{"total":115,"rows":[{"id":"2505.09388","title":"Qwen3 Technical Report","created":"2025-05-14","cited_by_count":8820,"area":"lr"},{"id":"2506.04178","title":"OpenThoughts: Data Recipes for Reasoning Models","created":"2025-06-04","cited_by_count":304,"area":"lr"},{"id":"2506.11763","title":"DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents","created":"2025-06-13","cited_by_count":248,"area":"agents"},{"id":"2502.12115","title":"SWE-Lancer: Can Frontier LLMs Earn $1 Million from Real-World Freelance Software Engineering?","created":"2025-02-17","cited_by_count":105,"area":null},{"id":"2507.02825","title":"Establishing Best Practices for Building Rigorous Agentic Benchmarks","created":"2025-07-03","cited_by_count":102,"area":"agents"},{"id":"2507.09089","title":"Measuring the Impact of Early-2025 AI on Experienced Open-Source Developer Productivity","created":"2025-07-12","cited_by_count":101,"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":"2502.15840","title":"Vending-Bench: A Benchmark for Long-Term Coherence of Autonomous Agents","created":"2025-02-20","cited_by_count":80,"area":"agents"},{"id":"2504.14655","title":"LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs","created":"2025-04-20","cited_by_count":70,"area":"lr"},{"id":"2509.14279","title":"Towards Robust Agentic CUDA Kernel Benchmarking, Verification, and Optimization","created":"2025-09-16","cited_by_count":56,"area":"lr"},{"id":"2506.03524","title":"Seed-Coder: Let the Code Model Curate Data for Itself","created":"2025-06-04","cited_by_count":49,"area":null},{"id":"2512.13607","title":"Nemotron-Cascade: Scaling Cascaded Reinforcement Learning for General-Purpose Reasoning Models","created":"2025-12-15","cited_by_count":48,"area":"lr"},{"id":"2505.11792","title":"Solver-Informed RL: Grounding Large Language Models for Authentic Optimization Modeling","created":"2025-05-17","cited_by_count":45,"area":null},{"id":"2505.13444","title":"ChartMuseum: Testing Visual Reasoning Capabilities of Large Vision-Language Models","created":"2025-05-19","cited_by_count":32,"area":"lr"},{"id":"2505.19702","title":"Point-RFT: Improving Multimodal Reasoning with Visually Grounded Reinforcement Finetuning","created":"2025-05-26","cited_by_count":32,"area":"lr"},{"id":"2503.07919","title":"BEARCUBS: A benchmark for computer-using web agents","created":"2025-03-10","cited_by_count":31,"area":"agents"},{"id":"2504.18838","title":"Toward Generalizable Evaluation in the LLM Era: A Survey Beyond Benchmarks","created":"2025-04-26","cited_by_count":28,"area":null},{"id":"2506.16395","title":"OJBench: A Competition Level Code Benchmark For Large Language Models","created":"2025-06-19","cited_by_count":26,"area":"lr"},{"id":"2504.18530","title":"Scaling Laws For Scalable Oversight","created":"2025-04-25","cited_by_count":23,"area":"safety"},{"id":"2512.15699","title":"FrontierCS: Evolving Challenges for Evolving Intelligence","created":"2025-12-17","cited_by_count":23,"area":null},{"id":"2508.08228","title":"LL3M: Large Language 3D Modelers","created":"2025-08-11","cited_by_count":20,"area":null},{"id":"2504.15254","title":"CRUST-Bench: A Comprehensive Benchmark for C-to-safe-Rust Transpilation","created":"2025-04-21","cited_by_count":19,"area":null},{"id":"2505.08253","title":"Evaluating LLM Metrics Through Real-World Capabilities","created":"2025-05-13","cited_by_count":18,"area":null},{"id":"2510.06672","title":"XRPO: Pushing the limits of GRPO with Targeted Exploration and Exploitation","created":"2025-10-08","cited_by_count":18,"area":"lr"},{"id":"2608.04794","title":"Privileged, but Biased: How PI-Conditioned Teachers Break Self-Distillation","created":"2026-08-05","cited_by_count":18,"area":"distill"},{"id":"2504.21751","title":"CodeFlowBench: A Multi-turn, Iterative Benchmark for Complex Code Generation","created":"2025-04-30","cited_by_count":17,"area":null},{"id":"2506.10963","title":"MMMG: A Massive, Multidisciplinary, Multi-Tier Generation Benchmark for Text-to-Image Reasoning","created":"2025-06-12","cited_by_count":16,"area":"lr"},{"id":"2502.20868","title":"ProBench: