{"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/base/papers/4","list_of":"/method/base","method":"BASE","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":4,"pages_in_order":58,"rows_per_page":100,"rows":[301,400],"of":5784,"counts":{"archive_papers_tagged":5784,"with_a_code_link":1913,"where_syntology_ran_a_sample":621,"not_listed_spam_title":0,"listed":5784,"listed_where_code_ran":621,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":523,"every_run_a_failure_of_syntologys_instrument":98,"listed_with_a_run_with_no_instrument_failure":523,"listed_every_run_a_failure_of_syntologys_instrument":98,"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/base","prev":"/method/base/papers/3","next":"/method/base/papers/5","papers":[{"paper":null,"slug":"simplicity-is-key-an-unsupervised-pretraining","title":"Simplicity is Key: An Unsupervised Pretraining Approach for Sparse Radio Channels","date":"2025-05-19","arxiv_id":"2505.13055","n_code_links":0,"syntology":null},{"paper":null,"slug":"unlocking-the-potential-of-difficulty-prior","title":"Unlocking the Potential of Difficulty Prior in RL-based Multimodal Reasoning","date":"2025-05-19","arxiv_id":"2505.13261","n_code_links":0,"syntology":null},{"paper":"/paper/warm-up-before-you-train-unlocking-general","slug":"warm-up-before-you-train-unlocking-general","title":"Warm Up Before You Train: Unlocking General Reasoning in Resource-Constrained Settings","date":"2025-05-19","arxiv_id":"2505.13718","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-universal-policy-wrapper-with-guarantees","title":"A universal policy wrapper with guarantees","date":"2025-05-18","arxiv_id":"2505.12354","n_code_links":0,"syntology":null},{"paper":null,"slug":"abflownet-optimizing-antibody-antigen-binding","title":"AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusion","date":"2025-05-18","arxiv_id":"2505.12358","n_code_links":0,"syntology":null},{"paper":null,"slug":"curriculum-abductive-learning","title":"Curriculum Abductive Learning","date":"2025-05-18","arxiv_id":"2505.12275","n_code_links":0,"syntology":null},{"paper":"/paper/psc-extending-context-window-of-large","slug":"psc-extending-context-window-of-large","title":"PSC: Extending Context Window of Large Language Models via Phase Shift Calibration","date":"2025-05-18","arxiv_id":"2505.12423","n_code_links":1,"syntology":null},{"paper":"/paper/synthetic-data-rl-task-definition-is-all-you","slug":"synthetic-data-rl-task-definition-is-all-you","title":"Synthetic Data RL: Task Definition Is All You Need","date":"2025-05-18","arxiv_id":"2505.17063","n_code_links":1,"syntology":{"ran":10,"of":13,"n_ran_checked":8,"n_instrument":2,"unverified":3,"pointer_only":0,"phrase":"10 ran (of which 0 constructed an object rather than computing a result; 8 with no instrument failure: 0 honoured, 0 violated, 8 with no contract checked; 2 where Syntology's instrument failed) · 3 unverified","official":{"repos":["gydpku/data_synthesis_rl"],"state":"official (archive's flag): 10 ran","n_ran":10,"n_constructed":0,"n_ran_no_instrument_failure":8,"n_unverified":3,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"table-r1-region-based-reinforcement-learning","title":"Table-R1: Region-based Reinforcement Learning for Table Understanding","date":"2025-05-18","arxiv_id":"2505.12415","n_code_links":0,"syntology":null},{"paper":null,"slug":"cot-vid-dynamic-chain-of-thought-routing-with","title":"CoT-Vid: Dynamic Chain-of-Thought Routing with Self Verification for Training-Free Video Reasoning","date":"2025-05-17","arxiv_id":"2505.11830","n_code_links":0,"syntology":null},{"paper":null,"slug":"mol-for-llms-dual-loss-optimization-to","title":"MoL