56 citations · 175 across the 29 of their papers we have counts for
8 papers · 1 filter
Combining Confidence Elicitation and Sample-based Methods for Uncertainty Quantification in Misinformation Mitigation
Mauricio Rivera, Jean-François Godbout, Reihaneh Rabbany +1
Large Language Models have emerged as prime candidates to tackle misinformation mitigation. However, existing approaches struggle with hallucinations and overconfident predictions.…
Comparing GPT-4 and Open-Source Language Models in Misinformation Mitigation
Tyler Vergho, Jean-Francois Godbout, Reihaneh Rabbany +1
Recent large language models (LLMs) have been shown to be effective for misinformation detection. However, the choice of LLMs for experiments varies widely, leading to uncertain co…
Uncertainty Resolution in Misinformation Detection
Yury Orlovskiy, Camille Thibault, Anne Imouza +3
Misinformation poses a variety of risks, such as undermining public trust and distorting factual discourse. Large Language Models (LLMs) like GPT-4 have been shown effective in mit…
Towards Detecting Contextual Real-Time Toxicity for In-Game Chat
Zachary Yang, Nicolas Grenan-Godbout, Reihaneh Rabbany
Real-time toxicity detection in online environments poses a significant challenge, due to the increasing prevalence of social media and gaming platforms. We introduce ToxBuster, a…
Open, Closed, or Small Language Models for Text Classification?
Hao Yu, Zachary Yang, Kellin Pelrine +2
Recent advancements in large language models have demonstrated remarkable capabilities across various NLP tasks. But many questions remain, including whether open-source models mat…
ToxBuster: In-game Chat Toxicity Buster with BERT
Zachary Yang, Yasmine Maricar, MohammadReza Davari +2
Detecting toxicity in online spaces is challenging and an ever more pressing problem given the increase in social media and gaming consumption. We introduce ToxBuster, a simple and…
Towards Reliable Misinformation Mitigation: Generalization, Uncertainty, and GPT-4
Kellin Pelrine, Anne Imouza, Camille Thibault +5
Misinformation poses a critical societal challenge, and current approaches have yet to produce an effective solution. We propose focusing on generalization, uncertainty, and how to…
The Surprising Performance of Simple Baselines for Misinformation Detection
Kellin Pelrine, Jacob Danovitch, Reihaneh Rabbany
As social media becomes increasingly prominent in our day to day lives, it is increasingly important to detect informative content and prevent the spread of disinformation and unve…