9 papers
Building a Precise Video Language with Human-AI Oversight
Zhiqiu Lin, Chancharik Mitra, Siyuan Cen +13
Video-language models (VLMs) learn to reason about the dynamic visual world through natural language. We introduce a suite of open datasets, benchmarks, and recipes for scalable ov…
TimeBlind: A Spatio-Temporal Compositionality Benchmark for Video LLMs
Baiqi Li, Kangyi Zhao, Ce Zhang +3
Fine-grained spatio-temporal understanding is essential for video reasoning and embodied AI. Yet, while Multimodal Large Language Models (MLLMs) master static semantics, their gras…
Mechanistic Finetuning of Vision-Language-Action Models via Few-Shot Demonstrations
Chancharik Mitra, Yusen Luo, Raj Saravanan +7
Vision-Language Action (VLAs) models promise to extend the remarkable success of vision-language models (VLMs) to robotics. Yet, unlike VLMs in the vision-language domain, VLAs for…
EduMod-LLM: A Modular Approach for Designing Flexible and Transparent Educational Assistants
Meenakshi Mittal, Rishi Khare, Mihran Miroyan +2
With the growing use of Large Language Model (LLM)-based Question-Answering (QA) systems in education, it is critical to evaluate their performance across individual pipeline compo…
Less is More Tokens: Efficient Math Reasoning via Difficulty-Aware Chain-of-Thought Distillation
Abdul Waheed, Chancharik Mitra, Laurie Z. Wang +2
Chain-of-thought reasoning, while powerful, can produce unnecessarily verbose output for simpler problems. We present a framework for difficulty-aware reasoning that teaches models…
Towards Understanding Camera Motions in Any Video
Zhiqiu Lin, Siyuan Cen, Daniel Jiang +12
We introduce CameraBench, a large-scale dataset and benchmark designed to assess and improve camera motion understanding. CameraBench consists of ~3,000 diverse internet videos, an…