12 citations · 12 across the 5 of their papers we have counts for
6 papers · 1 filter
Legibility is Not Interpretability: Comparing Judged and Actual Importance in Chain-Of-Thought Reasoning
Kevin Du, Alexander Hoyle, Laura Ruis +1
Reasoning traces from chain-of-thought models appear to offer a legible window into how a model arrives at its answer. A growing body of work treats them as such, using LLM judges…
Modeling Motivated Reasoning in Law: Evaluating Strategic Role Conditioning in LLM Summarization
Eunjung Cho, Alexander Hoyle, Yoan Hermstrüwer
Large Language Models (LLMs) are increasingly used to generate user-tailored summaries, adapting outputs to specific stakeholders. In legal contexts, this raises important question…
How Persuasive is Your Context?
Tu Nguyen, Kevin Du, Alexander Miserlis Hoyle +1
Two central capabilities of language models (LMs) are: (i) drawing on prior knowledge about entities, which allows them to answer queries such as "What's the official language of A…
Can Reasoning Help Large Language Models Capture Human Annotator Disagreement?
Jingwei Ni, Yu Fan, Vilém Zouhar +6
Variation in human annotation (i.e., disagreements) is common in NLP, often reflecting important information like task subjectivity and sample ambiguity. Modeling this variation is…
Large Language Models Struggle to Describe the Haystack without Human Help: Human-in-the-loop Evaluation of Topic Models
Zongxia Li, Lorena Calvo-Bartolomé, Alexander Hoyle +4
A common use of NLP is to facilitate the understanding of large document collections, with a shift from using traditional topic models to Large Language Models. Yet the effectivene…
TopicGPT: A Prompt-based Topic Modeling Framework
Chau Minh Pham, Alexander Hoyle, Simeng Sun +2
Topic modeling is a well-established technique for exploring text corpora. Conventional topic models (e.g., LDA) represent topics as bags of words that often require "reading the t…