1 citations · 1 across the 4 of their papers we have counts for
5 papers
EvoComp: Learning Visual Token Compression for Multimodal Large Language Models via Semantic-Guided Evolutionary Labeling
Jiafei Song, Fengwei Zhou, Jin Qu +7
Recent Multimodal Large Language Models (MLLMs) have demonstrated strong performance on vision-language understanding tasks, yet their inference efficiency is often hampered by the…
GLIMPSE : Real-Time Text Recognition and Contextual Understanding for VQA in Wearables
Akhil Ramachandran, Ankit Arun, Ashish Shenoy +8
Video Large Language Models (Video LLMs) have shown remarkable progress in understanding and reasoning about visual content, particularly in tasks involving text recognition and te…
MOOSComp: Improving Lightweight Long-Context Compressor via Mitigating Over-Smoothing and Incorporating Outlier Scores
Fengwei Zhou, Jiafei Song, Wenjin Jason Li +4
Recent advances in large language models have significantly improved their ability to process long-context input, but practical applications are challenged by increased inference t…
EgoQR: Efficient QR Code Reading in Egocentric Settings
Mohsen Moslehpour, Yichao Lu, Pierce Chuang +7
QR codes have become ubiquitous in daily life, enabling rapid information exchange. With the increasing adoption of smart wearable devices, there is a need for efficient, and frict…
Lumos : Empowering Multimodal LLMs with Scene Text Recognition
Ashish Shenoy, Yichao Lu, Srihari Jayakumar +11
We introduce Lumos, the first end-to-end multimodal question-answering system with text understanding capabilities. At the core of Lumos is a Scene Text Recognition (STR) component…