{"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/bpe/papers/8","list_of":"/method/bpe","method":"BPE","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":8,"pages_in_order":190,"rows_per_page":100,"rows":[701,800],"of":18975,"counts":{"archive_papers_tagged":18975,"with_a_code_link":8675,"where_syntology_ran_a_sample":2895,"not_listed_spam_title":0,"listed":18975,"listed_where_code_ran":2895,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":2443,"every_run_a_failure_of_syntologys_instrument":452,"listed_with_a_run_with_no_instrument_failure":2443,"listed_every_run_a_failure_of_syntologys_instrument":452,"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/bpe","prev":"/method/bpe/papers/7","next":"/method/bpe/papers/9","papers":[{"paper":null,"slug":"the-distracting-effect-understanding","title":"The Distracting Effect: Understanding Irrelevant Passages in RAG","date":"2025-05-11","arxiv_id":"2505.06914","n_code_links":0,"syntology":null},{"paper":null,"slug":"boosting-neural-language-inference-via","title":"Boosting Neural Language Inference via Cascaded Interactive Reasoning","date":"2025-05-10","arxiv_id":"2505.06607","n_code_links":0,"syntology":null},{"paper":"/paper/macrag-compress-slice-and-scale-up-for-multi","slug":"macrag-compress-slice-and-scale-up-for-multi","title":"MacRAG: Compress, Slice, and Scale-up for Multi-Scale Adaptive Context RAG","date":"2025-05-10","arxiv_id":"2505.06569","n_code_links":1,"syntology":null},{"paper":"/paper/omgm-orchestrate-multiple-granularities-and","slug":"omgm-orchestrate-multiple-granularities-and","title":"OMGM: Orchestrate Multiple Granularities and Modalities for Efficient Multimodal Retrieval","date":"2025-05-10","arxiv_id":"2505.07879","n_code_links":0,"syntology":{"ran":4,"of":5,"n_ran_checked":4,"n_instrument":0,"unverified":1,"pointer_only":5,"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":null}},{"paper":"/paper/probing-in-context-learning-impact-of-task","slug":"probing-in-context-learning-impact-of-task","title":"Probing In-Context Learning: Impact of Task Complexity and Model Architecture on Generalization and Efficiency","date":"2025-05-10","arxiv_id":"2505.06475","n_code_links":1,"syntology":null},{"paper":null,"slug":"qos-efficient-serving-of-multiple-mixture-of","title":"QoS-Efficient Serving of Multiple Mixture-of-Expert LLMs Using Partial Runtime Reconfiguration","date":"2025-05-10","arxiv_id":"2505.06481","n_code_links":0,"syntology":null},{"paper":null,"slug":"refine-af-a-task-agnostic-framework-to-align","title":"REFINE-AF: A Task-Agnostic Framework to Align Language Models via Self-Generated Instructions using Reinforcement Learning from Automated Feedback","date":"2025-05-10","arxiv_id":"2505.06548","n_code_links":0,"syntology":null},{"paper":null,"slug":"underwater-object-detection-in-sonar-imagery","title":"Underwater object detection in sonar imagery with detection transformer and Zero-shot neural architecture search","date":"2025-05-10","arxiv_id":"2505.06694","n_code_links":0,"syntology":null},{"paper":null,"slug":"utilizing-llms-to-investigate-the-disputed","title":"Utilizing LLMs to Investigate the Disputed Role of Evidence in Electronic Cigarette Health Policy Formation in Australia and the UK","date":"2025-05-10","arxiv_id":"2505.06782","n_code_links":0,"syntology":null},{"paper":null,"slug":"xgen-small-technical-report","title":"xGen-small Technical Report","date":"2025-05-10","arxiv_id":"2505.06496","n_code_links":0,"syntology":null},{"paper":null,"slug":"accurate-and-efficient-multivariate-time","title":"Accurate and Efficient Multivariate Time Series Forecasting via Offline Clustering","date":"2025-05-09","arxiv_id":"2505.05738","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-empathic-gpt-based-chatbot-to-talk-about","title":"An empathic GPT-based chatbot to talk about mental disorders with Spanish