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cs.LG2026
Maximizing Mutual Information Between Prompt and Response Improves LLM Performance With No Additional Data
Hyunji Nam, Haoran Li, Natasha Jaques
While post-training has successfully improved large language models (LLMs) across a variety of domains, these gains heavily rely on human-labeled data or external verifiers. Existi…
cs.LG2025
Learning to summarize user information for personalized reinforcement learning from human feedback
Hyunji Nam, Yanming Wan, Mickel Liu +3
As everyday use cases of large language model (LLM) AI assistants have expanded, it is becoming increasingly important to personalize responses to align to different users' prefere…