for LLMs: Dual-Loss Optimization to Enhance Domain Expertise While Preserving General Capabilities","date":"2025-05-17","arxiv_id":"2505.12043","n_code_links":0,"syntology":null},{"paper":null,"slug":"2505-10775","title":"A Systematic Analysis of Base Model Choice for Reward Modeling","date":"2025-05-16","arxiv_id":"2505.10775","n_code_links":0,"syntology":null},{"paper":null,"slug":"2505-10781","title":"Completely Weakly Supervised Class-Incremental Learning for Semantic Segmentation","date":"2025-05-16","arxiv_id":"2505.10781","n_code_links":0,"syntology":null},{"paper":"/paper/2505-10833","slug":"2505-10833","title":"MergeBench: A Benchmark for Merging Domain-Specialized LLMs","date":"2025-05-16","arxiv_id":"2505.10833","n_code_links":1,"syntology":null},{"paper":"/paper/2505-11080","slug":"2505-11080","title":"BLEUBERI: BLEU is a surprisingly effective reward for instruction following","date":"2025-05-16","arxiv_id":"2505.11080","n_code_links":1,"syntology":null},{"paper":null,"slug":"2505-11132","title":"Fairness-aware Anomaly Detection via Fair Projection","date":"2025-05-16","arxiv_id":"2505.11132","n_code_links":0,"syntology":null},{"paper":null,"slug":"2505-11344","title":"Dynamic Base model Shift for Delta Compression","date":"2025-05-16","arxiv_id":"2505.11344","n_code_links":0,"syntology":null},{"paper":null,"slug":"biocube-a-multimodal-dataset-for-biodiversity","title":"BioCube: A Multimodal Dataset for Biodiversity Research","date":"2025-05-16","arxiv_id":"2505.11568","n_code_links":0,"syntology":null},{"paper":"/paper/finetune-rag-fine-tuning-language-models-to","slug":"finetune-rag-fine-tuning-language-models-to","title":"Finetune-RAG: Fine-Tuning Language Models to Resist Hallucination in Retrieval-Augmented Generation","date":"2025-05-16","arxiv_id":"2505.10792","n_code_links":1,"syntology":null},{"paper":"/paper/reasoning-on-a-budget-miniaturizing-deepseek","slug":"reasoning-on-a-budget-miniaturizing-deepseek","title":"Reasoning on a Budget: Miniaturizing DeepSeek R1 with SFT-GRPO Alignment for Instruction-Tuned LLMs","date":"2025-05-16","arxiv_id":null,"n_code_links":1,"syntology":null},{"paper":null,"slug":"specmemo-speculative-decoding-is-in-your","title":"SpecMemo: Speculative Decoding is in Your Pocket","date":"2025-05-16","arxiv_id":"2506.01986","n_code_links":0,"syntology":null},{"paper":null,"slug":"spectral-policy-optimization-coloring-your","title":"Spectral Policy Optimization: Coloring your Incorrect Reasoning in GRPO","date":"2025-05-16","arxiv_id":"2505.11595","n_code_links":0,"syntology":null},{"paper":null,"slug":"2505-10717","title":"A Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment","date":"2025-05-15","arxiv_id":"2505.10717","n_code_links":0,"syntology":null},{"paper":"/paper/adaptclip-adapting-clip-for-universal-visual","slug":"adaptclip-adapting-clip-for-universal-visual","title":"AdaptCLIP: Adapting CLIP for Universal Visual Anomaly Detection","date":"2025-05-15","arxiv_id":"2505.09926","n_code_links":1,"syntology":null},{"paper":"/paper/adhmr-aligning-diffusion-based-human-mesh","slug":"adhmr-aligning-diffusion-based-human-mesh","title":"ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization","date":"2025-05-15","arxiv_id":"2505.10250","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":["shenwenhao01/adhmr"],"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":"flowvat-normalizing-flow-variational","title":"FlowVAT: Normalizing Flow Variational Inference with Affine-Invariant Tempering","date":"2025-05-15","arxiv_id":"2505.10466","n_code_links":0,"syntology":null},{"paper":null,"slug":"generative-ai-aided-qoe-maximization-for-ris","title":"Generative