656 citations · 2.6k across the 58 of their papers we have counts for
65 papers
Evidence-Backed Video Question Answering
Shijie Wang, Honglu Zhou, Ziyang Wang +5
Current Video Large Language Models (Video LLMs) excel in question answering (QA) but largely operate as black boxes, providing textual answers without verifiable visual grounding.…
Towards Robust Sequential Decomposition for Complex Image Editing
Zilai Zeng, Mingdeng Cao, Zijie Li +5
Recent advances in visual generative models have enabled high-fidelity image editing guided by human instructions. However, these models often struggle with complex instructions in…
$100K or 100 Days: Trade-offs when Pre-Training with Academic Resources
Apoorv Khandelwal, Tian Yun, Nihal V. Nayak +4
Pre-training is notoriously compute-intensive and academic researchers are notoriously under-resourced. It is, therefore, commonly assumed that academics can't pre-train models. In…
Analyzing Modular Approaches for Visual Question Decomposition
Apoorv Khandelwal, Ellie Pavlick, Chen Sun
Modular neural networks without additional training have recently been shown to surpass end-to-end neural networks on challenging vision-language tasks. The latest such methods sim…
Emergence of Abstract State Representations in Embodied Sequence Modeling
Tian Yun, Zilai Zeng, Kunal Handa +4
Decision making via sequence modeling aims to mimic the success of language models, where actions taken by an embodied agent are modeled as tokens to predict. Despite their promisi…
AntGPT: Can Large Language Models Help Long-term Action Anticipation from Videos?
Qi Zhao, Shijie Wang, Ce Zhang +5
Can we better anticipate an actor's future actions (e.g. mix eggs) by knowing what commonly happens after his/her current action (e.g. crack eggs)? What if we also know the longer-…