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Found 11 papers, 6 papers with code
PubHealthTab: A Public Health Table-based Dataset for Evidence-based Fact Checking
Inspired by human fact checkers, who use different types of evidence (e. g. tables, images, audio) in addition to text, several datasets with tabular evidence data have been released in recent years.
LEXam: Benchmarking Legal Reasoning on 340 Law Exams
The dataset comprises 4, 886 law exam questions in English and German, including 2, 841 long-form, open-ended questions and 2, 045 multiple-choice questions.
AILuminate: Introducing v1.0 of the AI Risk and Reliability Benchmark from MLCommons
This work represents a crucial step toward establishing global standards for AI risk and reliability evaluation while acknowledging the need for continued development in areas such as multiturn interactions, multimodal understanding, coverage of additional languages, and emerging hazard categories.
Ev2R: Evaluating Evidence Retrieval in Automated Fact-Checking
Current automated fact-checking (AFC) approaches commonly evaluate evidence either implicitly via the predicted verdicts or by comparing retrieved evidence with a predefined closed knowledge source, such as Wikipedia.
The Automated Verification of Textual Claims (AVeriTeC) Shared Task
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.
TANQ: An open domain dataset of table answered questions
Language models, potentially augmented with tool usage such as retrieval are becoming the go-to means of answering questions.
Croissant: A Metadata Format for ML-Ready Datasets
Data is a critical resource for machine learning (ML), yet working with data remains a key friction point.
ChartCheck: Explainable Fact-Checking over Real-World Chart Images
Whilst fact verification has attracted substantial interest in the natural language processing community, verifying misinforming statements against data visualizations such as charts has so far been overlooked.
Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data
Thus, understanding and reasoning with numbers are essential skills for language models to solve different tasks.
Multimodal Automated Fact-Checking: A Survey
In this survey, we conceptualise a framework for AFC including subtasks unique to multimodal misinformation.
Reading and Reasoning over Chart Images for Evidence-based Automated Fact-Checking
Evidence data for automated fact-checking (AFC) can be in multiple modalities such as text, tables, images, audio, or video.
