5 papers
Self-Evolving World Models for LLM Agent Planning
Xuan Zhang, Wenxuan Zhang, See-Kiong Ng +1
World models offer a principled way to equip long-horizon LLM agents with foresight: predictions of action consequences before execution. However, unreliable foresight can be ignor…
Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond
Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47
As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a central bottleneck. Agents that ma…
DR-Arena: an Automated Evaluation Framework for Deep Research Agents
Yiwen Gao, Ruochen Zhao, Yang Deng +1
As Large Language Models (LLMs) increasingly operate as Deep Research (DR) Agents capable of autonomous investigation and information synthesis, reliable evaluation of their task p…
Multilingual Agent-Based World Modeling for Social Science
Xuan Zhang, Wenxuan Zhang, Anxu Wang +2
Multi-agent role-playing has recently shown promise for studying social behavior with language agents, but existing simulations are mostly monolingual without cross-lingual interac…
Do LLMs Really Know What They Don't Know? Internal States Mainly Reflect Knowledge Recall Rather Than Truthfulness
Chi Seng Cheang, Hou Pong Chan, Wenxuan Zhang +1
Recent work suggests that LLMs "know what they don't know", positing that hallucinated and factually correct outputs arise from distinct internal processes and can therefore be dis…