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20232026
most citedCroissant: A Metadata Format for ML-Ready Datasets

18 citations · 31 across the 14 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CL2024

Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checking

Mubashara Akhtar, Michael Schlichtkrull, Andreas Vlachos

Current automated fact-checking (AFC) approaches typically evaluate evidence either implicitly via the predicted verdicts or through exact matches with predefined closed knowledge…

cs.CL2024

The Automated Verification of Textual Claims (AVeriTeC) Shared Task

Michael Schlichtkrull, Yulong Chen, Chenxi Whitehouse +9

The Automated Verification of Textual Claims (AVeriTeC) shared task asks participants to retrieve evidence and predict veracity for real-world claims checked by fact-checkers. Evid…

cs.IR2024★ 4 cited

A Standardized Machine-readable Dataset Documentation Format for Responsible AI

Nitisha Jain, Mubashara Akhtar, Joan Giner-Miguelez +15

Data is critical to advancing AI technologies, yet its quality and documentation remain significant challenges, leading to adverse downstream effects (e.g., potential biases) in AI…

cs.CL2024

TANQ: An open domain dataset of table answered questions

Mubashara Akhtar, Chenxi Pang, Andreea Marzoca +2

Language models, potentially augmented with tool usage such as retrieval are becoming the go-to means of answering questions. Understanding and answering questions in real-world se…

cs.LG2024★ 18 cited

Croissant: A Metadata Format for ML-Ready Datasets

Mubashara Akhtar, Omar Benjelloun, Costanza Conforti +28

Data is a critical resource for machine learning (ML), yet working with data remains a key friction point. This paper introduces Croissant, a metadata format for datasets that crea…