11 citations · 13 across the 2 of their papers we have counts for
9 papers · 1 filter
Measuring Sycophancy of Language Models in Multi-turn Dialogues
Jiseung Hong, Grace Byun, Seungone Kim +2
Large Language Models (LLMs) are expected to provide helpful and harmless responses, yet they often exhibit sycophancy--conforming to user beliefs regardless of factual accuracy or…
CRADLE Bench: A Clinician-Annotated Benchmark for Multi-Faceted Mental Health Crisis and Safety Risk Detection
Grace Byun, Rebecca Lipschutz, Sean T. Minton +2
Detecting mental health crisis situations such as suicide ideation, rape, domestic violence, child abuse, and sexual harassment is a critical yet underexplored challenge for langua…
D-GEN: Automatic Distractor Generation and Evaluation for Reliable Assessment of Generative Model
Grace Byun, Jinho D. Choi
Evaluating generative models with open-ended generation is challenging due to inconsistencies in response formats. Multiple-choice (MC) evaluation mitigates this issue, but generat…
How does a Language-Specific Tokenizer affect LLMs?
Jean Seo, Jaeyoon Kim, SungJoo Byun +1
The necessity of language-specific tokenizers intuitively appears crucial for effective natural language processing, yet empirical analyses on their significance and underlying rea…
ManWav: The First Manchu ASR Model
Jean Seo, Minha Kang, Sungjoo Byun +1
This study addresses the widening gap in Automatic Speech Recognition (ASR) research between high resource and extremely low resource languages, with a particular focus on Manchu,…
A Study on How Attention Scores in the BERT Model are Aware of Lexical Categories in Syntactic and Semantic Tasks on the GLUE Benchmark
Dongjun Jang, Sungjoo Byun, Hyopil Shin
This study examines whether the attention scores between tokens in the BERT model significantly vary based on lexical categories during the fine-tuning process for downstream tasks…