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cs.CV2024
Multimodal Task Vectors Enable Many-Shot Multimodal In-Context Learning
Brandon Huang, Chancharik Mitra, Assaf Arbelle +3
The recent success of interleaved Large Multimodal Models (LMMs) in few-shot learning suggests that in-context learning (ICL) with many examples can be promising for learning new t…
cs.CV2024
ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs
Irene Huang, Wei Lin, M. Jehanzeb Mirza +11
Compositional Reasoning (CR) entails grasping the significance of attributes, relations, and word order. Recent Vision-Language Models (VLMs), comprising a visual encoder and a Lar…
cs.CV2024
TraveLER: A Modular Multi-LMM Agent Framework for Video Question-Answering
Chuyi Shang, Amos You, Sanjay Subramanian +2
Recently, image-based Large Multimodal Models (LMMs) have made significant progress in video question-answering (VideoQA) using a frame-wise approach by leveraging large-scale pret…