31 citations · 47 across the 3 of their papers we have counts for
4 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…
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…