{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/method/attention/papers/38","list_of":"/method/attention","method":"Attention","archive":{"snapshot":"2025-07-28"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"date (newest first), then slug","page":38,"pages_in_order":316,"rows_per_page":100,"rows":[3701,3800],"of":31583,"counts":{"archive_papers_tagged":31583,"with_a_code_link":13473,"where_syntology_ran_a_sample":3998,"not_listed_spam_title":0,"listed":31583,"listed_where_code_ran":3998,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":3366,"every_run_a_failure_of_syntologys_instrument":632,"listed_with_a_run_with_no_instrument_failure":3366,"listed_every_run_a_failure_of_syntologys_instrument":632,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/method/attention","prev":"/method/attention/papers/37","next":"/method/attention/papers/39","papers":[{"paper":null,"slug":"enhanced-transformer-based-tracking-for","title":"Enhanced Transformer-Based Tracking for Skiing Events: Overcoming Multi-Camera Challenges, Scale Variations and Rapid Motion -- SkiTB Visual Tracking Challenge 2025","date":"2025-02-26","arxiv_id":"2502.18867","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluating-llms-and-pre-trained-models-for","title":"Evaluating LLMs and Pre-trained Models for Text Summarization Across Diverse Datasets","date":"2025-02-26","arxiv_id":"2502.19339","n_code_links":0,"syntology":null},{"paper":null,"slug":"fatigue-pinn-physics-informed-fatigue-driven","title":"Fatigue-PINN: Physics-Informed Fatigue-Driven Motion Modulation and Synthesis","date":"2025-02-26","arxiv_id":"2502.19056","n_code_links":0,"syntology":null},{"paper":"/paper/fintsb-a-comprehensive-and-practical","slug":"fintsb-a-comprehensive-and-practical","title":"FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting","date":"2025-02-26","arxiv_id":"2502.18834","n_code_links":1,"syntology":null},{"paper":null,"slug":"genotype-to-phenotype-prediction-in-rice-with","title":"Genotype-to-Phenotype Prediction in Rice with High-Dimensional Nonlinear Features","date":"2025-02-26","arxiv_id":"2502.18758","n_code_links":0,"syntology":null},{"paper":"/paper/integrate-the-temporal-scheme-for","slug":"integrate-the-temporal-scheme-for","title":"Integrate the temporal scheme for unsupervised video summarization via attention mechanism","date":"2025-02-26","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"integrating-biological-and-machine","title":"Integrating Biological and Machine Intelligence: Attention Mechanisms in Brain-Computer Interfaces","date":"2025-02-26","arxiv_id":"2502.19281","n_code_links":0,"syntology":null},{"paper":"/paper/introduction-to-sequence-modeling-with","slug":"introduction-to-sequence-modeling-with","title":"Introduction to Sequence Modeling with Transformers","date":"2025-02-26","arxiv_id":"2502.19597","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-to-align-multi-faceted-evaluation-a","title":"Learning to Align Multi-Faceted Evaluation: A Unified and Robust Framework","date":"2025-02-26","arxiv_id":"2502.18874","n_code_links":0,"syntology":null},{"paper":"/paper/max360iq-blind-omnidirectional-image-quality","slug":"max360iq-blind-omnidirectional-image-quality","title":"Max360IQ: Blind Omnidirectional Image Quality Assessment with Multi-axis Attention","date":"2025-02-26","arxiv_id":"2502.19046","n_code_links":1,"syntology":null},{"paper":null,"slug":"mebench-benchmarking-large-language-models","title":"MEBench: Benchmarking Large Language Models for Cross-Document Multi-Entity Question Answering","date":"2025-02-26","arxiv_id":"2502.18993","n_code_links":0,"syntology":null},{"paper":"/paper/multiview-graph-dual-attention-deep-learning","slug":"multiview-graph-dual-attention-deep-learning","title":"Multiview graph dual-attention deep learning and contrastive learning for multi-criteria recommender