32 citations · 64 across the 8 of their papers we have counts for
8 papers · 1 filter
ModelCitizens: Representing Community Voices in Online Safety
Ashima Suvarna, Christina Chance, Karolina Naranjo +4
Automatic toxic language detection is critical for creating safe, inclusive online spaces. However, it is a highly subjective task, with perceptions of toxic language shaped by com…
Language Models' Factuality Depends on the Language of Inquiry
Tushar Aggarwal, Kumar Tanmay, Ayush Agrawal +3
Multilingual language models (LMs) are expected to recall factual knowledge consistently across languages, yet they often fail to transfer knowledge between languages even when the…
Teaching Language Models to Hallucinate Less with Synthetic Tasks
Erik Jones, Hamid Palangi, Clarisse Simões +5
Large language models (LLMs) frequently hallucinate on abstractive summarization tasks such as document-based question-answering, meeting summarization, and clinical report generat…
Diversity of Thought Improves Reasoning Abilities of LLMs
Ranjita Naik, Varun Chandrasekaran, Mert Yuksekgonul +2
Large language models (LLMs) are documented to struggle in settings that require complex reasoning. Nevertheless, instructing the model to break down the problem into smaller reaso…
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones +5
We investigate the internal behavior of Transformer-based Large Language Models (LLMs) when they generate factually incorrect text. We propose modeling factual queries as constrain…
Orca: Progressive Learning from Complex Explanation Traces of GPT-4
Subhabrata Mukherjee, Arindam Mitra, Ganesh Jawahar +3
Recent research has focused on enhancing the capability of smaller models through imitation learning, drawing on the outputs generated by large foundation models (LFMs). A number o…