3 papers
cs.IR2026
Group-Aware Adaptive Retrieval for Evidence Navigation
June Park, Jun Kwon, Jonghyo Kim +1
Reasoning-intensive retrieval addresses queries whose relevance cannot be identified by surface-level matching, thereby requiring multi-step reasoning. Because relevant documents r…
cs.CL2025
Conflict-Aware Soft Prompting for Retrieval-Augmented Generation
Eunseong Choi, June Park, Hyeri Lee +1
Retrieval-augmented generation (RAG) enhances the capabilities of large language models (LLMs) by incorporating external knowledge into their input prompts. However, when the retri…
cs.CL2024
From Reading to Compressing: Exploring the Multi-document Reader for Prompt Compression
Eunseong Choi, Sunkyung Lee, Minjin Choi +2
Large language models (LLMs) have achieved significant performance gains using advanced prompting techniques over various tasks. However, the increasing length of prompts leads to…