1 citations · 1 across the 12 of their papers we have counts for
13 papers
Rethinking RAG in Long Videos: What to Retrieve and How to Use It?
Yuho Lee, Jisu Shin, Nicole Hee-Yeon Kim +5
Retrieval-augmented generation is extending beyond text to long videos, where query-relevant chunks can be represented across multiple modalities and temporal granularities. Progre…
Social Dynamics as Critical Vulnerabilities that Undermine Objective Decision-Making in LLM Collectives
Changgeon Ko, Jisu Shin, Hoyun Song +3
Large language model (LLM) agents are increasingly acting as human delegates in multi-agent environments, where a representative agent integrates diverse peer perspectives to make…
Beyond Static Benchmarks: Synthesizing Harmful Content via Persona-based Simulation for Robust Evaluation
Huije Lee, Jisu Shin, Hoyun Song +2
Static benchmarks for harmful content detection face limitations in scalability and diversity, and may also be affected by contamination from web-scale pre-training corpora. To add…
MentalBench: A DSM-Grounded Benchmark for Evaluating Psychiatric Diagnostic Capability of Large Language Models
Hoyun Song, Migyeong Kang, Jisu Shin +7
Large language models (LLMs) have attracted growing interest as supportive tools for psychiatric assessment and clinical decision support. However, existing mental health benchmark…
RoleConflictBench: A Benchmark of Role Conflict Scenarios for Evaluating LLMs' Contextual Sensitivity
Jisu Shin, Hoyun Song, Juhyun Oh +4
People often encounter role conflicts -- social dilemmas where the expectations of multiple roles clash and cannot be simultaneously fulfilled. As large language models (LLMs) incr…
CulTrace: Tracing Internal Cultural Reasoning in Large Language Models
Haeun Yu, Arnav Arora, Seogyeong Jeong +7
The growing deployment of large language models (LLMs) across diverse cultural contexts necessitates a deeper understanding of models' hidden representations of different cultures.…
Spotting Out-of-Character Behavior: Atomic-Level Evaluation of Persona Fidelity in Open-Ended Generation
Jisu Shin, Juhyun Oh, Eunsu Kim +2
Ensuring persona fidelity in large language models (LLMs) is essential for maintaining coherent and engaging human-AI interactions. However, LLMs often exhibit Out-of-Character (OO…
Does Rationale Quality Matter? Enhancing Mental Disorder Detection via Selective Reasoning Distillation
Hoyun Song, Huije Lee, Jisu Shin +3
The detection of mental health problems from social media and the interpretation of these results have been extensively explored. Research has shown that incorporating clinical sym…
Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach
Changgeon Ko, Jisu Shin, Hoyun Song +2
Large language models (LLMs) often reflect real-world biases, leading to efforts to mitigate these effects and make the models unbiased. Achieving this goal requires defining clear…
Towards Effective Counter-Responses: Aligning Human Preferences with Strategies to Combat Online Trolling
Huije Lee, Hoyun Song, Jisu Shin +3
Trolling in online communities typically involves disruptive behaviors such as provoking anger and manipulating discussions, leading to a polarized atmosphere and emotional distres…
Ask LLMs Directly, "What shapes your bias?": Measuring Social Bias in Large Language Models
Jisu Shin, Hoyun Song, Huije Lee +2
Social bias is shaped by the accumulation of social perceptions towards targets across various demographic identities. To fully understand such social bias in large language models…
A Simple and Flexible Modeling for Mental Disorder Detection by Learning from Clinical Questionnaires
Hoyun Song, Jisu Shin, Huije Lee +1
Social media is one of the most highly sought resources for analyzing characteristics of the language by its users. In particular, many researchers utilized various linguistic feat…
ELF22: A Context-based Counter Trolling Dataset to Combat Internet Trolls
Huije Lee, Young Ju NA, Hoyun Song +2
Online trolls increase social costs and cause psychological damage to individuals. With the proliferation of automated accounts making use of bots for trolling, it is difficult for…