5 citations · 20 across the 10 of their papers we have counts for
4 papers · 1 filter
FactLens: Benchmarking Fine-Grained Fact Verification
Kushan Mitra, Dan Zhang, Sajjadur Rahman +1
Large Language Models (LLMs) have shown impressive capability in language generation and understanding, but their tendency to hallucinate and produce factually incorrect informatio…
MEGAnno+: A Human-LLM Collaborative Annotation System
Hannah Kim, Kushan Mitra, Rafael Li Chen +2
Large language models (LLMs) can label data faster and cheaper than humans for various NLP tasks. Despite their prowess, LLMs may fall short in understanding of complex, sociocultu…
Reasoning Capacity in Multi-Agent Systems: Limitations, Challenges and Human-Centered Solutions
Pouya Pezeshkpour, Eser Kandogan, Nikita Bhutani +3
Remarkable performance of large language models (LLMs) in a variety of tasks brings forth many opportunities as well as challenges of utilizing them in production settings. Towards…
Characterizing Large Language Models as Rationalizers of Knowledge-intensive Tasks
Aditi Mishra, Sajjadur Rahman, Hannah Kim +2
Large language models (LLMs) are proficient at generating fluent text with minimal task-specific supervision. Yet, their ability to provide well-grounded rationalizations for knowl…