AI-Aided QoE Maximization for RIS-Assisted Digital Twin Interaction","date":"2025-05-15","arxiv_id":"2505.15828","n_code_links":0,"syntology":null},{"paper":"/paper/large-wireless-localization-model-lwlm-a","slug":"large-wireless-localization-model-lwlm-a","title":"Large Wireless Localization Model (LWLM): A Foundation Model for Positioning in 6G Networks","date":"2025-05-15","arxiv_id":"2505.10134","n_code_links":1,"syntology":null},{"paper":null,"slug":"learning-to-think-information-theoretic","title":"Learning to Think: Information-Theoretic Reinforcement Fine-Tuning for LLMs","date":"2025-05-15","arxiv_id":"2505.10425","n_code_links":0,"syntology":null},{"paper":"/paper/mmrl-parameter-efficient-and-interaction","slug":"mmrl-parameter-efficient-and-interaction","title":"MMRL++: Parameter-Efficient and Interaction-Aware Representation Learning for Vision-Language Models","date":"2025-05-15","arxiv_id":"2505.10088","n_code_links":1,"syntology":null},{"paper":null,"slug":"uav-enabled-passive-6dma-for-isac-joint","title":"UAV-Enabled Passive 6DMA for ISAC: Joint Location, Orientation, and Reflection Optimization","date":"2025-05-15","arxiv_id":"2505.10220","n_code_links":0,"syntology":null},{"paper":null,"slug":"variational-bayesian-inference-for-time","title":"Variational Bayesian Inference for Time-Varying Massive MIMO Channels: Estimation and Detection","date":"2025-05-15","arxiv_id":"2505.10673","n_code_links":0,"syntology":null},{"paper":"/paper/worldpm-scaling-human-preference-modeling","slug":"worldpm-scaling-human-preference-modeling","title":"WorldPM: Scaling Human Preference Modeling","date":"2025-05-15","arxiv_id":"2505.10527","n_code_links":1,"syntology":null},{"paper":null,"slug":"a-standardized-benchmark-set-of-clustering","title":"A Standardized Benchmark Set of Clustering Problem Instances for Comparing Black-Box Optimizers","date":"2025-05-14","arxiv_id":"2505.09233","n_code_links":0,"syntology":null},{"paper":"/paper/achieving-tokenizer-flexibility-in-language","slug":"achieving-tokenizer-flexibility-in-language","title":"Achieving Tokenizer Flexibility in Language Models through Heuristic Adaptation and Supertoken Learning","date":"2025-05-14","arxiv_id":"2505.09738","n_code_links":1,"syntology":null},{"paper":"/paper/atomic-consistency-preference-optimization","slug":"atomic-consistency-preference-optimization","title":"Atomic Consistency Preference Optimization for Long-Form Question Answering","date":"2025-05-14","arxiv_id":"2505.09039","n_code_links":1,"syntology":null},{"paper":null,"slug":"customizing-a-large-language-model-for-vhdl","title":"Customizing a Large Language Model for VHDL Design of High-Performance Microprocessors","date":"2025-05-14","arxiv_id":"2505.09610","n_code_links":0,"syntology":null},{"paper":"/paper/cxmarena-unified-dataset-to-benchmark","slug":"cxmarena-unified-dataset-to-benchmark","title":"CXMArena: Unified Dataset to benchmark performance in realistic CXM Scenarios","date":"2025-05-14","arxiv_id":"2505.09436","n_code_links":1,"syntology":null},{"paper":null,"slug":"enhanced-photonic-chip-design-via","title":"Enhanced Photonic Chip Design via Interpretable Machine Learning Techniques","date":"2025-05-14","arxiv_id":"2505.09266","n_code_links":0,"syntology":null},{"paper":"/paper/focus-merge-rank-improved-question-answering","slug":"focus-merge-rank-improved-question-answering","title":"Focus, Merge, Rank: Improved Question Answering Based on Semi-structured Knowledge Bases","date":"2025-05-14","arxiv_id":"2505.09246","n_code_links":1,"syntology":null},{"paper":null,"slug":"thz-band-near-field-ris-channel-modeling-for","title":"THz-Band Near-Field RIS Channel