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cs.LG2025
RLAX: Large-Scale, Distributed Reinforcement Learning for Large Language Models on TPUs
Runlong Zhou, Lefan Zhang, Shang-Chen Wu +29
Reinforcement learning (RL) has emerged as the de-facto paradigm for improving the reasoning capabilities of large language models (LLMs). We have developed RLAX, a scalable RL fra…
cs.HC2025
Autonomy Reshapes How Personalization Affects Privacy Concerns and Trust in LLM Agents
Zhiping Zhang, Yi Evie Zhang, Freda Shi +1
LLM agents require personal information for personalization in order to effectively act on users' behalf, but this raises privacy concerns that can discourage data sharing, limitin…
cs.LG2025
CASCADE Your Datasets for Cross-Mode Knowledge Retrieval of Language Models
Runlong Zhou, Yi Zhang
Language models often struggle with cross-mode knowledge retrieval -- the ability to access knowledge learned in one format (mode) when queried in another. We demonstrate that mode…