12 papers
Mendel Gödel Machine: Recursive Self-Improving Coding Agents via Comparative Evolution
Changzhi Liu, Yilun Liu, Sikuan Yan +2
Self-improving coding agents that iteratively rewrite their own source code have demonstrated impressive performance on coding tasks. However, existing solutions generally derive s…
MADA-RL: Multi-Agent Debate-Aware Reinforcement Learning for Parameter-Efficient Reasoning in Compact Models
Martino M. L. Pulici, Cuong Xuan Chu, Evgeny Kharlamov +3
Large language models achieve strong reasoning performance, but often at prohibitive training cost - a challenge that is especially acute for compact models (…
MetaSkill-Evolve: Recursive Self-Improvement of LLM Agents via Two-Timescale Meta-Skill Evolution
Zefeng Wang, Minxi Yan, Jinhe Bi +3
Recent LLM agents tackle increasingly long-horizon, open-ended tasks, and external skills, reusable procedural knowledge supplied to the agent, further extend this capability. Howe…
Behavioral and Representational Evidence of Binomial Ordering Preferences in Large Language Models
Zhiqing Yang, Yilun Liu, Yunpu Ma +2
Large language models (LLMs) can readily reproduce conventional expressions, yet their ability to model gradient frequency distributions remains underexplored. We investigate this…
Memory-R2: Fair Credit Assignment for Long-Horizon Memory-Augmented LLM Agents
Sikuan Yan, Ahmed Bahloul, Ercong Nie +4
Memory-augmented LLM agents enable interactions that extend beyond finite context windows by storing, updating, and reusing information across sessions. However, training such agen…
PyraVid: Hierarchical Multimodal Memory for Long-Horizon Video Reasoning
Sikuan Yan, Sicheng Dong, Haotong Wang +8
Memory has become an increasingly important component of agentic systems, as these systems are expected to reason over long-term experience. However, prior work has largely focused…