28 citations · 36 across the 9 of their papers we have counts for
9 papers
KoSBi: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model Application
Hwaran Lee, Seokhee Hong, Joonsuk Park +3
Large language models (LLMs) learn not only natural text generation abilities but also social biases against different demographic groups from real-world data. This poses a critica…
SQuARe: A Large-Scale Dataset of Sensitive Questions and Acceptable Responses Created Through Human-Machine Collaboration
Hwaran Lee, Seokhee Hong, Joonsuk Park +10
The potential social harms that large language models pose, such as generating offensive content and reinforcing biases, are steeply rising. Existing works focus on coping with thi…
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
Jeonghoon Kim, Jung Hyun Lee, Sungdong Kim +4
Large language models (LLMs) face the challenges in fine-tuning and deployment due to their high memory demands and computational costs. While parameter-efficient fine-tuning (PEFT…
Asking Clarification Questions to Handle Ambiguity in Open-Domain QA
Dongryeol Lee, Segwang Kim, Minwoo Lee +4
Ambiguous questions persist in open-domain question answering, because formulating a precise question with a unique answer is often challenging. Previously, Min et al. (2020) have…
Critic-Guided Decoding for Controlled Text Generation
Minbeom Kim, Hwanhee Lee, Kang Min Yoo +3
Steering language generation towards objectives or away from undesired content has been a long-standing goal in utilizing language models (LM). Recent work has demonstrated reinfor…
Masked Summarization to Generate Factually Inconsistent Summaries for Improved Factual Consistency Checking
Hwanhee Lee, Kang Min Yoo, Joonsuk Park +2
Despite the recent advances in abstractive summarization systems, it is still difficult to determine whether a generated summary is factual consistent with the source text. To this…
ClaimDiff: Comparing and Contrasting Claims on Contentious Issues
Miyoung Ko, Ingyu Seong, Hwaran Lee +3
With the growing importance of detecting misinformation, many studies have focused on verifying factual claims by retrieving evidence. However, canonical fact verification tasks do…
Plug-and-Play Adaptation for Continuously-updated QA
Kyungjae Lee, Wookje Han, Seung-won Hwang +3
Language models (LMs) have shown great potential as implicit knowledge bases (KBs). And for their practical use, knowledge in LMs need to be updated periodically. However, existing…
Argument Mining with Structured SVMs and RNNs
Vlad Niculae, Joonsuk Park, Claire Cardie
We propose a novel factor graph model for argument mining, designed for settings in which the argumentative relations in a document do not necessarily form a tree structure. (This…