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20212026
most citedDataComp: In search of the next generation of multimodal datasets

74 citations · 209 across the 38 of their papers we have counts for

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Showing 2023Show all

10 papers · 1 filter

cs.CL2023

Mismatch Quest: Visual and Textual Feedback for Image-Text Misalignment

Brian Gordon, Yonatan Bitton, Yonatan Shafir +5

While existing image-text alignment models reach high quality binary assessments, they fall short of pinpointing the exact source of misalignment. In this paper, we present a metho…

cs.CV2023

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…

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.CL2023★ 11 cited

VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use

Yonatan Bitton, Hritik Bansal, Jack Hessel +6

We introduce VisIT-Bench (Visual InsTruction Benchmark), a benchmark for evaluation of instruction-following vision-language models for real-world use. Our starting point is curati…

cs.CV2023★ 1 cited

Read, Look or Listen? What's Needed for Solving a Multimodal Dataset

Netta Madvil, Yonatan Bitton, Roy Schwartz

The prevalence of large-scale multimodal datasets presents unique challenges in assessing dataset quality. We propose a two-step method to analyze multimodal datasets, which levera…

cs.CL2023★ 14 cited

What You See is What You Read? Improving Text-Image Alignment Evaluation

Michal Yarom, Yonatan Bitton, Soravit Changpinyo +5

Automatically determining whether a text and a corresponding image are semantically aligned is a significant challenge for vision-language models, with applications in generative t…

cs.CL2023★ 1 cited

q2d: Turning Questions into Dialogs to Teach Models How to Search

Yonatan Bitton, Shlomi Cohen-Ganor, Ido Hakimi +3

One of the exciting capabilities of recent language models for dialog is their ability to independently search for relevant information to ground a given dialog response. However,…

cs.CV2023★ 74 cited

DataComp: In search of the next generation of multimodal datasets

Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang +31

Multimodal datasets are a critical component in recent breakthroughs such as Stable Diffusion and GPT-4, yet their design does not receive the same research attention as model arch…

cs.CL2023

IRFL: Image Recognition of Figurative Language

Ron Yosef, Yonatan Bitton, Dafna Shahaf

Figures of speech such as metaphors, similes, and idioms are integral parts of human communication. They are ubiquitous in many forms of discourse, allowing people to convey comple…

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…