teenagers","date":"2025-05-09","arxiv_id":"2505.05828","n_code_links":0,"syntology":null},{"paper":null,"slug":"camera-control-at-the-edge-with-language","title":"Camera Control at the Edge with Language Models for Scene Understanding","date":"2025-05-09","arxiv_id":"2505.06402","n_code_links":0,"syntology":null},{"paper":null,"slug":"cellverse-do-large-language-models-really","title":"CellVerse: Do Large Language Models Really Understand Cell Biology?","date":"2025-05-09","arxiv_id":"2505.07865","n_code_links":0,"syntology":null},{"paper":"/paper/dfen-dual-feature-equalization-network-for","slug":"dfen-dual-feature-equalization-network-for","title":"DFEN: Dual Feature Equalization Network for Medical Image Segmentation","date":"2025-05-09","arxiv_id":"2505.05913","n_code_links":1,"syntology":null},{"paper":null,"slug":"graph-laplacian-wavelet-transformer-via","title":"Graph Laplacian Wavelet Transformer via Learnable Spectral Decomposition","date":"2025-05-09","arxiv_id":"2505.07862","n_code_links":0,"syntology":null},{"paper":null,"slug":"healthy-llms-benchmarking-llm-knowledge-of-uk","title":"Healthy LLMs? Benchmarking LLM Knowledge of UK Government Public Health Information","date":"2025-05-09","arxiv_id":"2505.06046","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-agent-systems-for-robotic-autonomy-with","title":"Multi-Agent Systems for Robotic Autonomy with LLMs","date":"2025-05-09","arxiv_id":"2505.05762","n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-integrated-knowledge-transfer-to","slug":"multimodal-integrated-knowledge-transfer-to","title":"Multimodal Integrated Knowledge Transfer to Large Language Models through Preference Optimization with Biomedical Applications","date":"2025-05-09","arxiv_id":"2505.05736","n_code_links":1,"syntology":null},{"paper":null,"slug":"towards-robust-few-shot-text-classification","title":"Towards Robust Few-Shot Text Classification Using Transformer Architectures and Dual Loss Strategies","date":"2025-05-09","arxiv_id":"2505.06145","n_code_links":0,"syntology":null},{"paper":null,"slug":"turbo-icl-in-context-learning-based-turbo","title":"Turbo-ICL: In-Context Learning-Based Turbo Equalization","date":"2025-05-09","arxiv_id":"2505.06175","n_code_links":0,"syntology":null},{"paper":null,"slug":"unisymnet-a-unified-symbolic-network-guided","title":"UniSymNet: A Unified Symbolic Network Guided by Transformer","date":"2025-05-09","arxiv_id":"2505.06091","n_code_links":0,"syntology":null},{"paper":null,"slug":"what-is-next-for-llms-next-generation-ai","title":"What Is Next for LLMs? Next-Generation AI Computing Hardware Using Photonic Chips","date":"2025-05-09","arxiv_id":"2505.05794","n_code_links":0,"syntology":null},{"paper":null,"slug":"ai-approaches-to-qualitative-and-quantitative","title":"AI Approaches to Qualitative and Quantitative News Analytics on NATO Unity","date":"2025-05-08","arxiv_id":"2505.06313","n_code_links":0,"syntology":null},{"paper":"/paper/benchmarking-vision-language-action-models-in","slug":"benchmarking-vision-language-action-models-in","title":"Benchmarking Vision, Language, & Action Models in Procedurally Generated, Open Ended Action Environments","date":"2025-05-08","arxiv_id":"2505.05540","n_code_links":1,"syntology":null},{"paper":"/paper/cardioformer-advancing-ai-in-ecg-analysis","slug":"cardioformer-advancing-ai-in-ecg-analysis","title":"Cardioformer: Advancing AI in ECG Analysis with Multi-Granularity Patching and ResNet","date":"2025-05-08","arxiv_id":"2505.05538","n_code_links":1,"syntology":null},{"paper":null,"slug":"lost-in-ocr-translation-vision-based","title":"Lost in OCR Translation? Vision-Based Approaches to Robust Document Retrieval","date":"2025-05-08","arxiv_id":"2505.05666","n_code_links":0,"syntology":null},{"paper":null,"slug":"performance-evaluation-of-large-language-1","title":"Performance Evaluation of Large Language