systems","date":"2025-02-26","arxiv_id":"2502.19271","n_code_links":1,"syntology":null},{"paper":"/paper/neobert-a-next-generation-bert","slug":"neobert-a-next-generation-bert","title":"NeoBERT: A Next-Generation BERT","date":"2025-02-26","arxiv_id":"2502.19587","n_code_links":1,"syntology":null},{"paper":null,"slug":"nonparametric-heterogeneous-long-term-causal","title":"Nonparametric Heterogeneous Long-term Causal Effect Estimation via Data Combination","date":"2025-02-26","arxiv_id":"2502.18960","n_code_links":0,"syntology":null},{"paper":null,"slug":"online-pseudo-average-shifting-attention-pasa","title":"Online Pseudo-average Shifting Attention(PASA) for Robust Low-precision LLM Inference: Algorithms and Numerical Analysis","date":"2025-02-26","arxiv_id":"2503.01873","n_code_links":0,"syntology":null},{"paper":null,"slug":"optimal-approximate-matrix-multiplication-1","title":"Optimal Approximate Matrix Multiplication over Sliding Windows","date":"2025-02-26","arxiv_id":"2502.18830","n_code_links":0,"syntology":null},{"paper":null,"slug":"pce-gan-a-generative-adversarial-network-for","title":"PCE-GAN: A Generative Adversarial Network for Point Cloud Attribute Quality Enhancement based on Optimal Transport","date":"2025-02-26","arxiv_id":"2503.00047","n_code_links":0,"syntology":null},{"paper":"/paper/poster-long-php-webshell-files-detection","slug":"poster-long-php-webshell-files-detection","title":"Poster: Long PHP webshell files detection based on sliding window attention","date":"2025-02-26","arxiv_id":"2502.19257","n_code_links":1,"syntology":null},{"paper":null,"slug":"proxytransformation-preshaping-point-cloud","title":"ProxyTransformation: Preshaping Point Cloud Manifold With Proxy Attention For 3D Visual Grounding","date":"2025-02-26","arxiv_id":"2502.19247","n_code_links":0,"syntology":null},{"paper":null,"slug":"reimagining-personal-data-unlocking-the","title":"Reimagining Personal Data: Unlocking the Potential of AI-Generated Images in Personal Data Meaning-Making","date":"2025-02-26","arxiv_id":"2502.18853","n_code_links":0,"syntology":null},{"paper":"/paper/se-3-equivariant-ternary-complex-prediction","slug":"se-3-equivariant-ternary-complex-prediction","title":"SE(3)-Equivariant Ternary Complex Prediction Towards Target Protein Degradation","date":"2025-02-26","arxiv_id":"2502.18875","n_code_links":1,"syntology":null},{"paper":null,"slug":"slam-in-the-dark-self-supervised-learning-of","title":"SLAM in the Dark: Self-Supervised Learning of Pose, Depth and Loop-Closure from Thermal Images","date":"2025-02-26","arxiv_id":"2502.18932","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-sharpness-disparity-principle-in","title":"The Sharpness Disparity Principle in Transformers for Accelerating Language Model Pre-Training","date":"2025-02-26","arxiv_id":"2502.19002","n_code_links":0,"syntology":null},{"paper":null,"slug":"triple-difference-designs-with-heterogeneous","title":"Triple Difference Designs with Heterogeneous Treatment Effects","date":"2025-02-26","arxiv_id":"2502.19620","n_code_links":0,"syntology":null},{"paper":null,"slug":"uncertainty-comes-for-free-human-in-the-loop","title":"Uncertainty Comes for Free: Human-in-the-Loop Policies with Diffusion Models","date":"2025-02-26","arxiv_id":"2503.01876","n_code_links":0,"syntology":null},{"paper":null,"slug":"weaker-llms-opinions-also-matter-mixture-of","title":"Weaker LLMs' Opinions Also Matter: Mixture of Opinions Enhances LLM's Mathematical Reasoning","date":"2025-02-26","arxiv_id":"2502.19622","n_code_links":0,"syntology":null},{"paper":null,"slug":"2503-00036","title":"A Novel Spatiotemporal Correlation Anomaly Detection Method Based on Time-Frequency-Domain Feature Fusion and a Dynamic Graph Neural Network in Wireless Sensor Network","date":"2025-02-25","arxiv_id":"2503.00036","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-fusion-model-for-art-style-and-author","title":"A Fusion Model for Art