"pointer_only":3,"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) · 2 unverified","official":null}},{"paper":null,"slug":"unified-locomotion-transformer-with","title":"Unified Locomotion Transformer with Simultaneous Sim-to-Real Transfer for Quadrupeds","date":"2025-03-12","arxiv_id":"2503.08997","n_code_links":0,"syntology":null},{"paper":null,"slug":"unveiling-hidden-pivotal-players-with-goalnet","title":"Unveiling Hidden Pivotal Players with GoalNet: A GNN-Based Soccer Player Evaluation System","date":"2025-03-12","arxiv_id":"2503.09737","n_code_links":0,"syntology":null},{"paper":null,"slug":"vaxguard-a-multi-generator-multi-type-and","title":"VaxGuard: A Multi-Generator, Multi-Type, and Multi-Role Dataset for Detecting LLM-Generated Vaccine Misinformation","date":"2025-03-12","arxiv_id":"2503.09103","n_code_links":0,"syntology":null},{"paper":null,"slug":"vi-lad-vision-language-attention-distillation","title":"Vi-LAD: Vision-Language Attention Distillation for Socially-Aware Robot Navigation in Dynamic Environments","date":"2025-03-12","arxiv_id":"2503.09820","n_code_links":0,"syntology":null},{"paper":null,"slug":"video-individual-counting-for-moving-drones","title":"Video Individual Counting for Moving Drones","date":"2025-03-12","arxiv_id":"2503.10701","n_code_links":0,"syntology":null},{"paper":"/paper/vlog-video-language-models-by-generative","slug":"vlog-video-language-models-by-generative","title":"VLog: Video-Language Models by Generative Retrieval of Narration Vocabulary","date":"2025-03-12","arxiv_id":"2503.09402","n_code_links":1,"syntology":{"ran":7,"of":10,"n_ran_checked":5,"n_instrument":2,"unverified":3,"pointer_only":10,"phrase":"7 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; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["showlab/vlog"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":5,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"who-are-you-behind-the-screen-implicit-mbti","title":"Who Are You Behind the Screen? Implicit MBTI and Gender Detection Using Artificial Intelligence","date":"2025-03-12","arxiv_id":"2503.09853","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-grey-box-text-attack-framework-using","title":"A Grey-box Text Attack Framework using Explainable AI","date":"2025-03-11","arxiv_id":"2503.08226","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-survey-on-knowledge-oriented-retrieval","title":"A Survey on Knowledge-Oriented Retrieval-Augmented Generation","date":"2025-03-11","arxiv_id":"2503.10677","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-theory-of-learning-with-autoregressive","title":"A Theory of Learning with Autoregressive Chain of Thought","date":"2025-03-11","arxiv_id":"2503.07932","n_code_links":0,"syntology":null},{"paper":"/paper/accelerate-3d-object-detection-models-via","slug":"accelerate-3d-object-detection-models-via","title":"Accelerate 3D Object Detection Models via Zero-Shot Attention Key Pruning","date":"2025-03-11","arxiv_id":"2503.08101","n_code_links":1,"syntology":{"ran":2,"of":2,"n_ran_checked":1,"n_instrument":1,"unverified":0,"pointer_only":0,"phrase":"2 ran (of which 0 constructed an object rather than computing a result; 1 with no instrument failure: 1 honoured, 0 violated, 0 with no contract checked; 1 where Syntology's instrument failed) · 0 unverified","official":{"repos":["iseri27/tg_gbc"],"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":"accurate-int8-training-through-dynamic-block","title":"Accurate INT8 Training Through Dynamic Block-Level Fallback","date":"2025-03-11","arxiv_id":"2503.08040","n_code_links":0,"syntology":null},{"paper":"/paper/ag-vpreid-a-challenging-large-scale-benchmark","slug":"ag-vpreid-a-challenging-large-scale-benchmark","title":"AG-VPReID: A Challenging Large-Scale Benchmark for Aerial-Ground Video-based Person Re-Identification","date":"2025-03-11","arxiv_id":"2503.08121","n_code_links":1,"syntology":null},{"paper":null,"slug":"attention-hijackers-detect-and-disentangle","title":"Attention Hijackers: Detect and Disentangle Attention Hijacking in LVLMs for Hallucination Mitigation","date":"2025-03-11","arxiv_id":"2503.08216","n_code_links":0,"syntology":null},{"paper":null,"slug":"attention-reallocation-towards-zero-cost-and","title":"Attention Reallocation: Towards Zero-cost and Controllable Hallucination Mitigation of