Benchmarking Large Language Models in Competitive Programming","created":"2025-02-28","cited_by_count":15,"area":"lr"},{"id":"2505.14733","title":"The Energy Cost of Reasoning: Analyzing Energy Usage in LLMs with Test-time Compute","created":"2025-05-20","cited_by_count":15,"area":"lr"},{"id":"2505.17123","title":"MTR-Bench: A Comprehensive Benchmark for Multi-Turn Reasoning Evaluation","created":"2025-05-21","cited_by_count":15,"area":"lr"},{"id":"2511.18538","title":"From Code Foundation Models to Agents and Applications: A Comprehensive Survey and Practical Guide to Code Intelligence","created":"2025-11-23","cited_by_count":15,"area":"agents"},{"id":"2506.04894","title":"ICPC-Eval: Probing the Frontiers of LLM Reasoning with Competitive Programming Contests","created":"2025-06-05","cited_by_count":13,"area":"lr"},{"id":"2511.03628","title":"LiveTradeBench: Seeking Real-World Alpha with Large Language Models","created":"2025-11-05","cited_by_count":13,"area":"lr"},{"id":"2507.10541","title":"REST: Stress Testing Large Reasoning Models by Asking Multiple Problems at Once","created":"2025-07-14","cited_by_count":12,"area":"lr"},{"id":"2505.05283","title":"Software Development Life Cycle Perspective: A Survey of Benchmarks for Code Large Language Models and Agents","created":"2025-05-08","cited_by_count":11,"area":"agents"},{"id":"2507.01551","title":"Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning","created":"2025-07-02","cited_by_count":11,"area":"lr"},{"id":"2508.16402","title":"AetherCode: Evaluating LLMs' Ability to Win In Premier Programming Competitions","created":"2025-08-22","cited_by_count":11,"area":null},{"id":"2608.00146","title":"DiffusionGemma Technical Report","created":"2026-07-31","cited_by_count":11,"area":"diffusion"},{"id":"2503.16922","title":"RustEvo^2: An Evolving Benchmark for API Evolution in LLM-based Rust Code Generation","created":"2025-03-21","cited_by_count":10,"area":null},{"id":"2506.06821","title":"Can LLMs Generate Reliable Test Case Generators? A Study on Competition-Level Programming Problems","created":"2025-06-07","cited_by_count":9,"area":null},{"id":"2509.19894","title":"PromptCoT 2.0: Scaling Prompt Synthesis for Large Language Model Reasoning","created":"2025-09-24","cited_by_count":9,"area":"lr"},{"id":"2510.04786","title":"Learning on the Job: Test-Time Curricula for Targeted Reinforcement Learning","created":"2025-10-06","cited_by_count":9,"area":"deeprl"},{"id":"2502.09183","title":"RefineCoder: Iterative Improving of Large Language Models via Adaptive Critique Refinement for Code Generation","created":"2025-02-13","cited_by_count":8,"area":"lr"},{"id":"2507.21476","title":"Which LLMs Get the Joke? Probing Non-STEM Reasoning Abilities with HumorBench","created":"2025-07-29","cited_by_count":8,"area":"lr"},{"id":"2606.12191","title":"Agentic Environment Engineering for Large Language Models: A Survey of Environment Modeling, Synthesis, Evaluation, and Application","created":"2026-06-10","cited_by_count":8,"area":"agents"},{"id":"2503.19599","title":"HoarePrompt: Structural Reasoning About Program Correctness in Natural Language","created":"2025-03-25","cited_by_count":7,"area":"lr"},{"id":"2601.19697","title":"AlignCoder: Aligning Retrieval with Target Intent for Repository-Level Code Completion","created":"2026-01-27","cited_by_count":7,"area":null},{"id":"2602.07223","title":"Vegas: Self-Speculative Decoding with Verification-Guided Sparse Attention","created":"2026-02-06","cited_by_count":7,"area":"inference"},{"id":"2505.12331","title":"OSS-Bench: Benchmark Generator for Coding LLMs","created":"2025-05-18","cited_by_count":6,"area":null},{"id":"2506.15787","title":"SLR: Automated Synthesis for Scalable Logical Reasoning","created":"2025-06-18","cited_by_count":6,"area":"lr"},{"id":"2508.07932","title":"\\(X\\)-evolve: Solution space evolution powered by large language models","created":"2025-08-11","cited_by_count":6,"area":null},{"id":"2505.16686","title":"SPaRC: A Spatial Pathfinding Reasoning