66 citations · 134 across the 12 of their papers we have counts for
7 papers · 1 filter
HoneyBee: Data Recipes for Vision-Language Reasoners
Hritik Bansal, Devendra Singh Sachan, Kai-Wei Chang +4
Recent advances in vision-language models (VLMs) have made them highly effective at reasoning tasks. However, the principles underlying the construction of performant VL reasoning…
LaViDa: A Large Diffusion Language Model for Multimodal Understanding
Shufan Li, Konstantinos Kallidromitis, Hritik Bansal +7
Modern Vision-Language Models (VLMs) can solve a wide range of tasks requiring visual reasoning. In real-world scenarios, desirable properties for VLMs include fast inference and c…
VideoPhy-2: A Challenging Action-Centric Physical Commonsense Evaluation in Video Generation
Hritik Bansal, Clark Peng, Yonatan Bitton +3
Large-scale video generative models, capable of creating realistic videos of diverse visual concepts, are strong candidates for general-purpose physical world simulators. However,…
VideoPhy: Evaluating Physical Commonsense for Video Generation
Hritik Bansal, Zongyu Lin, Tianyi Xie +7
Recent advances in internet-scale video data pretraining have led to the development of text-to-video generative models that can create high-quality videos across a broad range of…
TALC: Time-Aligned Captions for Multi-Scene Text-to-Video Generation
Hritik Bansal, Yonatan Bitton, Michal Yarom +3
Most of these text-to-video (T2V) generative models often produce single-scene video clips that depict an entity performing a particular action (e.g., 'a red panda climbing a tree'…
VideoCon: Robust Video-Language Alignment via Contrast Captions
Hritik Bansal, Yonatan Bitton, Idan Szpektor +2
Despite being (pre)trained on a massive amount of data, state-of-the-art video-language alignment models are not robust to semantically-plausible contrastive changes in the video c…
MathVista: Evaluating Mathematical Reasoning of Foundation Models in Visual Contexts
Pan Lu, Hritik Bansal, Tony Xia +7
Large Language Models (LLMs) and Large Multimodal Models (LMMs) exhibit impressive problem-solving skills in many tasks and domains, but their ability in mathematical reasoning in…