Modeling for Linear Channel Estimation","date":"2025-05-14","arxiv_id":"2505.09767","n_code_links":0,"syntology":null},{"paper":null,"slug":"am-thinking-v1-advancing-the-frontier-of","title":"AM-Thinking-v1: Advancing the Frontier of Reasoning at 32B Scale","date":"2025-05-13","arxiv_id":"2505.08311","n_code_links":0,"syntology":null},{"paper":null,"slug":"for-gpt-4-as-with-humans-information","title":"For GPT-4 as with Humans: Information Structure Predicts Acceptability of Long-Distance Dependencies","date":"2025-05-13","arxiv_id":"2505.09005","n_code_links":0,"syntology":null},{"paper":null,"slug":"joint-optimization-of-user-association-and","title":"Joint Optimization of User Association and Resource Allocation for Load Balancing With Multi-Level Fairness","date":"2025-05-13","arxiv_id":"2505.08573","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-like-humans-advancing-llm-reasoning","title":"Learning Like Humans: Advancing LLM Reasoning Capabilities via Adaptive Difficulty Curriculum Learning and Expert-Guided Self-Reformulation","date":"2025-05-13","arxiv_id":"2505.08364","n_code_links":0,"syntology":null},{"paper":null,"slug":"max-min-fairness-in-stacked-intelligent","title":"Max-Min Fairness in Stacked Intelligent Metasurface-Aided Rate Splitting Networks","date":"2025-05-13","arxiv_id":"2505.08521","n_code_links":0,"syntology":null},{"paper":null,"slug":"performance-analysis-of-cooperative-1","title":"Performance Analysis of Cooperative Integrated Sensing and Communications for 6G Networks","date":"2025-05-13","arxiv_id":"2505.08221","n_code_links":0,"syntology":null},{"paper":null,"slug":"pwc-moe-privacy-aware-wireless-collaborative","title":"PWC-MoE: Privacy-Aware Wireless Collaborative Mixture of Experts","date":"2025-05-13","arxiv_id":"2505.08719","n_code_links":0,"syntology":null},{"paper":null,"slug":"robust-beamforming-design-for-star-ris-aided","title":"Robust Beamforming Design for STAR-RIS Aided RSMA Network with Hardware Impairments","date":"2025-05-13","arxiv_id":"2505.08642","n_code_links":0,"syntology":null},{"paper":null,"slug":"wixqa-a-multi-dataset-benchmark-for","title":"WixQA: A Multi-Dataset Benchmark for Enterprise Retrieval-Augmented Generation","date":"2025-05-13","arxiv_id":"2505.08643","n_code_links":0,"syntology":null},{"paper":null,"slug":"4tastic-time-and-trend-traveling-time-series","title":"4TaStiC: Time and trend traveling time series clustering for classifying long-term type 2 diabetes patients","date":"2025-05-12","arxiv_id":"2505.07702","n_code_links":0,"syntology":null},{"paper":"/paper/agent-rl-scaling-law-agent-rl-with","slug":"agent-rl-scaling-law-agent-rl-with","title":"Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving","date":"2025-05-12","arxiv_id":"2505.07773","n_code_links":2,"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":["anonymize-author/agentrl","yyht/openrlhf_async_pipline"],"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/mimo-unlocking-the-reasoning-potential-of","slug":"mimo-unlocking-the-reasoning-potential-of","title":"MiMo: Unlocking the Reasoning Potential of Language Model -- From Pretraining to Posttraining","date":"2025-05-12","arxiv_id":"2505.07608","n_code_links":1,"syntology":null},{"paper":null,"slug":"minimax-speech-intrinsic-zero-shot-text-to","title":"MiniMax-Speech: Intrinsic Zero-Shot Text-to-Speech with a Learnable Speaker Encoder","date":"2025-05-12","arxiv_id":"2505.07916","n_code_links":0,"syntology":null},{"paper":null,"slug":"pilot-based-end-to-end-radio-positioning-and","title":"Pilot-Based End-to-End Radio Positioning and Mapping for ISAC: Beyond Point-Based