2 citations · 2 across the 6 of their papers we have counts for
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cs.AI2026
OpenTinker: Separating Concerns in Agentic Reinforcement Learning
Siqi Zhu, Jiaxuan You
We introduce \textsc{OpenTinker}, an open infrastructure for training large language model (LLM) agents with many LoRA-backed policies over shared execution resources. Modern agent…
cs.AI2025
GTAlign: Game-Theoretic Alignment of LLM Assistants for Social Welfare
Siqi Zhu, David Zhang, Pedro Cisneros-Velarde +1
Large Language Models (LLMs) have achieved remarkable progress in reasoning, yet sometimes produce responses that are suboptimal for users in tasks such as writing, information see…
cs.AI2025
Multi-Agent Evolve: LLM Self-Improve through Co-evolution
Yixing Chen, Yiding Wang, Siqi Zhu +5
Reinforcement Learning (RL) has demonstrated significant potential in enhancing the reasoning capabilities of large language models (LLMs). However, the success of RL for LLMs heav…