MLLMs","date":"2025-03-11","arxiv_id":"2503.08342","n_code_links":0,"syntology":null},{"paper":"/paper/context-aware-biases-for-length-extrapolation","slug":"context-aware-biases-for-length-extrapolation","title":"Context-aware Biases for Length Extrapolation","date":"2025-03-11","arxiv_id":"2503.08067","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 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result","official":{"repos":["axiomlab/Cable"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["found_in_text"]}}},{"paper":"/paper/efficient-many-shot-in-context-learning-with","slug":"efficient-many-shot-in-context-learning-with","title":"Efficient Many-Shot In-Context Learning with Dynamic Block-Sparse Attention","date":"2025-03-11","arxiv_id":"2503.08640","n_code_links":1,"syntology":null},{"paper":null,"slug":"efpc-towards-efficient-and-flexible-prompt","title":"EFPC: Towards Efficient and Flexible Prompt Compression","date":"2025-03-11","arxiv_id":"2503.07956","n_code_links":0,"syntology":null},{"paper":null,"slug":"esnlir-a-spanish-multi-genre-dataset-with","title":"ESNLIR: A Spanish Multi-Genre Dataset with Causal Relationships","date":"2025-03-11","arxiv_id":"2503.08803","n_code_links":0,"syntology":null},{"paper":"/paper/external-knowledge-injection-for-clip-based","slug":"external-knowledge-injection-for-clip-based","title":"External Knowledge Injection for CLIP-Based Class-Incremental Learning","date":"2025-03-11","arxiv_id":"2503.08510","n_code_links":3,"syntology":null},{"paper":null,"slug":"from-slices-to-sequences-autoregressive","title":"From Slices to Sequences: Autoregressive Tracking Transformer for Cohesive and Consistent 3D Lymph Node Detection in CT Scans","date":"2025-03-11","arxiv_id":"2503.07933","n_code_links":0,"syntology":null},{"paper":null,"slug":"gpt-ppg-a-gpt-based-foundation-model-for","title":"GPT-PPG: A GPT-based Foundation Model for Photoplethysmography Signals","date":"2025-03-11","arxiv_id":"2503.08015","n_code_links":0,"syntology":null},{"paper":null,"slug":"gradient-guided-attention-map-editing-towards","title":"Gradient-guided Attention Map Editing: Towards Efficient Contextual Hallucination Mitigation","date":"2025-03-11","arxiv_id":"2503.08963","n_code_links":0,"syntology":null},{"paper":null,"slug":"guess-what-i-am-thinking-a-benchmark-for","title":"Guess What I am Thinking: A Benchmark for Inner Thought Reasoning of Role-Playing Language Agents","date":"2025-03-11","arxiv_id":"2503.08193","n_code_links":0,"syntology":null},{"paper":null,"slug":"hotformerloc-hierarchical-octree-transformer","title":"HOTFormerLoc: Hierarchical Octree Transformer for Versatile Lidar Place Recognition Across Ground and Aerial Views","date":"2025-03-11","arxiv_id":"2503.08140","n_code_links":0,"syntology":null},{"paper":null,"slug":"in-silico-clinical-trials-in-drug-development","title":"In silico clinical trials in drug development: a systematic review","date":"2025-03-11","arxiv_id":"2503.08746","n_code_links":0,"syntology":null},{"paper":null,"slug":"interpretable-and-robust-dialogue-state","title":"Interpretable and Robust Dialogue State Tracking via Natural Language Summarization with LLMs","date":"2025-03-11","arxiv_id":"2503.08857","n_code_links":0,"syntology":null},{"paper":"/paper/interpreting-the-repeated-token-phenomenon-in","slug":"interpreting-the-repeated-token-phenomenon-in","title":"Interpreting the Repeated Token Phenomenon in Large Language Models","date":"2025-03-11","arxiv_id":"2503.08908","n_code_links":1,"syntology":null},{"paper":null,"slug":"joint-image-instance-spatial-temporal","title":"Joint Image-Instance Spatial-Temporal Attention for Few-shot Action Recognition","date":"2025-03-11","arxiv_id":"2503.14430","n_code_links":0,"syntology":null},{"paper":null,"slug":"kan-mixers-a-new-deep-learning-architecture","title":"KAN-Mixers: a new deep learning architecture for image classification","date":"2025-03-11","arxiv_id":"2503.08939","n_code_links":0,"syntology":null},{"paper":null,"slug":"llm-based-corroborating-and-refuting-evidence","title":"LLM-based Corroborating and Refuting Evidence Retrieval for Scientific Claim Verification","date":"2025-03-11","arxiv_id":"2503.07937","n_code_links":0,"syntology":null},{"paper":null,"slug":"llms-know-what-to-drop-self-attention-guided","title":"LLMs Know What to Drop: Self-Attention Guided KV Cache Eviction for Efficient Long-Context