Models in Bangla Consumer Health Query Summarization","date":"2025-05-08","arxiv_id":"2505.05070","n_code_links":0,"syntology":null},{"paper":null,"slug":"pro2sam-mask-prompt-to-sam-with-grid-points","title":"Pro2SAM: Mask Prompt to SAM with Grid Points for Weakly Supervised Object Localization","date":"2025-05-08","arxiv_id":"2505.04905","n_code_links":0,"syntology":null},{"paper":null,"slug":"progressive-inertial-poser-progressive-real","title":"Progressive Inertial Poser: Progressive Real-Time Kinematic Chain Estimation for 3D Full-Body Pose from Three IMU Sensors","date":"2025-05-08","arxiv_id":"2505.05336","n_code_links":0,"syntology":null},{"paper":null,"slug":"qualbench-benchmarking-chinese-llms-with","title":"QualBench: Benchmarking Chinese LLMs with Localized Professional Qualifications for Vertical Domain Evaluation","date":"2025-05-08","arxiv_id":"2505.05225","n_code_links":0,"syntology":null},{"paper":"/paper/ssh-net-a-self-supervised-and-hybrid-network","slug":"ssh-net-a-self-supervised-and-hybrid-network","title":"SSH-Net: A Self-Supervised and Hybrid Network for Noisy Image Watermark Removal","date":"2025-05-08","arxiv_id":"2505.05088","n_code_links":1,"syntology":null},{"paper":null,"slug":"trading-under-uncertainty-a-distribution","title":"Trading Under Uncertainty: A Distribution-Based Strategy for Futures Markets Using FutureQuant Transformer","date":"2025-05-08","arxiv_id":"2505.05595","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-empirical-study-of-openai-api-discussions","title":"An Empirical Study of OpenAI API Discussions on Stack Overflow","date":"2025-05-07","arxiv_id":"2505.04084","n_code_links":0,"syntology":null},{"paper":null,"slug":"balancing-accuracy-calibration-and-efficiency","title":"Balancing Accuracy, Calibration, and Efficiency in Active Learning with Vision Transformers Under Label Noise","date":"2025-05-07","arxiv_id":"2505.04375","n_code_links":0,"syntology":null},{"paper":"/paper/benchmarking-llm-faithfulness-in-rag-with","slug":"benchmarking-llm-faithfulness-in-rag-with","title":"Benchmarking LLM Faithfulness in RAG with Evolving Leaderboards","date":"2025-05-07","arxiv_id":"2505.04847","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":["vectara/FaithJudge"],"state":"official (archive's flag): 1 ran","n_ran":1,"n_constructed":1,"n_ran_no_instrument_failure":1,"n_unverified":0,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"bringing-legal-knowledge-to-the-public-by","title":"Bringing legal knowledge to the public by constructing a legal question bank using large-scale pre-trained language model","date":"2025-05-07","arxiv_id":"2505.04132","n_code_links":0,"syntology":null},{"paper":null,"slug":"dota-deformable-optimized-transformer","title":"DOTA: Deformable Optimized Transformer Architecture for End-to-End Text Recognition with Retrieval-Augmented Generation","date":"2025-05-07","arxiv_id":"2505.04175","n_code_links":0,"syntology":null},{"paper":null,"slug":"fine-tuning-large-language-models-and","title":"Fine-Tuning Large Language Models and Evaluating Retrieval Methods for Improved Question Answering on Building Codes","date":"2025-05-07","arxiv_id":"2505.04666","n_code_links":0,"syntology":null},{"paper":"/paper/gascade-grouped-summarization-of-adverse-drug","slug":"gascade-grouped-summarization-of-adverse-drug","title":"GASCADE: Grouped Summarization of Adverse Drug Event for Enhanced Cancer Pharmacovigilance","date":"2025-05-07","arxiv_id":"2505.04284","n_code_links":1,"syntology":null},{"paper":"/paper/hdifftg-a-lightweight-hybrid-diffusion","slug":"hdifftg-a-lightweight-hybrid-diffusion","title":"HDiffTG: A Lightweight Hybrid Diffusion-Transformer-GCN Architecture for 3D Human Pose Estimation","date":"2025-05-07","arxiv_id":"2505.04276","n_code_links":1,"syntology":null},{"paper":null,"slug":"hiperrag-high-performance-retrieval-augmented","title":"HiPerRAG: High-Performance Retrieval Augmented Generation for Scientific Insights","date":"2025-05-07","arxiv_id":"2505.04846","n_code_links":0,"syntology":null},{"paper":"/paper/image-restoration-via-multi-domain-learning","slug":"image-restoration-via-multi-domain-learning","title":"Image Restoration via Multi-domain Learning","date":"2025-05-07","arxiv_id":"2505.05504","n_code_links":1,"syntology":null},{"paper":null,"slug":"lay-your-scene-natural-scene-layout","title":"Lay-Your-Scene: Natural Scene Layout Generation with Diffusion Transformers","date":"2025-05-07","arxiv_id":"2505.04718","n_code_links":0,"syntology":null},{"paper":"/paper/llm-e-guess-can-llms-capabilities-advance","slug":"llm-e-guess-can-llms-capabilities-advance","title":"LLM-e Guess: Can LLMs Capabilities Advance Without Hardware Progress?","date":"2025-05-07","arxiv_id":"2505.04075","n_code_links":1,"syntology":null},{"paper":null,"slug":"m2rec-multi-scale-mamba-for-efficient","title":"M2Rec: Multi-scale Mamba for Efficient Sequential Recommendation","date":"2025-05-07","arxiv_id":"2505.04445","n_code_links":0,"syntology":null},{"paper":null,"slug":"orbit-2-scaling-exascale-vision-foundation","title":"ORBIT-2: Scaling Exascale Vision Foundation Models for Weather and Climate Downscaling","date":"2025-05-07","arxiv_id":"2505.04802","n_code_links":0,"syntology":null},{"paper":null,"slug":"osiris-a-lightweight-open-source","title":"Osiris: A Lightweight Open-Source Hallucination Detection System","date":"2025-05-07","arxiv_id":"2505.04844","n_code_links":0,"syntology":null},{"paper":null,"slug":"personalized-risks-and-regulatory-strategies","title":"Personalized Risks and Regulatory Strategies of Large Language Models in Digital Advertising","date":"2025-05-07","arxiv_id":"2505.04665","n_code_links":0,"syntology":null},{"paper":null,"slug":"pose-estimation-for-intra-cardiac","title":"Pose Estimation for Intra-cardiac Echocardiography Catheter via AI-Based Anatomical Understanding","date":"2025-05-07","arxiv_id":"2505.07851","n_code_links":0,"syntology":null},{"paper":null,"slug":"red-teaming-the-mind-of-the-machine-a","title":"Red Teaming the Mind of the Machine: A Systematic Evaluation of Prompt Injection and Jailbreak Vulnerabilities in LLMs","date":"2025-05-07","arxiv_id":"2505.04806","n_code_links":0,"syntology":null},{"paper":null,"slug":"retrieval-augmented-generation-evaluation-for","title":"Retrieval Augmented Generation Evaluation for Health Documents","date":"2025-05-07","arxiv_id":"2505.04680","n_code_links":0,"syntology":null},{"paper":null,"slug":"swinlip-an-efficient-visual-speech-encoder","title":"SwinLip: An Efficient Visual Speech Encoder for Lip Reading Using Swin Transformer","date":"2025-05-07","arxiv_id":"2505.04394","n_code_links":0,"syntology":null},{"paper":null,"slug":"theoretical-guarantees-for-lt-ttd-a-unified","title":"Theoretical Guarantees for LT-TTD: A Unified Transformer-based Architecture for Two-Level Ranking Systems","date":"2025-05-07","arxiv_id":"2505.04434","n_code_links":0,"syntology":null},{"paper":null,"slug":"towards-effectively-leveraging-execution","title":"Towards Effectively Leveraging Execution Traces for Program Repair with Code LLMs","date":"2025-05-07","arxiv_id":"2505.04441","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-comparative-analysis-of-ethical-and-safety","title":"A Comparative Analysis of Ethical and Safety Gaps in LLMs using Relative Danger Coefficient","date":"2025-05-06","arxiv_id":"2505.04654","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-reasoning-focused-legal-retrieval-benchmark","title":"A Reasoning-Focused Legal Retrieval Benchmark","date":"2025-05-06","arxiv_id":"2505.03970","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-review-of-dna-restriction-free-overlapping","title":"A review of DNA restriction-free overlapping sequence cloning techniques for synthetic