Style and Author Recognition Based on Convolutional Neural Networks and Transformers","date":"2025-02-25","arxiv_id":"2502.18083","n_code_links":0,"syntology":null},{"paper":null,"slug":"afroxlmr-comet-multilingual-knowledge","title":"AfroXLMR-Comet: Multilingual Knowledge Distillation with Attention Matching for Low-Resource languages","date":"2025-02-25","arxiv_id":"2502.18020","n_code_links":0,"syntology":null},{"paper":"/paper/an-ensemble-framework-for-probabilistic-short","slug":"an-ensemble-framework-for-probabilistic-short","title":"An Ensemble Framework for Probabilistic Short-Term Load Forecasting Based on BiTCN and Deep Attention Networks","date":"2025-02-25","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"application-of-attention-mechanism-with","title":"Application of Attention Mechanism with Bidirectional Long Short-Term Memory (BiLSTM) and CNN for Human Conflict Detection using Computer Vision","date":"2025-02-25","arxiv_id":"2502.18555","n_code_links":0,"syntology":null},{"paper":"/paper/art-anonymous-region-transformer-for-variable","slug":"art-anonymous-region-transformer-for-variable","title":"ART: Anonymous Region Transformer for Variable Multi-Layer Transparent Image Generation","date":"2025-02-25","arxiv_id":"2502.18364","n_code_links":1,"syntology":{"ran":13,"of":14,"n_ran_checked":12,"n_instrument":1,"unverified":1,"pointer_only":0,"phrase":"13 ran (of which 0 constructed an object rather than computing a result; 12 with no instrument failure: 0 honoured, 0 violated, 12 with no contract checked; 1 where Syntology's instrument failed) · 1 unverified","official":null}},{"paper":null,"slug":"assessing-large-language-models-in-agentic","title":"Assessing Large Language Models in Agentic Multilingual National Bias","date":"2025-02-25","arxiv_id":"2502.17945","n_code_links":0,"syntology":null},{"paper":null,"slug":"automatic-vehicle-detection-using-detr-a","title":"Automatic Vehicle Detection using DETR: A Transformer-Based Approach for Navigating Treacherous Roads","date":"2025-02-25","arxiv_id":"2502.17843","n_code_links":0,"syntology":null},{"paper":null,"slug":"bayesian-optimization-for-controlled-image","title":"Bayesian Optimization for Controlled Image Editing via LLMs","date":"2025-02-25","arxiv_id":"2502.18116","n_code_links":0,"syntology":null},{"paper":null,"slug":"broadening-discovery-through-structural","title":"Broadening Discovery through Structural Models: Multimodal Combination of Local and Structural Properties for Predicting Chemical Features","date":"2025-02-25","arxiv_id":"2502.17986","n_code_links":0,"syntology":null},{"paper":null,"slug":"certified-decisions","title":"Certified Decisions","date":"2025-02-25","arxiv_id":"2502.17830","n_code_links":0,"syntology":null},{"paper":null,"slug":"detecting-knowledge-boundary-of-vision-large","title":"Detecting Knowledge Boundary of Vision Large Language Models by Sampling-Based Inference","date":"2025-02-25","arxiv_id":"2502.18023","n_code_links":0,"syntology":null},{"paper":null,"slug":"dual-classification-head-self-training","title":"Dual Classification Head Self-training Network for Cross-scene Hyperspectral Image Classification","date":"2025-02-25","arxiv_id":"2502.17879","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-speech-quality-through-the","title":"Enhancing Speech Quality through the Integration of BGRU and Transformer Architectures","date":"2025-02-25","arxiv_id":"2502.17911","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-text-classification-with-a-novel","title":"Enhancing Text Classification with a Novel Multi-Agent Collaboration Framework Leveraging BERT","date":"2025-02-25","arxiv_id":"2502.18653","n_code_links":0,"syntology":null},{"paper":null,"slug":"examining-the-threat-landscape-foundation","title":"Examining the Threat Landscape: Foundation Models and Model