Inference","date":"2025-03-11","arxiv_id":"2503.08879","n_code_links":0,"syntology":null},{"paper":null,"slug":"llms-virtual-users-and-bias-predicting-any","title":"Llms, Virtual Users, and Bias: Predicting Any Survey Question Without Human Data","date":"2025-03-11","arxiv_id":"2503.16498","n_code_links":0,"syntology":null},{"paper":null,"slug":"maskattn-unet-a-mask-attention-driven","title":"MaskAttn-UNet: A Mask Attention-Driven Framework for Universal Low-Resolution Image Segmentation","date":"2025-03-11","arxiv_id":"2503.10686","n_code_links":0,"syntology":null},{"paper":"/paper/meat-multiview-diffusion-model-for-human","slug":"meat-multiview-diffusion-model-for-human","title":"MEAT: Multiview Diffusion Model for Human Generation on Megapixels with Mesh Attention","date":"2025-03-11","arxiv_id":"2503.08664","n_code_links":1,"syntology":null},{"paper":null,"slug":"mfrs-a-multi-frequency-reference-series","title":"MFRS: A Multi-Frequency Reference Series Approach to Scalable and Accurate Time-Series Forecasting","date":"2025-03-11","arxiv_id":"2503.08328","n_code_links":0,"syntology":null},{"paper":null,"slug":"mvgsr-multi-view-consistency-gaussian","title":"MVGSR: Multi-View Consistency Gaussian Splatting for Robust Surface Reconstruction","date":"2025-03-11","arxiv_id":"2503.08093","n_code_links":0,"syntology":null},{"paper":null,"slug":"on-digital-optimization-of-analog-self","title":"On Digital Optimization of Analog Self-Interference Cancellation for Full-Duplex Wireless Systems","date":"2025-03-11","arxiv_id":"2503.08357","n_code_links":0,"syntology":null},{"paper":null,"slug":"openrag-optimizing-rag-end-to-end-via-in","title":"OpenRAG: Optimizing RAG End-to-End via In-Context Retrieval Learning","date":"2025-03-11","arxiv_id":"2503.08398","n_code_links":0,"syntology":null},{"paper":null,"slug":"overlap-aware-meta-learning-attention-to","title":"Overlap-aware meta-learning attention to enhance hypergraph neural networks for node classification","date":"2025-03-11","arxiv_id":"2503.07961","n_code_links":0,"syntology":null},{"paper":null,"slug":"promptgar-flexible-promptive-group-activity","title":"PromptGAR: Flexible Promptive Group Activity Recognition","date":"2025-03-11","arxiv_id":"2503.08933","n_code_links":0,"syntology":null},{"paper":null,"slug":"quiet-sr-quantum-image-enhancement","title":"QUIET-SR: Quantum Image Enhancement Transformer for Single Image Super-Resolution","date":"2025-03-11","arxiv_id":"2503.08759","n_code_links":0,"syntology":null},{"paper":"/paper/quota-query-oriented-token-assignment-via-cot","slug":"quota-query-oriented-token-assignment-via-cot","title":"QuoTA: Query-oriented Token Assignment via CoT Query Decouple for Long Video Comprehension","date":"2025-03-11","arxiv_id":"2503.08689","n_code_links":1,"syntology":{"ran":1,"of":1,"n_ran_checked":0,"n_instrument":1,"unverified":0,"pointer_only":1,"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":["mac-automl/quota"],"state":"official: no sample here; runs from other or unrecorded repositories","n_ran":0,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":0,"ran_from_kinds":["unlocated"]}}},{"paper":null,"slug":"recent-advances-in-hypergraph-neural-networks","title":"Recent Advances in Hypergraph Neural Networks","date":"2025-03-11","arxiv_id":"2503.07959","n_code_links":0,"syntology":null},{"paper":null,"slug":"seeing-what-s-not-there-spurious-correlation","title":"Seeing What's Not There: Spurious Correlation in Multimodal LLMs","date":"2025-03-11","arxiv_id":"2503.08884","n_code_links":0,"syntology":null},{"paper":null,"slug":"shedding-light-in-task-decomposition-in","title":"Shedding Light in Task Decomposition in Program Synthesis: The Driving Force of the Synthesizer Model","date":"2025-03-11","arxiv_id":"2503.08738","n_code_links":0,"syntology":null},{"paper":null,"slug":"simulating-automotive-radar-with-lidar-and","title":"Simulating Automotive Radar with Lidar and Camera Inputs","date":"2025-03-11","arxiv_id":"2503.08068","n_code_links":0,"syntology":null},{"paper":"/paper/stead-spatio-temporal-efficient-anomaly-1","slug":"stead-spatio-temporal-efficient-anomaly-1","title":"STEAD: Spatio-Temporal Efficient Anomaly Detection for Time and Compute Sensitive Applications","date":"2025-03-11","arxiv_id":"2503.07942","n_code_links":1,"syntology":null},{"paper":null,"slug":"stick-to-facts-towards-fidelity-oriented","title":"Stick to Facts: Towards Fidelity-oriented Product