biology","date":"2025-05-06","arxiv_id":"2505.03681","n_code_links":0,"syntology":null},{"paper":null,"slug":"an-analysis-of-hyper-parameter-optimization","title":"An Analysis of Hyper-Parameter Optimization Methods for Retrieval Augmented Generation","date":"2025-05-06","arxiv_id":"2505.03452","n_code_links":0,"syntology":null},{"paper":null,"slug":"evaluation-of-llms-on-long-tail-entity","title":"Evaluation of LLMs on Long-tail Entity Linking in Historical Documents","date":"2025-05-06","arxiv_id":"2505.03473","n_code_links":0,"syntology":null},{"paper":null,"slug":"image-recognition-with-online-lightweight","title":"Image Recognition with Online Lightweight Vision Transformer: A Survey","date":"2025-05-06","arxiv_id":"2505.03113","n_code_links":0,"syntology":null},{"paper":"/paper/mergeguard-efficient-thwarting-of-trojan","slug":"mergeguard-efficient-thwarting-of-trojan","title":"MergeGuard: Efficient Thwarting of Trojan Attacks in Machine Learning Models","date":"2025-05-06","arxiv_id":"2505.04015","n_code_links":1,"syntology":null},{"paper":null,"slug":"physics-inspired-energy-transition-neural","title":"Physics-inspired Energy Transition Neural Network for Sequence Learning","date":"2025-05-06","arxiv_id":"2505.03281","n_code_links":0,"syntology":null},{"paper":"/paper/rethinking-boundary-detection-in-deep-1","slug":"rethinking-boundary-detection-in-deep-1","title":"Rethinking Boundary Detection in Deep Learning-Based Medical Image Segmentation","date":"2025-05-06","arxiv_id":"2505.04652","n_code_links":1,"syntology":null},{"paper":null,"slug":"transformers-for-learning-on-noisy-and-task","title":"Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights","date":"2025-05-06","arxiv_id":"2505.03205","n_code_links":0,"syntology":null},{"paper":"/paper/direct-retrieval-augmented-optimization","slug":"direct-retrieval-augmented-optimization","title":"Direct Retrieval-augmented Optimization: Synergizing Knowledge Selection and Language Models","date":"2025-05-05","arxiv_id":"2505.03075","n_code_links":1,"syntology":null},{"paper":"/paper/knowing-you-don-t-know-learning-when-to","slug":"knowing-you-don-t-know-learning-when-to","title":"Knowing You Don't Know: Learning When to Continue Search in Multi-round RAG through Self-Practicing","date":"2025-05-05","arxiv_id":"2505.02811","n_code_links":1,"syntology":null},{"paper":null,"slug":"large-language-model-partitioning-for-low","title":"Large Language Model Partitioning for Low-Latency Inference at the Edge","date":"2025-05-05","arxiv_id":"2505.02533","n_code_links":0,"syntology":null},{"paper":null,"slug":"llm4fts-enhancing-large-language-models-for","title":"LLM4FTS: Enhancing Large Language Models for Financial Time Series Prediction","date":"2025-05-05","arxiv_id":"2505.02880","n_code_links":0,"syntology":null},{"paper":"/paper/low-loss-space-in-neural-networks-is","slug":"low-loss-space-in-neural-networks-is","title":"Low-Loss Space in Neural Networks is Continuous and Fully Connected","date":"2025-05-05","arxiv_id":"2505.02604","n_code_links":0,"syntology":{"ran":9,"of":13,"n_ran_checked":9,"n_instrument":0,"unverified":4,"pointer_only":0,"phrase":"9 ran (of which 0 constructed an object rather than computing a result; 9 with no instrument failure: 0 honoured, 0 violated, 9 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":null}},{"paper":null,"slug":"memorization-or-interpolation-detecting-llm","title":"Memorization or Interpolation ? Detecting LLM Memorization through Input Perturbation Analysis","date":"2025-05-05","arxiv_id":"2505.03019","n_code_links":0,"syntology":null},{"paper":null,"slug":"rapid-yet-accurate-tile-circuit-and-device","title":"Rapid yet accurate Tile-circuit and device modeling for Analog In-Memory Computing","date":"2025-05-05","arxiv_id":"2506.00004","n_code_links":0,"syntology":null},{"paper":"/paper/scformer-structured-channel-wise-transformer","slug":"scformer-structured-channel-wise-transformer","title":"SCFormer: Structured Channel-wise Transformer with Cumulative Historical State for Multivariate Time Series Forecasting","date":"2025-05-05","arxiv_id":"2505.02655","n_code_links":1,"syntology":null},{"paper":null,"slug":"symbioticrag-enhancing-document-intelligence","title":"SymbioticRAG: Enhancing Document Intelligence Through Human-LLM Symbiotic Collaboration","date":"2025-05-05","arxiv_id":"2505.02418","n_code_links":0,"syntology":null},{"paper":"/paper/t2s-high-resolution-time-series-generation","slug":"t2s-high-resolution-time-series-generation","title":"T2S: High-resolution Time Series Generation with Text-to-Series Diffusion Models","date":"2025-05-05","arxiv_id":"2505.02417","n_code_links":1,"syntology":null},{"paper":"/paper/voila-voice-language-foundation-models-for","slug":"voila-voice-language-foundation-models-for","title":"Voila: Voice-Language Foundation Models for Real-Time Autonomous Interaction and Voice Role-Play","date":"2025-05-05","arxiv_id":"2505.02707","n_code_links":1,"syntology":{"ran":7,"of":11,"n_ran_checked":7,"n_instrument":0,"unverified":4,"pointer_only":0,"phrase":"7 ran (of which 6 constructed an object rather than computing a result; 7 with no instrument failure: 1 honoured, 0 violated, 6 with no contract checked; 0 where Syntology's instrument failed) · 4 unverified","official":{"repos":["maitrix-org/voila"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":6,"n_ran_no_instrument_failure":7,"n_unverified":4,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"a-new-hope-domain-agnostic-automatic","title":"A New HOPE: Domain-agnostic Automatic Evaluation of Text Chunking","date":"2025-05-04","arxiv_id":"2505.02171","n_code_links":0,"syntology":null},{"paper":"/paper/casa-cnn-autoencoder-based-score-attention","slug":"casa-cnn-autoencoder-based-score-attention","title":"CASA: CNN Autoencoder-based Score Attention for Efficient Multivariate Long-term Time-series Forecasting","date":"2025-05-04","arxiv_id":"2505.02011","n_code_links":1,"syntology":null},{"paper":null,"slug":"dualreal-adaptive-joint-training-for-lossless","title":"DualReal: Adaptive Joint Training for Lossless Identity-Motion Fusion in Video Customization","date":"2025-05-04","arxiv_id":"2505.02192","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-local-causal-world-models-with-state","title":"Learning Local Causal World Models with State Space Models and Attention","date":"2025-05-04","arxiv_id":"2505.02074","n_code_links":0,"syntology":null},{"paper":"/paper/llm-optira-llm-driven-optimization-of","slug":"llm-optira-llm-driven-optimization-of","title":"LLM-OptiRA: LLM-Driven Optimization of Resource Allocation for Non-Convex Problems in Wireless Communications","date":"2025-05-04","arxiv_id":"2505.02091","n_code_links":1,"syntology":null},{"paper":null,"slug":"local-herb-identification-using-transfer","title":"Local Herb Identification Using Transfer Learning: A CNN-Powered Mobile Application for Nepalese Flora","date":"2025-05-04","arxiv_id":"2505.02147","n_code_links":0,"syntology":null},{"paper":null,"slug":"real-time-spatial-retrieval-augmented","title":"Real-time Spatial Retrieval Augmented Generation for Urban Environments","date":"2025-05-04","arxiv_id":"2505.02271","n_code_links":0,"syntology":null},{"paper":null,"slug":"seval-ex-a-statement-level-framework-for","title":"SEval-Ex: A Statement-Level Framework for Explainable Summarization Evaluation","date":"2025-05-04","arxiv_id":"2505.02235","n_code_links":0,"syntology":null},{"paper":null,"slug":"securing-5g-and-beyond-enabled-uav-networks","title":"Securing 5G and Beyond-Enabled UAV Networks: Resilience Through Multiagent Learning and Transformers Detection","date":"2025-05-03","arxiv_id":"2505.01885","n_code_links":0,"syntology":null},{"paper":null,"slug":"semantic-intelligence-integrating-gpt-4-with","title":"Semantic