Challenge","created":"2025-05-22","cited_by_count":5,"area":"lr"},{"id":"2505.19987","title":"How Well Do Large Reasoning Models Translate? A Comprehensive Evaluation for Multi-Domain Machine Translation","created":"2025-05-26","cited_by_count":5,"area":"lr"},{"id":"2506.01074","title":"How Programming Concepts and Neurons Are Shared in Code Language Models","created":"2025-06-01","cited_by_count":5,"area":null},{"id":"2507.22462","title":"IFEvalCode: Controlled Code Generation","created":"2025-07-30","cited_by_count":5,"area":null},{"id":"2602.14798","title":"Overthinking Loops in Agents: A Structural Risk via MCP Tools","created":"2026-02-16","cited_by_count":5,"area":"lr"},{"id":"2602.16066","title":"Improving Interactive In-Context Learning from Natural Language Feedback","created":"2026-02-17","cited_by_count":5,"area":null},{"id":"2608.31075","title":"Scaling Large Reasoning Models beyond Human Supervision: A Path toward Superintelligence","created":"2026-08-31","cited_by_count":5,"area":"lr"},{"id":"2503.05860","title":"Benchmarking AI Models in Software Engineering: A Review, Search Tool, and Unified Approach for Elevating Benchmark Quality","created":"2025-03-07","cited_by_count":4,"area":null},{"id":"2506.07313","title":"SCGAgent: Recreating the Benefits of Reasoning Models for Secure Code Generation with Agentic Workflows","created":"2025-06-08","cited_by_count":4,"area":"agents"},{"id":"2509.12464","title":"Reasoning Models Can be Accurately Pruned Via Chain-of-Thought Reconstruction","created":"2025-09-15","cited_by_count":4,"area":"lr"},{"id":"2510.09595","title":"LiveOIBench: Can Large Language Models Outperform Human Contestants in Informatics Olympiads?","created":"2025-10-10","cited_by_count":4,"area":null},{"id":"2510.11919","title":"LLM Reasoning for Machine Translation: Synthetic Data Generation over Thinking Tokens","created":"2025-10-13","cited_by_count":4,"area":"lr"},{"id":"2604.02721","title":"GrandCode: Achieving Grandmaster Level in Competitive Programming via Agentic Reinforcement Learning","created":"2026-04-03","cited_by_count":4,"area":"agents"},{"id":"2605.24812","title":"CoRe-Code: Collaborative Reinforcement Learning for Code Generation","created":"2026-05-24","cited_by_count":4,"area":null},{"id":"2607.02606","title":"ChainSWE: Benchmarking Coding Agents on Multi-Bug Software Maintenance","created":"2026-07-01","cited_by_count":4,"area":"agents"},{"id":"2507.13337","title":"FormulaOne: Measuring the Depth of Algorithmic Reasoning Beyond Competitive Programming","created":"2025-07-17","cited_by_count":3,"area":null},{"id":"2509.17489","title":"MapCoder-Lite: Distilling Multi-Agent Coding into a Single Small LLM","created":"2025-09-22","cited_by_count":3,"area":"agents"},{"id":"2601.20615","title":"DRAINCODE: Stealthy Energy Consumption Attacks on Retrieval-Augmented Code Generation via Context Poisoning","created":"2026-01-28","cited_by_count":3,"area":"rag"},{"id":"2605.15301","title":"Solvita: Enhancing Large Language Models for Competitive Programming via Agentic Evolution","created":"2026-05-14","cited_by_count":3,"area":"agents"},{"id":"2605.17333","title":"Leveraging Error Diversity in Group Rollouts for Reinforcement Learning","created":"2026-05-17","cited_by_count":3,"area":"lr"},{"id":"2503.06885","title":"ProBench: Judging Multimodal Foundation Models on Open-ended Multi-domain Expert Tasks","created":"2025-03-10","cited_by_count":2,"area":null},{"id":"2510.06101","title":"The Valley of Code Reasoning: Scaling Knowledge Distillation of Large Language Models","created":"2025-10-07","cited_by_count":2,"area":"lr"},{"id":"2601.12019","title":"Acting Flatterers via LLMs Sycophancy: Combating Clickbait with LLMs Opposing-Stance Reasoning","created":"2026-01-17","cited_by_count":2,"area":"lr"},{"id":"2602.06486","title":"JADE: Expert-Grounded Dynamic Evaluation for Open-Ended Professional Tasks","created":"2026-02-06","cited_by_count":2,"area":"agents"},{"id":"2604.10182","title":"Credit-Budgeted ICPC-Style Coding: When Agents Must Pay for Every Decision","created":"2026-04-11","cited_by_count":2,"area":"agents"},{"id":"2606.12864","title":"Beyond