Landmarks","date":"2025-05-12","arxiv_id":"2505.07402","n_code_links":0,"syntology":null},{"paper":null,"slug":"private-lora-fine-tuning-of-open-source-llms","title":"Private LoRA Fine-tuning of Open-Source LLMs with Homomorphic Encryption","date":"2025-05-12","arxiv_id":"2505.07329","n_code_links":0,"syntology":null},{"paper":null,"slug":"remedi-relative-feature-enhanced-meta","title":"REMEDI: Relative Feature Enhanced Meta-Learning with Distillation for Imbalanced Prediction","date":"2025-05-12","arxiv_id":"2505.07245","n_code_links":0,"syntology":null},{"paper":null,"slug":"cross-link-interference-mitigation-with-over","title":"Cross-Link Interference Mitigation With Over-the-Air Pilot Forwarding for Dynamic TDD","date":"2025-05-11","arxiv_id":"2505.06816","n_code_links":0,"syntology":null},{"paper":null,"slug":"multi-objective-guided-discrete-flow-matching","title":"Multi-Objective-Guided Discrete Flow Matching for Controllable Biological Sequence Design","date":"2025-05-11","arxiv_id":"2505.07086","n_code_links":0,"syntology":null},{"paper":null,"slug":"realistic-counterfactual-explanations-for","title":"Realistic Counterfactual Explanations for Machine Learning-Controlled Mobile Robots using 2D LiDAR","date":"2025-05-11","arxiv_id":"2505.06906","n_code_links":0,"syntology":null},{"paper":null,"slug":"time-modulated-em-skins-for-integrated","title":"Time-Modulated EM Skins for Integrated Sensing and Communications","date":"2025-05-11","arxiv_id":"2505.06909","n_code_links":0,"syntology":null},{"paper":null,"slug":"illuminating-the-path-attention-assisted","title":"Illuminating the Path: Attention-Assisted Beamforming and Predictive Insights in 5G NR Systems","date":"2025-05-10","arxiv_id":"2505.18160","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":"an-exploratory-analysis-on-the-explanatory","title":"An Exploratory Analysis on the Explanatory Potential of Embedding-Based Measures of Semantic Transparency for Malay Word Recognition","date":"2025-05-09","arxiv_id":"2505.05973","n_code_links":0,"syntology":null},{"paper":null,"slug":"learning-augmented-algorithms-for-boolean","title":"Learning-Augmented Algorithms for Boolean Satisfiability","date":"2025-05-09","arxiv_id":"2505.06146","n_code_links":0,"syntology":null},{"paper":null,"slug":"picd-versatile-perceptual-image-compression","title":"PICD: Versatile Perceptual Image Compression with Diffusion Rendering","date":"2025-05-09","arxiv_id":"2505.05853","n_code_links":0,"syntology":null},{"paper":null,"slug":"reliable-collaborative-conversational-agent","title":"Reliable Collaborative Conversational Agent System Based on LLMs and Answer Set Programming","date":"2025-05-09","arxiv_id":"2505.06438","n_code_links":0,"syntology":null},{"paper":"/paper/biomed-dpt-dual-modality-prompt-tuning-for","slug":"biomed-dpt-dual-modality-prompt-tuning-for","title":"Biomed-DPT: Dual Modality Prompt Tuning for Biomedical Vision-Language Models","date":"2025-05-08","arxiv_id":"2505.05189","n_code_links":1,"syntology":null},{"paper":null,"slug":"compo-preference-alignment-via-comparison","title":"ComPO: Preference Alignment via Comparison Oracles","date":"2025-05-08","arxiv_id":"2505.05465","n_code_links":0,"syntology":null},{"paper":null,"slug":"crashsage-a-large-language-model-centered","title":"CrashSage: A Large Language Model-Centered Framework for Contextual and Interpretable Traffic Crash Analysis","date":"2025-05-08","arxiv_id":"2505.07853","n_code_links":0,"syntology":null},{"paper":"/paper/enhancing-satellite-object-localization-with","slug":"enhancing-satellite-object-localization-with","title":"Enhancing Satellite Object Localization with Dilated Convolutions and Attention-aided Spatial