Description Generation","date":"2025-03-11","arxiv_id":"2503.08454","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-algorithmic-state-architecture-asa-an","title":"The Algorithmic State Architecture (ASA): An Integrated Framework for AI-Enabled Government","date":"2025-03-11","arxiv_id":"2503.08725","n_code_links":0,"syntology":null},{"paper":null,"slug":"transecg-leveraging-transformers-for","title":"TransECG: Leveraging Transformers for Explainable ECG Re-identification Risk Analysis","date":"2025-03-11","arxiv_id":"2503.13495","n_code_links":0,"syntology":null},{"paper":null,"slug":"vision-transformer-for-intracranial","title":"Vision Transformer for Intracranial Hemorrhage Classification in CT Scans Using an Entropy-Aware Fuzzy Integral Strategy for Adaptive Scan-Level Decision Fusion","date":"2025-03-11","arxiv_id":"2503.08609","n_code_links":0,"syntology":null},{"paper":null,"slug":"visual-attention-graph","title":"Visual Attention Graph","date":"2025-03-11","arxiv_id":"2503.08531","n_code_links":0,"syntology":null},{"paper":null,"slug":"wisa-world-simulator-assistant-for-physics","title":"WISA: World Simulator Assistant for Physics-Aware Text-to-Video Generation","date":"2025-03-11","arxiv_id":"2503.08153","n_code_links":0,"syntology":null},{"paper":"/paper/a-comprehensive-survey-of-mixture-of-experts","slug":"a-comprehensive-survey-of-mixture-of-experts","title":"A Comprehensive Survey of Mixture-of-Experts: Algorithms, Theory, and Applications","date":"2025-03-10","arxiv_id":"2503.07137","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":["deepseek-ai/DeepEP"],"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-data-centric-revisit-of-pre-trained-vision","slug":"a-data-centric-revisit-of-pre-trained-vision","title":"A Data-Centric Revisit of Pre-Trained Vision Models for Robot Learning","date":"2025-03-10","arxiv_id":"2503.06960","n_code_links":1,"syntology":{"ran":3,"of":4,"n_ran_checked":2,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"3 ran (of which 2 constructed an object rather than computing a result; 2 with no instrument failure: 0 honoured, 0 violated, 2 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":{"repos":["cvmi-lab/slotmim"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":2,"n_ran_no_instrument_failure":2,"n_unverified":1,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"a-longformer-based-framework-for-accurate-and","title":"A LongFormer-Based Framework for Accurate and Efficient Medical Text Summarization","date":"2025-03-10","arxiv_id":"2503.06888","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-lstm-transformer-model-for-pulsation","title":"A LSTM-Transformer Model for pulsation control of pVADs","date":"2025-03-10","arxiv_id":"2503.07110","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-recipe-for-improving-remote-sensing-vlm","title":"A Recipe for Improving Remote Sensing VLM Zero Shot Generalization","date":"2025-03-10","arxiv_id":"2503.08722","n_code_links":0,"syntology":null},{"paper":null,"slug":"attentionswarm-reinforcement-learning-with","title":"AttentionSwarm: Reinforcement Learning with Attention Control Barier Function for Crazyflie Drones in Dynamic Environments","date":"2025-03-10","arxiv_id":"2503.07376","n_code_links":0,"syntology":null},{"paper":null,"slug":"attfc-attention-fully-connected-layer-for","title":"AttFC: Attention Fully-Connected Layer for Large-Scale Face Recognition with One GPU","date":"2025-03-10","arxiv_id":"2503.06839","n_code_links":0,"syntology":null},{"paper":null,"slug":"bot-wars-evolved-orchestrating-competing-llms","title":"Bot Wars Evolved: Orchestrating Competing LLMs in a Counterstrike Against Phone Scams","date":"2025-03-10","arxiv_id":"2503.07036","n_code_links":0,"syntology":null},{"paper":null,"slug":"building-english-asr-model-with-regional","title":"Building English ASR model with regional language support","date":"2025-03-10","arxiv_id":"2503.07522","n_code_links":0,"syntology":null},{"paper":"/paper/catanet-efficient-content-aware-token","slug":"catanet-efficient-content-aware-token","title":"CATANet: Efficient Content-Aware Token Aggregation for Lightweight Image Super-Resolution","date":"2025-03-10","arxiv_id":"2503.06896","n_code_links":1,"syntology":null}],"record_sha256":"724a8a655ed2097e18270195252177d7290841c447ae25c8ccc5327202559414","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}