7 citations · 23 across the 19 of their papers we have counts for
6 papers · 1 filter
AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy
Jinghang Shi, Xiaoyu Tang, Yang Huang +4
Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…
Learning to Steer: Input-dependent Steering for Multimodal LLMs
Jayneel Parekh, Pegah Khayatan, Mustafa Shukor +3
Steering has emerged as a practical approach to enable post-hoc guidance of LLMs towards enforcing a specific behavior. However, it remains largely underexplored for multimodal LLM…
Scaling Laws for Optimal Data Mixtures
Mustafa Shukor, Louis Bethune, Dan Busbridge +4
Large foundation models are typically trained on data from multiple domains, with the data mixture--the proportion of each domain used--playing a critical role in model performance…
SmolVLA: A Vision-Language-Action Model for Affordable and Efficient Robotics
Mustafa Shukor, Dana Aubakirova, Francesco Capuano +11
Vision-language models (VLMs) pretrained on large-scale multimodal datasets encode rich visual and linguistic knowledge, making them a strong foundation for robotics. Rather than t…
Scaling Laws for Native Multimodal Models
Mustafa Shukor, Enrico Fini, Victor Guilherme Turrisi da Costa +3
Building general-purpose models that can effectively perceive the world through multimodal signals has been a long-standing goal. Current approaches involve integrating separately…
Analyzing Finetuning Representation Shift for Multimodal LLMs Steering
Pegah Khayatan, Mustafa Shukor, Jayneel Parekh +2
Multimodal LLMs (MLLMs) have reached remarkable levels of proficiency in understanding multimodal inputs. However, understanding and interpreting the behavior of such complex model…