Papers by Adel Ahmadyan

2 papers
SymPyBench: A Dynamic Benchmark for Scientific Reasoning with Executable Python Code (2026.eacl-industry)

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Challenge: Existing benchmarks do not capture the complexity of structured, step-by-step reasoning essential in physics and related domains.
Approach: They propose a large-scale synthetic benchmark of 15K university-level physics problems . they use structured, step-by-step reasoning and executable Python code to produce the ground-truth solution.
Outcome: The proposed model is based on a set of 15K university-level physics problems with three question types.
VideoMind: Thinking in Steps for Long Video Understanding (2026.eacl-industry)

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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.

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