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cs.LG2026
The Interplay of Harness Design and Post-Training in LLM Agents
Kyungmin Kim, Youngbin Choi, Seoyeon Lee +3
Tool-integrated LLM agents are often wrapped within a harness: the scaffolding that determines which tools are exposed, how they are described, and what auxiliary information accom…
cs.LG2025
CoPL: Collaborative Preference Learning for Personalizing LLMs
Youngbin Choi, Seunghyuk Cho, Minjong Lee +4
Personalizing large language models (LLMs) is important for aligning outputs with diverse user preferences, yet existing methods struggle with flexibility and generalization. We pr…