64 citations · 84 across the 18 of their papers we have counts for
18 papers
Artificial Impressions: Evaluating Large Language Model Behavior Through the Lens of Trait Impressions
Nicholas Deas, Kathleen McKeown
We introduce and study artificial impressions--patterns in LLMs' internal representations of prompts that resemble human impressions and stereotypes based on language. We fit linea…
Exploring Chain-of-Thought Reasoning for Steerable Pluralistic Alignment
Yunfan Zhang, Kathleen McKeown, Smaranda Muresan
Large Language Models (LLMs) are typically trained to reflect a relatively uniform set of values, which limits their applicability to tasks that require understanding of nuanced hu…
Mining Contextualized Visual Associations from Images for Creativity Understanding
Ananya Sahu, Amith Ananthram, Kathleen McKeown
Understanding another person's creative output requires a shared language of association. However, when training vision-language models such as CLIP, we rely on web-scraped dataset…
ModelingAgent: Bridging LLMs and Mathematical Modeling for Real-World Challenges
Cheng Qian, Hongyi Du, Hongru Wang +6
Recent progress in large language models (LLMs) has enabled substantial advances in solving mathematical problems. However, existing benchmarks often fail to reflect the complexity…
DYSTIL: Dynamic Strategy Induction with Large Language Models for Reinforcement Learning
Borui Wang, Kathleen McKeown, Rex Ying
Reinforcement learning from expert demonstrations has long remained a challenging research problem, and existing state-of-the-art methods using behavioral cloning plus further RL t…
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Liyan Tang, Igor Shalyminov, Amy Wing-mei Wong +11
Single document news summarization has seen substantial progress on faithfulness in recent years, driven by research on the evaluation of factual consistency, or hallucinations. We…