Intelligence: Integrating GPT-4 with A Planning in Low-Cost Robotics","date":"2025-05-03","arxiv_id":"2505.01931","n_code_links":0,"syntology":null},{"paper":null,"slug":"toward-onboard-ai-enabled-solutions-to-space","title":"Toward Onboard AI-Enabled Solutions to Space Object Detection for Space Sustainability","date":"2025-05-03","arxiv_id":"2505.01650","n_code_links":0,"syntology":null},{"paper":"/paper/3d-human-pose-estimation-via-spatial-graph","slug":"3d-human-pose-estimation-via-spatial-graph","title":"3D Human Pose Estimation via Spatial Graph Order Attention and Temporal Body Aware Transformer","date":"2025-05-02","arxiv_id":"2505.01003","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-character-based-diffusion-embedding","title":"A Character-based Diffusion Embedding Algorithm for Enhancing the Generation Quality of Generative Linguistic Steganographic Texts","date":"2025-05-02","arxiv_id":"2505.00977","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-domain-adaptation-of-large-language-models","title":"A Domain Adaptation of Large Language Models for Classifying Mechanical Assembly Components","date":"2025-05-02","arxiv_id":"2505.01627","n_code_links":0,"syntology":null},{"paper":null,"slug":"a-self-supervised-transformer-for-unusable","title":"A Self-Supervised Transformer for Unusable Shared Bike Detection","date":"2025-05-02","arxiv_id":"2505.00932","n_code_links":0,"syntology":null},{"paper":"/paper/a-transformer-based-neural-architecture","slug":"a-transformer-based-neural-architecture","title":"A Transformer-based Neural Architecture Search Method","date":"2025-05-02","arxiv_id":"2505.01314","n_code_links":1,"syntology":null},{"paper":null,"slug":"asset-pricing-in-pre-trained-transformer","title":"Asset Pricing in Pre-trained Transformer","date":"2025-05-02","arxiv_id":"2505.01575","n_code_links":0,"syntology":null},{"paper":null,"slug":"chorus-zero-shot-hierarchical-retrieval-and","title":"CHORUS: Zero-shot Hierarchical Retrieval and Orchestration for Generating Linear Programming Code","date":"2025-05-02","arxiv_id":"2505.01485","n_code_links":0,"syntology":null},{"paper":null,"slug":"compact-recurrent-transformer-with-persistent","title":"Compact Recurrent Transformer with Persistent Memory","date":"2025-05-02","arxiv_id":"2505.00929","n_code_links":0,"syntology":null},{"paper":null,"slug":"enhancing-sparql-query-rewriting-for-complex","title":"Enhancing SPARQL Query Rewriting for Complex Ontology Alignments","date":"2025-05-02","arxiv_id":"2505.01309","n_code_links":0,"syntology":null},{"paper":null,"slug":"falconwing-an-open-source-platform-for-ultra","title":"FalconWing: An Open-Source Platform for Ultra-Light Fixed-Wing Aircraft Research","date":"2025-05-02","arxiv_id":"2505.01383","n_code_links":0,"syntology":null},{"paper":null,"slug":"frect-frequency-augmented-convolutional","title":"FreCT: Frequency-augmented Convolutional Transformer for Robust Time Series Anomaly Detection","date":"2025-05-02","arxiv_id":"2505.00941","n_code_links":0,"syntology":null},{"paper":null,"slug":"good-news-for-script-kiddies-evaluating-large","title":"Good News for Script Kiddies? Evaluating Large Language Models for Automated Exploit Generation","date":"2025-05-02","arxiv_id":"2505.01065","n_code_links":0,"syntology":null},{"paper":"/paper/multimodal-transformers-are-hierarchical","slug":"multimodal-transformers-are-hierarchical","title":"Multimodal Transformers are Hierarchical Modal-wise Heterogeneous Graphs","date":"2025-05-02","arxiv_id":"2505.01068","n_code_links":0,"syntology":{"ran":0,"of":2,"n_ran_checked":0,"n_instrument":0,"unverified":2,"pointer_only":0,"phrase":"0 ran · 2 unverified","official":null}}],"record_sha256":"23e42fa278c62fc371af71f1d6141bbb4103de72ee3b4c56e63b847abdc5ca25","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}