5 papers
EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective
Yuyao Wang, Zhongjian Zhang, Mo Chi +7
Recent benchmarks for Large Language Model (LLM) agents mainly evaluate reasoning, planning, and execution. However, memory is also essential for agents, as it enables them to stor…
CP-Agent: A Calibrated Risk-Controlled Agent for Feedback-Driven Competitive Programming
Peisong Wang, Bowen Liu, Zehua Li +4
Large language models still struggle with contest-level programming, while many agentic remedies rely on massive inference-time sampling or expensive multi-stage post-training. We…
What Papers Don't Tell You: Recovering Tacit Knowledge for Automated Paper Reproduction
Lehui Li, Ruining Wang, Haochen Song +8
Automated paper reproduction -- generating executable code from academic papers -- is bottlenecked not by information retrieval but by the tacit knowledge that papers inevitably le…
NPG-Muse: Scaling Long Chain-of-Thought Reasoning with NP-Hard Graph Problems
Yuyao Wang, Bowen Liu, Jianheng Tang +6
Reasoning Large Language Models (RLLMs) have recently achieved remarkable progress on complex reasoning tasks, largely enabled by their long chain-of-thought (Long CoT) capabilitie…
AlgBench: To What Extent Do Large Reasoning Models Understand Algorithms?
Henan Sun, Kaichi Yu, Yuyao Wang +5
Reasoning ability has become a central focus in the advancement of Large Reasoning Models (LRMs). Although notable progress has been achieved on several reasoning benchmarks such a…