7 citations · 14 across the 11 of their papers we have counts for
5 papers · 1 filter
Self-Assessment Reinforcement Learning for Search-State Awareness in Retrieval-Augmented Large Language Models
Taewhoo Lee, Minju Song, Jungwoo Park +6
Recent advances in search agents have enabled large language models to tackle complex tasks by retrieving and synthesizing external information. However, existing search agents oft…
Enhancing Low-Resource Language Reasoning via High-Resource Language Feature Transfer
Minju Song, Hyeon Hwang, Junhyun Lee +1
Large language models exhibit substantial performance variation across languages, even when solving semantically equivalent tasks. Existing analyses often treat this phenomenon as…
TheBioCollection: Unified Pre-Training Scale LLM Corpus for Biology
Hyunjin Seo, Hyeon Hwang, Gyubok Lee +7
The push toward large language models for biology (BioLM) has created a need for training corpora that can endow models with a genuine understanding of biology. However, existing b…
Overview of the MedHopQA track at BioCreative IX: track description, participation and evaluation of systems for multi-hop medical question answering
Rezarta Islamaj, Joey Chan, Robert Leaman +13
Multi-hop question answering (QA) remains a significant challenge in the biomedical domain, requiring systems to integrate information across multiple sources to answer complex que…
Teaching Language Models to Think in Code
Hyeon Hwang, Jiwoo Lee, Jaewoo Kang
Tool-integrated reasoning (TIR) has emerged as a dominant paradigm for mathematical problem solving in language models, combining natural language (NL) reasoning with code executio…