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20232026
most citedWeb Retrieval Agents for Evidence-Based Misinformation Detection

2 citations · 7 across the 10 of their papers we have counts for

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Showing 2024Show all

5 papers · 1 filter

cs.CL2024★ 1 cited

Epistemic Integrity in Large Language Models

Bijean Ghafouri, Shahrad Mohammadzadeh, James Zhou +8

Large language models are increasingly relied upon as sources of information, but their propensity for generating false or misleading statements with high confidence poses risks fo…

cs.SI2024

A Guide to Misinformation Detection Data and Evaluation

Camille Thibault, Jacob-Junqi Tian, Gabrielle Peloquin-Skulski +7

Misinformation is a complex societal issue, and mitigating solutions are difficult to create due to data deficiencies. To address this, we have curated the largest collection of (m…

cs.IR2024★ 2 cited

Web Retrieval Agents for Evidence-Based Misinformation Detection

Jacob-Junqi Tian, Hao Yu, Yury Orlovskiy +7

This paper develops an agent-based automated fact-checking approach for detecting misinformation. We demonstrate that combining a powerful LLM agent, which does not have access to…

cs.LG2024

Filtered not Mixed: Stochastic Filtering-Based Online Gating for Mixture of Large Language Models

Raeid Saqur, Anastasis Kratsios, Florian Krach +5

We propose MoE-F - a formalized mechanism for combining pre-trained Large Language Models (LLMs) for online time-series prediction by adaptively forecasting the best weighting…

cs.CL2024

Template-Based Probes Are Imperfect Lenses for Counterfactual Bias Evaluation in LLMs

Farnaz Kohankhaki, D. B. Emerson, Jacob-Junqi Tian +2

Bias in large language models (LLMs) has many forms, from overt discrimination to implicit stereotypes. Counterfactual bias evaluation is a widely used approach to quantifying bias…