collaborators

6 papers

cs.RO2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CV2025

Activation Reward Models for Few-Shot Model Alignment

Tianning Chai, Chancharik Mitra, Brandon Huang +8

Aligning Large Language Models (LLMs) and Large Multimodal Models (LMMs) to human preferences is a central challenge in improving the quality of the models' generative outputs for…

cs.CV2025

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…

cs.CV2024

Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features

Chancharik Mitra, Brandon Huang, Tianning Chai +7

Generative Large Multimodal Models (LMMs) like LLaVA and Qwen-VL excel at a wide variety of vision-language (VL) tasks. Despite strong performance, LMMs' generative outputs are not…