Stealing","date":"2025-02-25","arxiv_id":"2502.18077","n_code_links":0,"syntology":null},{"paper":null,"slug":"faster-cheaper-better-multi-objective","title":"Faster, Cheaper, Better: Multi-Objective Hyperparameter Optimization for LLM and RAG Systems","date":"2025-02-25","arxiv_id":"2502.18635","n_code_links":0,"syntology":null},{"paper":"/paper/forest-frame-of-reference-evaluation-in","slug":"forest-frame-of-reference-evaluation-in","title":"FoREST: Frame of Reference Evaluation in Spatial Reasoning Tasks","date":"2025-02-25","arxiv_id":"2502.17775","n_code_links":1,"syntology":null},{"paper":"/paper/fwnet-eca-facilitating-window-attention-with","slug":"fwnet-eca-facilitating-window-attention-with","title":"FwNet-ECA: Facilitating Window Attention with Global Receptive Fields through Fourier Filtering Operations","date":"2025-02-25","arxiv_id":"2502.18094","n_code_links":1,"syntology":null},{"paper":null,"slug":"ghost-2-0-generative-high-fidelity-one-shot","title":"GHOST 2.0: generative high-fidelity one shot transfer of heads","date":"2025-02-25","arxiv_id":"2502.18417","n_code_links":0,"syntology":null},{"paper":null,"slug":"graph-inference-with-effective-resistance","title":"Graph Inference with Effective Resistance Queries","date":"2025-02-25","arxiv_id":"2502.18350","n_code_links":0,"syntology":null},{"paper":null,"slug":"h-fltn-a-privacy-preserving-hierarchical","title":"H-FLTN: A Privacy-Preserving Hierarchical Framework for Electric Vehicle Spatio-Temporal Charge Prediction","date":"2025-02-25","arxiv_id":"2502.18697","n_code_links":0,"syntology":null},{"paper":"/paper/harnessing-multiple-large-language-models-a","slug":"harnessing-multiple-large-language-models-a","title":"Harnessing Multiple Large Language Models: A Survey on LLM Ensemble","date":"2025-02-25","arxiv_id":"2502.18036","n_code_links":1,"syntology":null},{"paper":null,"slug":"how-vital-is-the-jurisprudential-relevance","title":"How Vital is the Jurisprudential Relevance: Law Article Intervened Legal Case Retrieval and Matching","date":"2025-02-25","arxiv_id":"2502.18292","n_code_links":0,"syntology":null},{"paper":null,"slug":"improved-yolov7x-based-defect-detection","title":"Improved YOLOv7x-Based Defect Detection Algorithm for Power Equipment","date":"2025-02-25","arxiv_id":"2502.17961","n_code_links":0,"syntology":null},{"paper":null,"slug":"independent-mobility-gpt-idm-gpt-a-self","title":"Independent Mobility GPT (IDM-GPT): A Self-Supervised Multi-Agent Large Language Model Framework for Customized Traffic Mobility Analysis Using Machine Learning Models","date":"2025-02-25","arxiv_id":"2502.18652","n_code_links":0,"syntology":null},{"paper":null,"slug":"invdriver-intra-instance-aware-vectorized","title":"InVDriver: Intra-Instance Aware Vectorized Query-Based Autonomous Driving Transformer","date":"2025-02-25","arxiv_id":"2502.17949","n_code_links":0,"syntology":null},{"paper":null,"slug":"k-lora-unlocking-training-free-fusion-of-any","title":"K-LoRA: Unlocking Training-Free Fusion of Any Subject and Style LoRAs","date":"2025-02-25","arxiv_id":"2502.18461","n_code_links":0,"syntology":null},{"paper":null,"slug":"lam-large-avatar-model-for-one-shot","title":"LAM: Large Avatar Model for One-shot Animatable Gaussian Head","date":"2025-02-25","arxiv_id":"2502.17796","n_code_links":0,"syntology":null},{"paper":null,"slug":"ldgen-enhancing-text-to-image-synthesis-via","title":"LDGen: Enhancing Text-to-Image Synthesis via Large Language Model-Driven Language Representation","date":"2025-02-25","arxiv_id":"2502.18302","n_code_links":0,"syntology":null},{"paper":"/paper/learning-structure-supporting-dependencies","slug":"learning-structure-supporting-dependencies","title":"Learning Structure-Supporting Dependencies via Keypoint Interactive Transformer for General Mammal Pose Estimation","date":"2025-02-25","arxiv_id":"2502.18214","n_code_links":1,"syntology":null},{"paper":"/paper/levelrag-enhancing-retrieval-augmented","slug":"levelrag-enhancing-retrieval-augmented","title":"LevelRAG: Enhancing Retrieval-Augmented Generation with Multi-hop Logic Planning over Rewriting Augmented Searchers","date":"2025-02-25","arxiv_id":"2502.18139","n_code_links":1,"syntology":null},{"paper":null,"slug":"mage-multi-head-attention-guided-embeddings","title":"MAGE: Multi-Head Attention Guided Embeddings for Low Resource Sentiment Classification","date":"2025-02-25","arxiv_id":"2502.17987","n_code_links":0,"syntology":null},{"paper":"/paper/mm-poisonrag-disrupting-multimodal-rag-with","slug":"mm-poisonrag-disrupting-multimodal-rag-with","title":"MM-PoisonRAG: Disrupting Multimodal RAG with Local and Global Poisoning Attacks","date":"2025-02-25","arxiv_id":"2502.17832","n_code_links":1,"syntology":null},{"paper":null,"slug":"mucos-efficient-drug-target-prediction","title":"MuCoS: Efficient Drug-Target Prediction through Multi-Context-Aware Sampling","date":"2025-02-25","arxiv_id":"2502.17784","n_code_links":0,"syntology":null},{"paper":"/paper/neural-network-graph-similarity-computation","slug":"neural-network-graph-similarity-computation","title":"Neural Network Graph Similarity Computation Based on Graph Fusion","date":"2025-02-25","arxiv_id":"2502.18291","n_code_links":1,"syntology":null},{"paper":null,"slug":"opus-a-workflow-intention-framework-for","title":"Opus: A Workflow Intention Framework for Complex Workflow Generation","date":"2025-02-25","arxiv_id":"2502.19532","n_code_links":0,"syntology":null},{"paper":null,"slug":"refutebench-2-0-agentic-benchmark-for-dynamic","title":"RefuteBench 2.0 -- Agentic Benchmark for Dynamic Evaluation of LLM Responses to Refutation Instruction","date":"2025-02-25","arxiv_id":"2502.18308","n_code_links":0,"syntology":null},{"paper":null,"slug":"say-less-mean-more-leveraging-pragmatics-in","title":"Say Less, Mean More: Leveraging Pragmatics in Retrieval-Augmented Generation","date":"2025-02-25","arxiv_id":"2502.17839","n_code_links":0,"syntology":null},{"paper":null,"slug":"scaling-llm-pre-training-with-vocabulary","title":"Scaling LLM Pre-training with Vocabulary Curriculum","date":"2025-02-25","arxiv_id":"2502.17910","n_code_links":0,"syntology":null},{"paper":null,"slug":"self-adjust-softmax","title":"Self-Adjust Softmax","date":"2025-02-25","arxiv_id":"2502.18277","n_code_links":0,"syntology":null},{"paper":null,"slug":"software-implemented-fault-diagnosis-of","title":"Software implemented fault diagnosis of natural gas pumping unit based on feedforward neural network","date":"2025-02-25","arxiv_id":"2502.18233","n_code_links":0,"syntology":null},{"paper":"/paper/spargeattn-accurate-sparse-attention","slug":"spargeattn-accurate-sparse-attention","title":"SpargeAttention: Accurate and Training-free Sparse Attention Accelerating Any Model Inference","date":"2025-02-25","arxiv_id":"2502.18137","n_code_links":1,"syntology":null},{"paper":null,"slug":"stackelberg-game-preference-optimization-for","title":"Stackelberg Game Preference Optimization for Data-Efficient Alignment of Language Models","date":"2025-02-25","arxiv_id":"2502.18099","n_code_links":0,"syntology":null},{"paper":null,"slug":"synthesizing-consistent-novel-views-via-3d","title":"Synthesizing Consistent Novel Views via 3D Epipolar Attention without Re-Training","date":"2025-02-25","arxiv_id":"2502.18219","n_code_links":0,"syntology":null},{"paper":null,"slug":"systems-and-algorithms-for-convolutional","title":"Systems and Algorithms for Convolutional Multi-Hybrid Language Models at Scale","date":"2025-02-25","arxiv_id":"2503.01868","n_code_links":0,"syntology":null},{"paper":"/paper/the-fft-strikes-back-an-efficient-alternative","slug":"the-fft-strikes-back-an-efficient-alternative","title":"SPECTRE: An FFT-Based Efficient Drop-In Replacement to Self-Attention for Long Contexts","date":"2025-02-25","arxiv_id":"2502.18394","n_code_links":2,"syntology":null},{"paper":"/paper/vesselsam-leveraging-sam-for-aortic-vessel","slug":"vesselsam-leveraging-sam-for-aortic-vessel","title":"VesselSAM: Leveraging SAM for Aortic Vessel Segmentation with AtrousLoRA","date":"2025-02-25","arxiv_id":"2502.18185","n_code_links":1,"syntology":null},{"paper":"/paper/vidorag-visual-document-retrieval-augmented","slug":"vidorag-visual-document-retrieval-augmented","title":"ViDoRAG: Visual Document Retrieval-Augmented Generation via Dynamic Iterative Reasoning Agents","date":"2025-02-25","arxiv_id":"2502.18017","n_code_links":1,"syntology":{"ran":1,"of":6,"n_ran_checked":0,"n_instrument":1,"unverified":5,"pointer_only":6,"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) · 5 unverified","official":{"repos":["Alibaba-NLP/ViDoRAG"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":0,"n_ran_no_instrument_failure":0,"n_unverified":5,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"a-concise-lyapunov-analysis-of-nesterov-s","title":"A Concise Lyapunov Analysis of Nesterov's Accelerated Gradient Method","date":"2025-02-24","arxiv_id":"2502.17373","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-novel-approach-to-navigate-the-taxonomic","title":"A novel approach to navigate the taxonomic hierarchy to address the Open-World Scenarios in Medicinal Plant Classification","date":"2025-02-24","arxiv_id":"2502.17289","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-transformer-in-transformer-network","title":"A Transformer-in-Transformer Network Utilizing Knowledge Distillation for Image Recognition","date":"2025-02-24","arxiv_id":"2502.16762","n_code_links":0,"syntology":null},{"paper":null,"slug":"actionable-help-in-crises-a-novel-dataset-and","title":"\"Actionable Help\" in Crises: A Novel Dataset and Resource-Efficient Models for Identifying Request and Offer Social Media Posts","date":"2025-02-24","arxiv_id":"2502.16839","n_code_links":0,"syntology":null},{"paper":"/paper/adversarial-training-for-defense-against","slug":"adversarial-training-for-defense-against","title":"Adversarial Training for Defense Against Label Poisoning Attacks","date":"2025-02-24","arxiv_id":"2502.17121","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":["melisilaydabal/floral"],"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/anytop-character-animation-diffusion-with-any","slug":"anytop-character-animation-diffusion-with-any","title":"AnyTop: Character Animation Diffusion with Any Topology","date":"2025-02-24","arxiv_id":"2502.17327","n_code_links":1,"syntology":null},{"paper":null,"slug":"applying-llms-to-active-learning-towards-cost","title":"Applying LLMs to Active Learning: Towards Cost-Efficient Cross-Task Text Classification without Manually Labeled Data","date":"2025-02-24","arxiv_id":"2502.16892","n_code_links":0,"syntology":null},{"paper":null,"slug":"are-large-language-models-good-data","title":"Are Large Language Models Good Data Preprocessors?","date":"2025-02-24","arxiv_id":"2502.16790","n_code_links":0,"syntology":null},{"paper":null,"slug":"atten-transformer-a-deep-learning-framework","title":"Atten-Transformer: A Deep Learning Framework for User App Usage Prediction","date":"2025-02-24","arxiv_id":"2502.16957","n_code_links":0,"syntology":null},{"paper":"/paper/benchmarking-retrieval-augmented-generation-1","slug":"benchmarking-retrieval-augmented-generation-1","title":"Benchmarking Retrieval-Augmented Generation in Multi-Modal Contexts","date":"2025-02-24","arxiv_id":"2502.17297","n_code_links":2,"syntology":null},{"paper":"/paper/calibrefine-deep-learning-based-online","slug":"calibrefine-deep-learning-based-online","title":"CalibRefine: Deep Learning-Based Online Automatic Targetless LiDAR-Camera Calibration with Iterative and Attention-Driven Post-Refinement","date":"2025-02-24","arxiv_id":"2502.17648","n_code_links":1,"syntology":null},{"paper":null,"slug":"child-vs-machine-language-learning-can-the","title":"Child vs. machine language learning: Can the logical structure of human language unleash LLMs?","date":"2025-02-24","arxiv_id":"2502.17304","n_code_links":0,"syntology":null},{"paper":"/paper/cipherprune-efficient-and-scalable-private","slug":"cipherprune-efficient-and-scalable-private","title":"CipherPrune: Efficient and Scalable Private Transformer Inference","date":"2025-02-24","arxiv_id":"2502.16782","n_code_links":1,"syntology":{"ran":3,"of":9,"n_ran_checked":3,"n_instrument":0,"unverified":6,"pointer_only":9,"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) · 6 unverified","official":{"repos":["ucf-lou-lab-pet/cipher-prune-inference"],"state":"official (archive's flag): 3 ran","n_ran":3,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":6,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"clep-gan-an-innovative-approach-to-subject","title":"CLEP-GAN: An Innovative Approach to Subject-Independent ECG Reconstruction from PPG Signals","date":"2025-02-24","arxiv_id":"2502.17536","n_code_links":0,"syntology":null},{"paper":null,"slug":"dbudgetkv-dynamic-budget-in-kv-cache","title":"DBudgetKV: Dynamic Budget in KV Cache Compression for Ensuring Optimal Performance","date":"2025-02-24","arxiv_id":"2502.16886","n_code_links":0,"syntology":null},{"paper":null,"slug":"dimitra-audio-driven-diffusion-model-for","title":"Dimitra: Audio-driven Diffusion model for Expressive Talking Head Generation","date":"2025-02-24","arxiv_id":"2502.17198","n_code_links":0,"syntology":null},{"paper":null,"slug":"disentangling-visual-transformers-patch-level","title":"Disentangling Visual Transformers: Patch-level Interpretability for Image Classification","date":"2025-02-24","arxiv_id":"2502.17196","n_code_links":0,"syntology":null},{"paper":null,"slug":"enact-heart-ensemble-based-assessment-using","title":"ENACT-Heart -- ENsemble-based Assessment Using CNN and Transformer on Heart Sounds","date":"2025-02-24","arxiv_id":"2502.16914","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-image-matting-in-real-world-scenes","title":"Enhancing Image Matting in Real-World Scenes with Mask-Guided Iterative Refinement","date":"2025-02-24","arxiv_id":"2502.17093","n_code_links":0,"syntology":null},{"paper":"/paper/erwin-a-tree-based-hierarchical-transformer","slug":"erwin-a-tree-based-hierarchical-transformer","title":"Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems","date":"2025-02-24","arxiv_id":"2502.17019","n_code_links":2,"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":["maxxxzdn/erwin"],"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":null,"slug":"evaluating-the-effect-of-retrieval","title":"Evaluating the Effect of Retrieval Augmentation on Social Biases","date":"2025-02-24","arxiv_id":"2502.17611","n_code_links":0,"syntology":null},{"paper":null,"slug":"functional-bayesian-additive-regression-trees","title":"Functional BART with Shape Priors: A Bayesian Tree Approach to Constrained Functional Regression","date":"2025-02-24","arxiv_id":"2502.16888","n_code_links":0,"syntology":null},{"paper":"/paper/gabor-enhanced-physics-informed-neural","slug":"gabor-enhanced-physics-informed-neural","title":"Gabor-Enhanced Physics-Informed Neural Networks for Fast Simulations of Acoustic Wavefields","date":"2025-02-24","arxiv_id":"2502.17134","n_code_links":1,"syntology":null},{"paper":null,"slug":"gaussianflowocc-sparse-and-weakly-supervised","title":"GaussianFlowOcc: Sparse and Weakly Supervised Occupancy Estimation using Gaussian Splatting and Temporal Flow","date":"2025-02-24","arxiv_id":"2502.17288","n_code_links":0,"syntology":null},{"paper":null,"slug":"guidedbench-equipping-jailbreak-evaluation","title":"GuidedBench: Equipping Jailbreak Evaluation with Guidelines","date":"2025-02-24","arxiv_id":"2502.16903","n_code_links":0,"syntology":null}],"record_sha256":"c2e79dff105e3257265939db6c33aba8cecf3f754739fdea5a031a1389ecd843","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}