Pooling","date":"2025-05-08","arxiv_id":"2505.05599","n_code_links":1,"syntology":null},{"paper":null,"slug":"gcn-based-throughput-oriented-handover","title":"GCN-Based Throughput-Oriented Handover Management in Dense 5G Vehicular Networks","date":"2025-05-08","arxiv_id":"2505.04894","n_code_links":0,"syntology":null},{"paper":null,"slug":"latent-preference-coding-aligning-large","title":"Latent Preference Coding: Aligning Large Language Models via Discrete Latent Codes","date":"2025-05-08","arxiv_id":"2505.04993","n_code_links":0,"syntology":null},{"paper":null,"slug":"mtl-ue-learning-to-learn-nothing-for-multi","title":"MTL-UE: Learning to Learn Nothing for Multi-Task Learning","date":"2025-05-08","arxiv_id":"2505.05279","n_code_links":0,"syntology":null},{"paper":"/paper/openworldauc-towards-unified-evaluation-and","slug":"openworldauc-towards-unified-evaluation-and","title":"OpenworldAUC: Towards Unified Evaluation and Optimization for Open-world Prompt Tuning","date":"2025-05-08","arxiv_id":"2505.05180","n_code_links":1,"syntology":null},{"paper":"/paper/prompt-based-llms-for-position-bias-aware","slug":"prompt-based-llms-for-position-bias-aware","title":"Prompt-Based LLMs for Position Bias-Aware Reranking in Personalized Recommendations","date":"2025-05-08","arxiv_id":"2505.04948","n_code_links":1,"syntology":null},{"paper":"/paper/cyber-security-data-science-machine-learning","slug":"cyber-security-data-science-machine-learning","title":"Cyber Security Data Science: Machine Learning Methods and their Performance on Imbalanced Datasets","date":"2025-05-07","arxiv_id":"2505.04204","n_code_links":1,"syntology":null},{"paper":"/paper/echoink-r1-exploring-audio-visual-reasoning","slug":"echoink-r1-exploring-audio-visual-reasoning","title":"EchoInk-R1: Exploring Audio-Visual Reasoning in Multimodal LLMs via Reinforcement Learning","date":"2025-05-07","arxiv_id":"2505.04623","n_code_links":1,"syntology":null},{"paper":null,"slug":"guide-your-favorite-protein-sequence","title":"Guide your favorite protein sequence generative model","date":"2025-05-07","arxiv_id":"2505.04823","n_code_links":0,"syntology":null},{"paper":null,"slug":"integrated-equilibrium-model-for-electrified","title":"Integrated equilibrium model for electrified logistics and power systems","date":"2025-05-07","arxiv_id":"2505.04532","n_code_links":0,"syntology":null},{"paper":null,"slug":"near-field-mimo-channel-acquisition-geometry","title":"Near-Field MIMO Channel Acquisition: Geometry-Aided Feedback and Transmission Design","date":"2025-05-07","arxiv_id":"2505.04305","n_code_links":0,"syntology":null},{"paper":null,"slug":"putting-the-value-back-in-rl-better-test-time","title":"Putting the Value Back in RL: Better Test-Time Scaling by Unifying LLM Reasoners With Verifiers","date":"2025-05-07","arxiv_id":"2505.04842","n_code_links":0,"syntology":null},{"paper":null,"slug":"soaesv2-7b-72b-full-pipeline-optimization-for","title":"SOAEsV2-7B/72B: Full-Pipeline Optimization for State-Owned Enterprise LLMs via Continual Pre-Training, Domain-Progressive SFT and Distillation-Enhanced Speculative Decoding","date":"2025-05-07","arxiv_id":"2505.04723","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-aloe-family-recipe-for-open-and","title":"The Aloe Family Recipe for Open and Specialized Healthcare LLMs","date":"2025-05-07","arxiv_id":"2505.04388","n_code_links":0,"syntology":null},{"paper":null,"slug":"when-bad-data-leads-to-good-models","title":"When Bad Data Leads to Good Models","date":"2025-05-07","arxiv_id":"2505.04741","n_code_links":0,"syntology":null},{"paper":"/paper/zerosearch-incentivize-the-search-capability","slug":"zerosearch-incentivize-the-search-capability","title":"ZeroSearch: