2 citations · 3 across the 12 of their papers we have counts for
4 papers · 1 filter
Unleashing Multi-Hop Reasoning Potential in Large Language Models through Repetition of Misordered Context
Sangwon Yu, Ik-hwan Kim, Jongyoon Song +3
Multi-hop reasoning, which requires multi-step reasoning based on the supporting documents within a given context, remains challenging for large language models (LLMs). LLMs often…
Correcting Negative Bias in Large Language Models through Negative Attention Score Alignment
Sangwon Yu, Jongyoon Song, Bongkyu Hwang +7
A binary decision task, like yes-no questions or answer verification, reflects a significant real-world scenario such as where users look for confirmation about the correctness of…
Interactive Text-to-Image Retrieval with Large Language Models: A Plug-and-Play Approach
Saehyung Lee, Sangwon Yu, Junsung Park +2
In this paper, we primarily address the issue of dialogue-form context query within the interactive text-to-image retrieval task. Our methodology, PlugIR, actively utilizes the gen…
Large Language Models are Skeptics: False Negative Problem of Input-conflicting Hallucination
Jongyoon Song, Sangwon Yu, Sungroh Yoon
In this paper, we identify a new category of bias that induces input-conflicting hallucinations, where large language models (LLMs) generate responses inconsistent with the content…