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20152026
most citedOpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

71 citations · 415 across the 48 of their papers we have counts for

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9 papers · 1 filter

cs.CV2024

GenEARL: A Training-Free Generative Framework for Multimodal Event Argument Role Labeling

Hritik Bansal, Po-Nien Kung, P. Jeffrey Brantingham +2

Multimodal event argument role labeling (EARL), a task that assigns a role for each event participant (object) in an image is a complex challenge. It requires reasoning over the en…

cs.CV2023★ 71 cited

OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models

Anas Awadalla, Irena Gao, Josh Gardner +13

We introduce OpenFlamingo, a family of autoregressive vision-language models ranging from 3B to 9B parameters. OpenFlamingo is an ongoing effort to produce an open-source replicati…

cs.CV2023★ 1 cited

FunQA: Towards Surprising Video Comprehension

Binzhu Xie, Sicheng Zhang, Zitang Zhou +5

Surprising videos, such as funny clips, creative performances, or visual illusions, attract significant attention. Enjoyment of these videos is not simply a response to visual stim…

cs.CV2023★ 17 cited

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…

cs.CV2023★ 4 cited

Breaking Common Sense: WHOOPS! A Vision-and-Language Benchmark of Synthetic and Compositional Images

Nitzan Bitton-Guetta, Yonatan Bitton, Jack Hessel +4

Weird, unusual, and uncanny images pique the curiosity of observers because they challenge commonsense. For example, an image released during the 2022 world cup depicts the famous…

cs.CV2022

The Abduction of Sherlock Holmes: A Dataset for Visual Abductive Reasoning

Jack Hessel, Jena D. Hwang, Jae Sung Park +5

Humans have remarkable capacity to reason abductively and hypothesize about what lies beyond the literal content of an image. By identifying concrete visual clues scattered through…

cs.CV2022

MERLOT Reserve: Neural Script Knowledge through Vision and Language and Sound

Rowan Zellers, Jiasen Lu, Ximing Lu +7

As humans, we navigate a multimodal world, building a holistic understanding from all our senses. We introduce MERLOT Reserve, a model that represents videos jointly over time -- t…

cs.CV2021★ 54 cited

MERLOT: Multimodal Neural Script Knowledge Models

Rowan Zellers, Ximing Lu, Jack Hessel +5

As humans, we understand events in the visual world contextually, performing multimodal reasoning across time to make inferences about the past, present, and future. We introduce M…

cs.CV2021★ 2 cited

CLIPScore: A Reference-free Evaluation Metric for Image Captioning

Jack Hessel, Ari Holtzman, Maxwell Forbes +2

Image captioning has conventionally relied on reference-based automatic evaluations, where machine captions are compared against captions written by humans. This is in contrast to…