3 papers
cs.HC2026
Dark and Bright Side of Participatory Red-Teaming with Targets of Stereotyping for Eliciting Harmful Behaviors from Large Language Models
Sieun Kim, Yeeun Jo, Sungmin Na +5
Red-teaming, where adversarial prompts are crafted to expose harmful behaviors and assess risks, offers a dynamic approach to surfacing underlying stereotypical bias in large langu…
cs.AI2025
AssurAI: Experience with Constructing Korean Socio-cultural Datasets to Discover Potential Risks of Generative AI
Chae-Gyun Lim, Seung-Ho Han, EunYoung Byun +51
The rapid evolution of generative AI necessitates robust safety evaluations. However, current safety datasets are predominantly English-centric, failing to capture specific risks i…
cs.CY2025
PANORAMA: A Dataset and Benchmarks Capturing Decision Trails and Rationales in Patent Examination
Hyunseung Lim, Sooyohn Nam, Sungmin Na +7
Patent examination remains an ongoing challenge in the NLP literature even after the advent of large language models (LLMs), as it requires an extensive yet nuanced human judgment…