10 papers
Analogical Deep Research: Retrieving and Integrating Historical Analogies for Foresight Analysis
Yongqiang Chen, Guangyi Chen, Yuewen Sun +1
Systematic comparisons between current situations and structurally similar past events in the historical, i.e., historical analogies, is among the most powerful tools for foresight…
Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling
Fan Feng, Yujia Zheng, Minghao Fu +5
Learning and planning in imagination using world models provides an effective paradigm for training agents for decision-making. However, existing approaches often rely on high-dime…
CausalGame: Benchmarking Causal Thinking of LLM Agents in Games
Zhenhao Chen, Yongqiang Chen, Chenxi Liu +7
Building AI Scientist agents with Large Language Models (LLMs) has recently attracted growing attention. Since scientific discovery fundamentally relies on uncovering causal relati…
CiPO: Counterfactual Unlearning for Large Reasoning Models through Iterative Preference Optimization
Junyi Li, Yongqiang Chen, Ningning Ding
Machine unlearning has gained increasing attention in recent years, as a promising technique to selectively remove unwanted privacy or copyrighted information from Large Language M…
CausalEvolve: Towards Open-Ended Discovery with Causal Scratchpad
Yongqiang Chen, Chenxi Liu, Zhenhao Chen +3
Evolve-based agent such as AlphaEvolve is one of the notable successes in using Large Language Models (LLMs) to build AI Scientists. These agents tackle open-ended scientific probl…
ParamMem: Augmenting Language Agents with Parametric Reflective Memory
Tianjun Yao, Yongqiang Chen, Yujia Zheng +3
Self-reflection enables language agents to iteratively refine solutions, yet often produces repetitive outputs that limit reasoning performance. Recent studies have attempted to ad…