Papers by Dasol Choi
What Users Leave Unsaid: Under-Specified Queries Limit Vision-Language Models (2026.findings-acl)
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Dasol Choi, Guijin Son, Hanwool Lee, Minhyuk Kim, Hyunwoo Ko, Teabin Lim, Eungyeol Ahn, Jungwhan Kim, Seunghyeok Hong, Youngsook Song
| Challenge: | HAERAE-Vision benchmarks feature clear, explicit prompts but are often informal and underspecified . state-of-the-art models achieve under 50% on original queries, compared to GPT-5 and Gemini 2.5 Pro . |
| Approach: | They propose a benchmark of 653 real-world visual questions from Korean online communities . they find that even state-of-the-art models achieve under 50% on original queries . |
| Outcome: | HAERAE-Vision benchmarks from Korean online communities yield 1,306 query variants . state-of-the-art models achieve under 50% on original queries, compared with smaller models . authors show that query explicitation alone yields 8 to 22 point improvements . |
COMPASS: A Framework for Evaluating Organization-Specific Policy Alignment in LLMs (2026.acl-long)
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Dasol Choi, DongGeon Lee, Brigitta Jesica Kartono, Helena Berndt, Taeyoun Kwon, Joonwon Jang, Haon Park, Hwanjo Yu, Minsuk Kahng
| Challenge: | Large language models are being rapidly adopted across a wide range of domains, including healthcare, finance, and the public sector. |
| Approach: | They propose a framework to evaluate whether large language models comply with policies . they apply COMPASS to eight diverse industry scenarios to validate models . |
| Outcome: | The proposed framework evaluates whether LLMs comply with allowlist and denylist policies. |