{"total":156,"rows":[{"id":"2403.14624","title":"MathVerse: Does Your Multi-modal LLM Truly See the Diagrams in Visual Math Problems?","created":"2024-03-21","cited_by_count":586,"area":"mllm"},{"id":"2406.20094","title":"Scaling Synthetic Data Creation with 1,000,000,000 Personas","created":"2024-06-28","cited_by_count":417,"area":"synth"},{"id":"2503.09567","title":"Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language Models","created":"2025-03-12","cited_by_count":384,"area":"lr"},{"id":"2501.04519","title":"rStar-Math: Small LLMs Can Master Math Reasoning with Self-Evolved Deep Thinking","created":"2025-01-08","cited_by_count":313,"area":"lr"},{"id":"2311.07575","title":"SPHINX: The Joint Mixing of Weights, Tasks, and Visual Embeddings for Multi-modal Large Language Models","created":"2023-11-13","cited_by_count":286,"area":"mllm"},{"id":"2407.01284","title":"We-Math: Does Your Large Multimodal Model Achieve Human-like Mathematical Reasoning?","created":"2024-07-01","cited_by_count":286,"area":"lr"},{"id":"2406.18629","title":"Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs","created":"2024-06-26","cited_by_count":273,"area":"lr"},{"id":"2401.05459","title":"Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security","created":"2024-01-10","cited_by_count":260,"area":"agents"},{"id":"2503.23383","title":"ToRL: Scaling Tool-Integrated RL","created":"2025-03-30","cited_by_count":169,"area":"agents"},{"id":"2405.03553","title":"AlphaMath Almost Zero: Process Supervision without Process","created":"2024-05-06","cited_by_count":162,"area":"lr"},{"id":"2402.14800","title":"Not All Experts are Equal: Efficient Expert Pruning and Skipping for Mixture-of-Experts Large Language Models","created":"2024-02-22","cited_by_count":146,"area":"moe"},{"id":"2402.10176","title":"OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset","created":"2024-02-15","cited_by_count":143,"area":"lr"},{"id":"2511.05271","title":"DeepEyesV2: Toward Agentic Multimodal Model","created":"2025-11-07","cited_by_count":125,"area":"agents"},{"id":"2402.06332","title":"InternLM-Math: Open Math Large Language Models Toward Verifiable Reasoning","created":"2024-02-09","cited_by_count":119,"area":"lr"},{"id":"2407.08739","title":"MAVIS: Mathematical Visual Instruction Tuning with an Automatic Data Engine","created":"2024-07-11","cited_by_count":113,"area":"lr"},{"id":"2310.20689","title":"Learning From Mistakes Makes LLM Better Reasoner","created":"2023-10-31","cited_by_count":101,"area":"lr"},{"id":"2503.20752","title":"Reason-RFT: Reinforcement Fine-Tuning for Visual Reasoning of Vision Language Models","created":"2025-03-26","cited_by_count":99,"area":"lr"},{"id":"2406.10833","title":"A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery","created":"2024-06-16","cited_by_count":96,"area":null},{"id":"2509.01055","title":"VerlTool: Towards Holistic Agentic Reinforcement Learning with Tool Use","created":"2025-09-01","cited_by_count":96,"area":"lr"},{"id":"2410.15115","title":"On Designing Effective RL Reward at Training Time for LLM Reasoning","created":"2024-10-19","cited_by_count":87,"area":"lr"},{"id":"2401.08190","title":"MARIO: MAth Reasoning with code Interpreter Output -- A Reproducible Pipeline","created":"2024-01-16","cited_by_count":81,"area":"lr"},{"id":"2402.16352","title":"MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs","created":"2024-02-26","cited_by_count":72,"area":"lr"},{"id":"2406.10858","title":"Step-level Value Preference Optimization for Mathematical Reasoning","created":"2024-06-16","cited_by_count":72,"area":"lr"},{"id":"2402.11451","title":"SciAgent: Tool-augmented Language Models for Scientific Reasoning","created":"2024-02-18","cited_by_count":70,"area":"lr"},{"id":"2504.17192","title":"Paper2Code: Automating Code Generation from Scientific Papers in Machine Learning","created":"2025-04-24","cited_by_count":70,"area":null},{"id":"2407.21018","title":"ThinK: Thinner Key Cache by Query-Driven Pruning","created":"2024-07-30","cited_by_count":68,"area":"lr"},{"id":"2506.13654","title":"Ego-R1: