2 citations · 3 across the 5 of their papers we have counts for
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cs.AI2026
State Representation Shapes Long-Horizon Agent Learning and Transfer: An Empirical Study
Dong Nie, Rui Lan, Yixin Nie +1
An end-to-end success rate alone cannot distinguish failure to learn an action from failure to apply it as task state changes. We study this distinction in deterministic tool workf…
cs.AI2026
Paying Less Generalization Tax: A Cross-Domain Generalization Study of RL Training for LLM Agents
Zhihan Liu, Lin Guan, Yixin Nie +6
Generalist LLM agents are often post-trained on a narrow set of environments but deployed across far broader, unseen domains. In this work, we investigate the challenge of agentic…