Papers by Jungwhan Kim

1 papers
What Users Leave Unsaid: Under-Specified Queries Limit Vision-Language Models (2026.findings-acl)

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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 .

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