Problem Solving: UOJ-Bench for Evaluating Code Generation, Hacking, and Repair in Competitive Programming","created":"2026-06-11","cited_by_count":2,"area":null},{"id":"2607.18859","title":"PhoenixRepair: Rethinking Repair Strategy Exploration in Software Agents","created":"2026-07-21","cited_by_count":2,"area":"lr"},{"id":"2608.00355","title":"CurveShift: Is Agent Progress Scalar? Separating Level from Shape","created":"2026-07-31","cited_by_count":2,"area":"agents"},{"id":"2609.15309","title":"When Agents Slow Down: Understanding LLM Agents' Test-Time Strategies via Elo-per-token Analysis","created":"2026-09-14","cited_by_count":2,"area":"lr"},{"id":"2503.07884","title":"LLMIA: An Out-of-the-Box Index Advisor via In-Context Learning with LLMs","created":"2025-03-10","cited_by_count":1,"area":null},{"id":"2506.13841","title":"LocationReasoner: Evaluating LLMs on Real-World Site Selection Reasoning","created":"2025-06-16","cited_by_count":1,"area":"lr"},{"id":"2507.03162","title":"MateInfoUB: A Real-World Benchmark for Testing LLMs in Competitive, Multilingual, and Multimodal Educational Tasks","created":"2025-07-03","cited_by_count":1,"area":null},{"id":"2509.03537","title":"AR$^2$: Adversarial Reinforcement Learning for Abstract Reasoning in Large Language Models","created":"2025-08-27","cited_by_count":1,"area":"lr"},{"id":"2509.23510","title":"Model Consistency as a Cheap yet Predictive Proxy for LLM Elo Scores","created":"2025-09-27","cited_by_count":1,"area":null},{"id":"2510.17868","title":"UniCode: Augmenting Evaluation for Code Reasoning","created":"2025-10-16","cited_by_count":1,"area":"lr"},{"id":"2510.18895","title":"CosmoCore Affective Dream-Replay Reinforcement Learning for Code Generation","created":"2025-10-20","cited_by_count":1,"area":null},{"id":"2601.17421","title":"Oops, Wait: Discourse Tokens Matter in Reasoning Model","created":"2026-01-24","cited_by_count":1,"area":"lr"},{"id":"2603.07927","title":"SWE-Fuse: Empowering Software Agents via Issue-free Trajectory Learning and Entropy-aware RLVR Training","created":"2026-03-09","cited_by_count":1,"area":"agents"},{"id":"2604.12162","title":"AlphaEval: Evaluating Agents in Production","created":"2026-04-14","cited_by_count":1,"area":"agents"},{"id":"2605.07307","title":"Rethinking Dense Sequential Chains: Reasoning Language Models Can Extract Answers from Sparse, Order-Shuffling Chain-of-Thoughts","created":"2026-05-08","cited_by_count":1,"area":"lr"},{"id":"2606.13982","title":"Adaptive Nucleus Truncation for Long-Form Reasoning","created":"2026-06-12","cited_by_count":1,"area":null},{"id":"2607.22098","title":"Reasoning Denoiser: Denoising Reasoning Traces for Hallucination Detection in Large Reasoning Models","created":"2026-07-24","cited_by_count":1,"area":"lr"},{"id":"2609.15983","title":"Stellar Colosseum: A Many-Agent Harness for Long-Horizon Research in Mathematics and Theoretical Computer Science","created":"2026-09-14","cited_by_count":1,"area":"agents"},{"id":"2609.17943","title":"ASPIRE: Asynchronous Batched Self-Speculative Decoding for Long-Context LLM Inference","created":"2026-09-16","cited_by_count":1,"area":"inference"},{"id":"2506.07064","title":"Com$^2$: A Causal-Guided Benchmark for Exploring Complex Commonsense Reasoning in Large Language Models","created":"2025-06-08","cited_by_count":0,"area":"lr"},{"id":"2509.04442","title":"Delta Activations: A Representation for Finetuned Large Language Models","created":"2025-09-04","cited_by_count":0,"area":null},{"id":"2512.21010","title":"LLM Swiss Round: Aggregating Multi-Benchmark Performance via Competitive Swiss-System Dynamics","created":"2025-12-24","cited_by_count":0,"area":null},{"id":"2602.11674","title":"Benchmark Health Index: A Systematic Framework for Benchmarking the Benchmarks of LLMs","created":"2026-02-12","cited_by_count":0,"area":null},{"id":"2603.13761","title":"Level Up: Defining and Exploiting Transitional Problems for Curriculum Learning","created":"2026-03-14","cited_by_count":0,"area":null}],"next_cursor":"100"}