Key papers

• RSIBench-Data: Benchmarking Data-Centric Research for Recursive Self-Improvement (2026)
  Fanqing Meng et al.
  4.39
• AVO: Agentic Variation Operators for Autonomous Evolutionary Search (2026)
  Terry Chen et al.
  4.04
• ABC-Bench: Benchmarking Agentic Backend Coding in Real-World Development (2026)
  Jie Yang et al.
  1.94
• Scaling Small Agents Through Strategy Auctions (2026)
  Lisa Alazraki et al.
  1.94
• ContextBench: A Benchmark for Context Retrieval in Coding Agents (2026)
  Han Li et al.
  1.94
• ISO-Bench: Can Coding Agents Optimize Real-World Inference Workloads? (2026)
  Ayush Nangia et al.
  1.94
• InfoPO: Information-Driven Policy Optimization for User-Centric Agents (2026)
  Fanqi Kong et al.
  1.94
• Code2Math: Can Your Code Agent Effectively Evolve Math Problems Through Exploration? (2026)
  Dadi Guo et al.
  1.94
• ProRL Agent: Rollout-as-a-Service for RL Training of Multi-Turn LLM Agents (2026)
  Hao Zhang et al.
  1.94
• PRBench: End-to-end Paper Reproduction in Physics Research (2026)
  Shi Qiu et al.
  1.94
• HiL-Bench (Human-in-Loop Benchmark): Do Agents Know When to Ask for Help? (2026)
  Mohamed Elfeki et al.
  1.94
• Counting as a minimal probe of language model reliability (2026)
  Tianxiang Dai et al.
  1.94
• AgentKernelArena: Generalization-Aware Benchmarking of GPU Kernel Optimization Agents (2026)
  Sharareh Younesian et al.
  1.94
• SpecBench: Measuring Reward Hacking in Long-Horizon Coding Agents (2026)
  Bingchen Zhao et al.
  1.94
• SABER: Benchmarking Operational Safety of LLM Coding Agents in Stateful Project Workspaces (2026)
  Qi Hu et al.
  1.94
• MLEvolve: A Self-Evolving Framework for Automated Machine Learning Algorithm Discovery (2026)
  Shangheng Du et al.
  1.94
• SWE-INTERACT: Reimagining SWE Benchmarks as User-Driven Long-Horizon Coding Sessions (2026)
  Mohit Raghavendra et al.
  1.94
• Nemotron-Cascade 2: Post-Training LLMs with Cascade RL and Multi-Domain On-Policy Distillation (2026)
  Zhuolin Yang et al.
  1.78
• Search-o1: Agentic Search-Enhanced Large Reasoning Models (2025)
  Xiaoxi Li et al.
  1.28
• Control LLM: Controlled Evolution for Intelligence Retention in LLM (2025)
  Haichao Wei et al.
  1.28
• Phi-4-reasoning Technical Report (2025)
  Marah Abdin et al.
  1.28
• Darwin Godel Machine: Open-Ended Evolution of Self-Improving Agents (2025)
  Jenny Zhang et al.
  1.28
• Co-Evolving LLM Coder and Unit Tester via Reinforcement Learning (2025)
  Yinjie Wang et al.
  1.28
• AutoMind: Adaptive Knowledgeable Agent for Automated Data Science (2025)
  Yixin Ou et al.
  1.28
• Specification Self-Correction: Mitigating In-Context Reward Hacking Through Test-Time Refinement (2025)
  Víctor Gallego
  1.28
• A Survey of Self-Evolving Agents: On Path to Artificial Super Intelligence (2025)
  Huan-ang Gao et al.
  1.28
• Agent Data Protocol: Unifying Datasets for Diverse, Effective Fine-tuning of LLM Agents (2025)
  Yueqi Song et al.
  1.28
• Generalist Foundation Models Are Not Clinical Enough for Hospital Operations (2025)
  Lavender Y. Jiang et al.
  1.28
• From Code Foundation Models to Agents and Applications: A Practical Guide to Code Intelligence (2025)
  Jian Yang et al.
  1.28
• The Llama 3 Herd of Models (2024)
  Abhimanyu Dubey et al.
  —
• CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding Capabilities of CodeLLMs (2024)
  Dung Nguyen Manh et al.
  —
• Hallucinating AI Hijacking Attack: Large Language Models and Malicious Code Recommenders (2024)
  David Noever et al.
  —
• B-STaR: Monitoring and Balancing Exploration and Exploitation in Self-Taught Reasoners (2024)
  Weihao Zeng et al.
  —