Chain-of-Tool-Thought for Ultra-Long Egocentric Video Reasoning","created":"2025-06-16","cited_by_count":68,"area":"lr"},{"id":"2505.07773","title":"Agent RL Scaling Law: Agent RL with Spontaneous Code Execution for Mathematical Problem Solving","created":"2025-05-12","cited_by_count":62,"area":"lr"},{"id":"2412.11936","title":"A Survey of Mathematical Reasoning in the Era of Multimodal Large Language Model: Benchmark, Method & Challenges","created":"2024-12-16","cited_by_count":55,"area":"lr"},{"id":"2502.19411","title":"Code to Think, Think to Code: A Survey on Code-Enhanced Reasoning and Reasoning-Driven Code Intelligence in LLMs","created":"2025-02-26","cited_by_count":47,"area":"lr"},{"id":"2605.18747","title":"Code as Agent Harness","created":"2026-05-18","cited_by_count":47,"area":"agents"},{"id":"2405.14365","title":"JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models","created":"2024-05-23","cited_by_count":45,"area":"lr"},{"id":"2505.10557","title":"MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning","created":"2025-05-15","cited_by_count":45,"area":"lr"},{"id":"2506.19835","title":"MAM: Modular Multi-Agent Framework for Multi-Modal Medical Diagnosis via Role-Specialized Collaboration","created":"2025-06-24","cited_by_count":40,"area":"lr"},{"id":"2410.08196","title":"MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code","created":"2024-10-10","cited_by_count":39,"area":"lr"},{"id":"2505.08783","title":"CodePDE: An Inference Framework for LLM-driven PDE Solver Generation","created":"2025-05-13","cited_by_count":39,"area":null},{"id":"2407.00782","title":"Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning","created":"2024-06-30","cited_by_count":35,"area":"lr"},{"id":"2510.14958","title":"MathCanvas: Intrinsic Visual Chain-of-Thought for Multimodal Mathematical Reasoning","created":"2025-10-16","cited_by_count":35,"area":"lr"},{"id":"2502.02871","title":"Position: Multimodal Large Language Models Can Significantly Advance Scientific Reasoning","created":"2025-02-05","cited_by_count":33,"area":"lr"},{"id":"2510.11701","title":"Demystifying Reinforcement Learning in Agentic Reasoning","created":"2025-10-13","cited_by_count":33,"area":"lr"},{"id":"2402.09664","title":"CodeMind: Evaluating Large Language Models for Code Reasoning","created":"2024-02-15","cited_by_count":32,"area":"lr"},{"id":"2406.11503","title":"GeoGPT4V: Towards Geometric Multi-modal Large Language Models with Geometric Image Generation","created":"2024-06-17","cited_by_count":32,"area":"mllm"},{"id":"2509.24765","title":"Semantic-Aware Logical Reasoning via a Semiotic Framework","created":"2025-09-29","cited_by_count":32,"area":"lr"},{"id":"2511.19900","title":"Agent0-VL: Exploring Self-Evolving Agent for Tool-Integrated Vision-Language Reasoning","created":"2025-11-25","cited_by_count":31,"area":"lr"},{"id":"2503.16212","title":"MathFusion: Enhancing Mathematical Problem-solving of LLM through Instruction Fusion","created":"2025-03-20","cited_by_count":30,"area":"lr"},{"id":"2408.08656","title":"LLMs Are Biased Towards Output Formats! Systematically Evaluating and Mitigating Output Format Bias of LLMs","created":"2024-08-16","cited_by_count":25,"area":null},{"id":"2504.12597","title":"GeoSense: Evaluating Identification and Application of Geometric Principles in Multimodal Reasoning","created":"2025-04-17","cited_by_count":25,"area":"lr"},{"id":"2601.02902","title":"Logical Phase Transitions: Understanding Collapse in LLM Logical Reasoning","created":"2026-01-06","cited_by_count":25,"area":"lr"},{"id":"2410.03524","title":"Steering Large Language Models between Code Execution and Textual Reasoning","created":"2024-10-04","cited_by_count":24,"area":"lr"},{"id":"2410.18693","title":"Unleashing LLM Reasoning Capability via Scalable Question Synthesis from Scratch","created":"2024-10-24","cited_by_count":24,"area":"lr"},{"id":"2412.00821","title":"Improving Physics Reasoning in Large Language Models Using Mixture of Refinement