5 citations · 9 across the 21 of their papers we have counts for
5 papers · 1 filter
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…
Topic Coverage-based Demonstration Retrieval for In-Context Learning
Wonbin Kweon, SeongKu Kang, Runchu Tian +3
The effectiveness of in-context learning relies heavily on selecting demonstrations that provide all the necessary information for a given test input. To achieve this, it is crucia…
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…
On the Effectiveness of Integration Methods for Multimodal Dialogue Response Retrieval
Seongbo Jang, Seonghyeon Lee, Dongha Lee +1
Multimodal chatbots have become one of the major topics for dialogue systems in both research community and industry. Recently, researchers have shed light on the multimodality of…
Verbosity-Aware Rationale Reduction: Effective Reduction of Redundant Rationale via Principled Criteria
Joonwon Jang, Jaehee Kim, Wonbin Kweon +2
Large Language Models (LLMs) rely on generating extensive intermediate reasoning units (e.g., tokens, sentences) to enhance final answer quality across a wide range of complex task…