54 citations · 114 across the 17 of their papers we have counts for
5 papers · 1 filter
Localized Symbolic Knowledge Distillation for Visual Commonsense Models
Jae Sung Park, Jack Hessel, Khyathi Raghavi Chandu +8
Instruction following vision-language (VL) models offer a flexible interface that supports a broad range of multimodal tasks in a zero-shot fashion. However, interfaces that operat…
Symbolic Chain-of-Thought Distillation: Small Models Can Also "Think" Step-by-Step
Liunian Harold Li, Jack Hessel, Youngjae Yu +3
Chain-of-thought prompting (e.g., "Let's think step-by-step") primes large language models to verbalize rationalization for their predictions. While chain-of-thought can lead to dr…
CLARA: Classifying and Disambiguating User Commands for Reliable Interactive Robotic Agents
Jeongeun Park, Seungwon Lim, Joonhyung Lee +4
In this paper, we focus on inferring whether the given user command is clear, ambiguous, or infeasible in the context of interactive robotic agents utilizing large language models…
Multimodal C4: An Open, Billion-scale Corpus of Images Interleaved with Text
Wanrong Zhu, Jack Hessel, Anas Awadalla +7
In-context vision and language models like Flamingo support arbitrarily interleaved sequences of images and text as input. This format not only enables few-shot learning via interl…
CHAMPAGNE: Learning Real-world Conversation from Large-Scale Web Videos
Seungju Han, Jack Hessel, Nouha Dziri +2
Visual information is central to conversation: body gestures and physical behaviour, for example, contribute to meaning that transcends words alone. To date, however, most neural c…