152 citations · 276 across the 36 of their papers we have counts for
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cs.AI2026
Foundations of Proactive Agents: Principles, Technical Layers, and Proactivity-Gym
Jio Oh, Seunghyun Do, Young-Jun Lee +2
Proactive LLM agents can turn idle compute into useful support before users ask. Yet even correct work can misread user context, impose review costs, or undermine trust. This work…
cs.AI2026
Preference Data Selection for Mitigating the Alignment Tax in Large Language Models
Minsu Kim, Jianxun Lian, Xing Xie +1
Aligning large language models to human preferences is crucial for real-world deployment but frequently incurs an alignment tax, leading to the catastrophic forgetting of pre-train…
cs.AI2024★ 1 cited
Talking with Tables for Better LLM Factual Data Interactions
Jio Oh, Geon Heo, Seungjun Oh +5
Large Language Models (LLMs) often struggle with requests related to information retrieval and data manipulation that frequently arise in real-world scenarios under multiple condit…