Agents","created":"2024-12-01","cited_by_count":24,"area":"lr"},{"id":"2505.24362","title":"Knowing Before Saying: LLM Representations Encode Information About Chain-of-Thought Success Before Completion","created":"2025-05-30","cited_by_count":23,"area":"lr"},{"id":"2510.10991","title":"A Survey on Agentic Multimodal Large Language Models","created":"2025-10-13","cited_by_count":23,"area":"mllm"},{"id":"2510.11718","title":"CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images","created":"2025-10-13","cited_by_count":23,"area":"lr"},{"id":"2405.07551","title":"MuMath-Code: Combining Tool-Use Large Language Models with Multi-perspective Data Augmentation for Mathematical Reasoning","created":"2024-05-13","cited_by_count":22,"area":"lr"},{"id":"2412.04857","title":"Neuro-Symbolic Data Generation for Math Reasoning","created":"2024-12-06","cited_by_count":22,"area":"lr"},{"id":"2409.13729","title":"MathGLM-Vision: Solving Mathematical Problems with Multi-Modal Large Language Model","created":"2024-09-10","cited_by_count":21,"area":"lr"},{"id":"2507.13618","title":"Seed-X: Building Strong Multilingual Translation LLM with 7B Parameters","created":"2025-07-18","cited_by_count":21,"area":null},{"id":"2601.03555","title":"SCRIBE: Structured Mid-Level Supervision for Tool-Using Language Models","created":"2026-01-07","cited_by_count":21,"area":"alignment"},{"id":"2501.18617","title":"DarkMind: Latent Chain-of-Thought Backdoor in Customized LLMs","created":"2025-01-24","cited_by_count":20,"area":"lr"},{"id":"2409.04267","title":"An overview of domain-specific foundation model: key technologies, applications and challenges","created":"2024-09-06","cited_by_count":19,"area":null},{"id":"2410.17635","title":"Markov Chain of Thought for Efficient Mathematical Reasoning","created":"2024-10-23","cited_by_count":19,"area":"lr"},{"id":"2503.03196","title":"SpiritSight Agent: Advanced GUI Agent with One Look","created":"2025-03-05","cited_by_count":18,"area":"agents"},{"id":"2406.13846","title":"Text Serialization and Their Relationship with the Conventional Paradigms of Tabular Machine Learning","created":"2024-06-19","cited_by_count":17,"area":null},{"id":"2502.11476","title":"FastMCTS: A Simple Sampling Strategy for Data Synthesis","created":"2025-02-17","cited_by_count":17,"area":"lr"},{"id":"2512.20745","title":"AgentMath: Empowering Mathematical Reasoning for Large Language Models via Tool-Augmented Agent","created":"2025-12-23","cited_by_count":17,"area":"lr"},{"id":"2411.11504","title":"Search, Verify and Feedback: Towards Next Generation Post-training Paradigm of Foundation Models via Verifier Engineering","created":"2024-11-18","cited_by_count":16,"area":null},{"id":"2506.17667","title":"PhysUniBench: A Multi-Modal Physics Reasoning Benchmark at Undergraduate Level","created":"2025-06-21","cited_by_count":16,"area":"lr"},{"id":"2406.12050","title":"Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning","created":"2024-06-17","cited_by_count":15,"area":"lr"},{"id":"2405.17057","title":"ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation","created":"2024-05-27","cited_by_count":14,"area":"lr"},{"id":"2502.13137","title":"Theorem Prover as a Judge for Synthetic Data Generation","created":"2025-02-18","cited_by_count":14,"area":"lr"},{"id":"2403.18295","title":"Dual Instruction Tuning with Large Language Models for Mathematical Reasoning","created":"2024-03-27","cited_by_count":10,"area":"lr"},{"id":"2405.10959","title":"Foundation Models for Education: Promises and Prospects","created":"2024-04-08","cited_by_count":10,"area":null},{"id":"2503.01700","title":"Code-as-Symbolic-Planner: Foundation Model-Based Robot Planning via Symbolic Code Generation","created":"2025-03-03","cited_by_count":10,"area":null},{"id":"2502.13791","title":"From Tools to Teammates: Evaluating LLMs in Multi-Session Coding Interactions","created":"2025-02-19","cited_by_count":8,"area":null},{"id":"2502.20859","title":"The Power of Personality: A Human Simulation Perspective to Investigate Large Language Model