1 citations · 1 across the 6 of their papers we have counts for
6 papers
Factuality on Demand: Controlling the Factuality-Informativeness Trade-off in Text Generation
Ziwei Gong, Yanda Chen, Julia Hirschberg +4
Large language models (LLMs) encode knowledge with varying degrees of confidence. When responding to queries, models face an inherent trade-off: they can generate responses that ar…
Story Ribbons: Reimagining Storyline Visualizations with Large Language Models
Catherine Yeh, Tara Menon, Robin Singh Arya +4
Analyzing literature involves tracking interactions between characters, locations, and themes. Visualization has the potential to facilitate the mapping and analysis of these compl…
Your Co-Workers Matter: Evaluating Collaborative Capabilities of Language Models in Blocks World
Guande Wu, Chen Zhao, Claudio Silva +1
Language agents that interact with the world on their own have great potential for automating digital tasks. While large language model (LLM) agents have made progress in understan…
Parallel Structures in Pre-training Data Yield In-Context Learning
Yanda Chen, Chen Zhao, Zhou Yu +2
Pre-trained language models (LMs) are capable of in-context learning (ICL): they can adapt to a task with only a few examples given in the prompt without any parameter update. Howe…
Towards Consistent Natural-Language Explanations via Explanation-Consistency Finetuning
Yanda Chen, Chandan Singh, Xiaodong Liu +4
Large language models (LLMs) often generate convincing, fluent explanations. However, different from humans, they often generate inconsistent explanations on different inputs. For…
Pragmatic Radiology Report Generation
Dang Nguyen, Chacha Chen, He He +1
When pneumonia is not found on a chest X-ray, should the report describe this negative observation or omit it? We argue that this question cannot be answered from the X-ray alone a…