Papers by Shubhang Bhatnagar
VideoMind: Thinking in Steps for Long Video Understanding (2026.eacl-industry)
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Shubhang Bhatnagar, Renxiong Wang, Kapil Krishnakumar, Adel Ahmadyan, Zhaojiang Lin, Lambert Mathias, Xin Luna Dong, Babak Damavandi, Narendra Ahuja, Seungwhan Moon
| Challenge: | Multimodal Large Language Models struggle with Long Video Understanding due to their limited context window and the distributed nature of salient information across many redundant frames. |
| Approach: | They propose a training framework that mimics a human reasoning process to train Long Video Understanding models. |
| Outcome: | The proposed framework achieves 77.6% performance on Video MME, LongVideo, and MLVU benchmarks while yielding 5% improvement on Llama 4 Scout. |