Papers by Wonjeong Ryu
Too Many Frames, Not All Useful: Efficient Strategies for Long-Form Video QA (2026.eacl-long)
Copied to clipboard
| Challenge: | Recent studies leverage large language models (LLMs) in LVQA benchmarks, achieving exceptional performance while relying on vision language models to convert all visual content into natural language. |
| Approach: | They propose a modular and training-free framework that leverages large language models to generate a small subset of informative frames tailored to each question. |
| Outcome: | The proposed framework achieves state-of-the-art performance among similar models across four benchmark LVQA datasets: EgoSchema, NExT-QA, IntentQA, VideoMME. |