activity
20242026
collaborators

7 papers

cs.LG2026

GPTZero: Robust Detection of LLM-Generated Texts

George Alexandru Adam, Alexander Cui, Edwin Thomas +7

While historical considerations surrounding text authenticity revolved primarily around plagiarism, the advent of large language models (LLMs) has introduced a new challenge: disti…

cs.CL2026

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…

cs.SI2025

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.CL2025

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.LG2025

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.IR2024

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…