Incentivize the Search Capability of LLMs without Searching","date":"2025-05-07","arxiv_id":"2505.04588","n_code_links":1,"syntology":{"ran":7,"of":15,"n_ran_checked":3,"n_instrument":4,"unverified":8,"pointer_only":0,"phrase":"7 ran (of which 0 constructed an object rather than computing a result; 3 with no instrument failure: 1 honoured, 0 violated, 2 with no contract checked; 4 where Syntology's instrument failed) · 8 unverified","official":{"repos":["alibaba-nlp/zerosearch"],"state":"official (archive's flag): 7 ran","n_ran":7,"n_constructed":0,"n_ran_no_instrument_failure":3,"n_unverified":8,"ran_from_kinds":["official"]}}},{"paper":null,"slug":"a-trustworthy-multi-llm-network-challenges","title":"A Trustworthy Multi-LLM Network: Challenges,Solutions, and A Use Case","date":"2025-05-06","arxiv_id":"2505.03196","n_code_links":0,"syntology":null},{"paper":null,"slug":"base-detail-feature-learning-framework-for","title":"Base-Detail Feature Learning Framework for Visible-Infrared Person Re-Identification","date":"2025-05-06","arxiv_id":"2505.03286","n_code_links":0,"syntology":null},{"paper":null,"slug":"differentially-private-densest-k-subgraph","title":"Differentially Private Densest-$k$-Subgraph","date":"2025-05-06","arxiv_id":"2505.03858","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":"hierarchical-forecast-reconciliation-on","title":"Hierarchical Forecast Reconciliation on Networks: A Network Flow Optimization Formulation","date":"2025-05-06","arxiv_id":"2505.03955","n_code_links":0,"syntology":null},{"paper":null,"slug":"marco-a-multi-agent-system-for-optimizing-hpc","title":"MARCO: Multi-Agent Code Optimization with Real-Time Knowledge Integration for High-Performance Computing","date":"2025-05-06","arxiv_id":"2505.03906","n_code_links":0,"syntology":null},{"paper":"/paper/token-communication-driven-multimodal-large","slug":"token-communication-driven-multimodal-large","title":"Token Communication-Driven Multimodal Large Models in Resource-Constrained Multiuser Networks","date":"2025-05-06","arxiv_id":"2505.07841","n_code_links":1,"syntology":null},{"paper":null,"slug":"developing-a-framework-to-support-human","title":"Developing A Framework to Support Human Evaluation of Bias in Generated Free Response Text","date":"2025-05-05","arxiv_id":"2505.03053","n_code_links":0,"syntology":null},{"paper":null,"slug":"reem-ensemble-building-thermodynamics-model","title":"ReeM: Ensemble Building Thermodynamics Model for Efficient HVAC Control via Hierarchical Reinforcement Learning","date":"2025-05-05","arxiv_id":"2505.02439","n_code_links":0,"syntology":null},{"paper":null,"slug":"temporal-robustness-in-discrete-time-linear","title":"Temporal Robustness in Discrete Time Linear Dynamical Systems","date":"2025-05-05","arxiv_id":"2505.02347","n_code_links":0,"syntology":null},{"paper":null,"slug":"the-art-of-repair-optimizing-iterative","title":"The Art of Repair: Optimizing Iterative Program Repair with Instruction-Tuned Models","date":"2025-05-05","arxiv_id":"2505.02931","n_code_links":0,"syntology":null},{"paper":null,"slug":"bayesian-federated-cause-of-death","title":"Bayesian Federated Cause-of-Death Classification and Quantification Under Distribution Shift","date":"2025-05-04","arxiv_id":"2505.02257","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":"training-environment-for-high-performance","title":"Training Environment for High Performance Reinforcement Learning","date":"2025-05-04","arxiv_id":"2505.01953","n_code_links":0,"syntology":null}],"record_sha256":"9c2459f8823ed59f3a17167ba55725487269231736f4451fbfbf9fe09659cd79","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}