5 papers · 1 filter
COMMUNITYNOTES: A Dataset for Exploring the Helpfulness of Fact-Checking Explanations
Rui Xing, Preslav Nakov, Timothy Baldwin +1
Fact-checking on major platforms, such as X, Meta, and TikTok, is shifting from expert-driven verification to a community-based setup, where users contribute explanatory notes to c…
Benchmarking Uncertainty Quantification Methods for Large Language Models with LM-Polygraph
Roman Vashurin, Ekaterina Fadeeva, Artem Vazhentsev +12
The rapid proliferation of large language models (LLMs) has stimulated researchers to seek effective and efficient approaches to deal with LLM hallucinations and low-quality output…
LLM-DetectAIve: a Tool for Fine-Grained Machine-Generated Text Detection
Mervat Abassy, Kareem Elozeiri, Alexander Aziz +21
The ease of access to large language models (LLMs) has enabled a widespread of machine-generated texts, and now it is often hard to tell whether a piece of text was human-written o…
Evaluating Evidence Attribution in Generated Fact Checking Explanations
Rui Xing, Timothy Baldwin, Jey Han Lau
Automated fact-checking systems often struggle with trustworthiness, as their generated explanations can include hallucinations. In this work, we explore evidence attribution for f…
Loki: An Open-Source Tool for Fact Verification
Haonan Li, Xudong Han, Hao Wang +7
We introduce Loki, an open-source tool designed to address the growing problem of misinformation. Loki adopts a human-centered approach, striking a balance between the quality of f…