Agents","created":"2025-02-28","cited_by_count":8,"area":"agents"},{"id":"2505.11966","title":"Solve-Detect-Verify: Inference-Time Scaling with Flexible Generative Verifier","created":"2025-05-17","cited_by_count":8,"area":"lr"},{"id":"2602.17607","title":"AutoNumerics: An Autonomous, PDE-Agnostic Multi-Agent Pipeline for Scientific Computing","created":"2026-02-19","cited_by_count":8,"area":"agents"},{"id":"2608.03874","title":"ContinualSkillBench: Can LLM Agents Truly Evolve Their Capabilities?","created":"2026-08-04","cited_by_count":8,"area":"agents"},{"id":"2403.00799","title":"An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning","created":"2024-02-23","cited_by_count":7,"area":"lr"},{"id":"2412.16964","title":"System-2 Mathematical Reasoning via Enriched Instruction Tuning","created":"2024-12-22","cited_by_count":7,"area":"lr"},{"id":"2412.18072","title":"MMFactory: A Universal Solution Search Engine for Vision-Language Tasks","created":"2024-12-24","cited_by_count":7,"area":"mllm"},{"id":"2501.18482","title":"A Tool for In-depth Analysis of Code Execution Reasoning of Large Language Models","created":"2025-01-30","cited_by_count":7,"area":"lr"},{"id":"2509.05657","title":"LM-Searcher: Cross-domain Neural Architecture Search with LLMs via Unified Numerical Encoding","created":"2025-09-06","cited_by_count":7,"area":null},{"id":"2509.25851","title":"MuSLR: Multimodal Symbolic Logical Reasoning","created":"2025-09-30","cited_by_count":7,"area":"lr"},{"id":"2510.19361","title":"AgenticMath: Enhancing LLM Reasoning via Agentic-based Math Data Generation","created":"2025-10-22","cited_by_count":7,"area":"lr"},{"id":"2512.10931","title":"Asynchronous Reasoning: Training-Free Interactive Thinking LLMs","created":"2025-12-11","cited_by_count":7,"area":"lr"},{"id":"2408.15565","title":"SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models","created":"2024-08-28","cited_by_count":6,"area":"lr"},{"id":"2505.21785","title":"Born a Transformer -- Always a Transformer? On the Effect of Pretraining on Architectural Abilities","created":"2025-05-27","cited_by_count":6,"area":null},{"id":"2510.10085","title":"Pharmacist: Safety Alignment Data Curation for Large Language Models against Harmful Fine-tuning","created":"2025-10-11","cited_by_count":6,"area":"alignment"},{"id":"2604.19749","title":"The Tool-Overuse Illusion: Why Does LLM Prefer External Tools over Internal Knowledge?","created":"2026-03-03","cited_by_count":6,"area":null},{"id":"2606.14502","title":"From Chatbot to Digital Colleague: The Paradigm Shift Toward Persistent Autonomous AI","created":"2026-06-12","cited_by_count":6,"area":null},{"id":"2608.03972","title":"ReflectRL: Learning from Golden Negative Trajectories via Reflective-to-Direct Reasoning","created":"2026-08-04","cited_by_count":6,"area":"lr"},{"id":"2403.06097","title":"Can LLM Substitute Human Labeling? A Case Study of Fine-grained Chinese Address Entity Recognition Dataset for UAV Delivery","created":"2024-03-10","cited_by_count":5,"area":null},{"id":"2410.13510","title":"GeoCoder: Solving Geometry Problems by Generating Modular Code through Vision-Language Models","created":"2024-10-17","cited_by_count":5,"area":"lr"},{"id":"2507.15640","title":"Data Mixing Agent: Learning to Re-weight Domains for Continual Pre-training","created":"2025-07-21","cited_by_count":5,"area":"agents"},{"id":"2510.15079","title":"Assessing Coherency and Consistency of Code Execution Reasoning by Large Language Models","created":"2025-10-16","cited_by_count":5,"area":"lr"},{"id":"2601.09066","title":"Mi:dm 2.0 Korea-centric Bilingual Language Models","created":"2026-01-14","cited_by_count":5,"area":null},{"id":"2402.13035","title":"Learning to Check: Unleashing Potentials for Self-Correction in Large Language Models","created":"2024-02-20","cited_by_count":4,"area":"lr"},{"id":"2406.17873","title":"Improving Arithmetic Reasoning Ability of Large Language Models through Relation Tuples, Verification and Dynamic Feedback","created":"2024-06-25","cited_by_count":4,"area":"lr"}],"next_cursor":"100"}