1 citations · 1 across the 12 of their papers we have counts for
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SocioVerse2: A Longitudinal Dynamic Social Simulation Framework under a Human-AI Co-evolutionary Paradigm
Xinnong Zhang, Jiayu Lin, Jia Wang +19
Social simulation offers the social sciences an experimental instrument that the real world cannot supply, and generative agents have transformed it by acting as silicon samples th…
JEPA-Anything: Learning Predictive Models across Different Worlds
Taoyong Cui, Zhongyao Wang, Xinyue Xu +10
World modeling enables intelligence to anticipate consequences, guide interventions, and learn from interaction. Yet predictive models remain domain-specific: can a common learning…
Discovery Foundation Models: Toward Open-Ended Discovery Intelligence
Ling Yang, Zhenfei Yin, Yingcheng Wu
Foundation models have progressed from learning and reasoning over existing knowledge, to increasingly learning through action, tool use, and outcome feedback. We argue that the ne…
Toward Skill-Native LLMs: Skill Entropy for Benchmarking and Training Long-Horizon Reasoning
Yinghui He, Ling Yang, Jiarui Liu +6
Long-horizon reasoning in recent LLMs demands that the model switch between distinct skills inside a reasoning chain, such as first doing a math derivation, then using the result t…
PAST-Bench: Benchmarking the Foundations of Recursive Self-Improvement in Personal Agents
Shuhan Xue, Zixin Ding, Yichen Shen +6
Recursive self-improvement requires agents to turn accumulated experience into better future behavior. Personal AI agents offer a concrete setting for studying this capability beca…
From Word to World: Can Large Language Models be Implicit Text-based World Models?
Yixia Li, Hongru Wang, Jiahao Qiu +7
Agentic reinforcement learning increasingly relies on experience-driven scaling, yet real-world environments remain non-adaptive, limited in coverage, and difficult to scale. World…