3 papers
cs.CL2025
STEPER: Step-wise Knowledge Distillation for Enhancing Reasoning Ability in Multi-Step Retrieval-Augmented Language Models
Kyumin Lee, Minjin Jeon, Sanghwan Jang +1
Answering complex real-world questions requires step-by-step retrieval and integration of relevant information to generate well-grounded responses. However, existing knowledge dist…
cs.CL2025
From What to Respond to When to Respond: Timely Response Generation for Open-domain Dialogue Agents
Seongbo Jang, Minjin Jeon, Jaehoon Lee +3
While research on dialogue response generation has primarily focused on generating coherent responses conditioning on textual context, the critical question of when to respond grou…
cs.CL2024
Rectifying Demonstration Shortcut in In-Context Learning
Joonwon Jang, Sanghwan Jang, Wonbin Kweon +2
Large language models (LLMs) are able to solve various tasks with only a few demonstrations utilizing their in-context learning (ICL) abilities. However, LLMs often rely on their p…