5 citations · 5 across the 5 of their papers we have counts for
5 papers · 1 filter
NewsEdits 2.0: Learning the Intentions Behind Updating News
Alexander Spangher, Kung-Hsiang Huang, Hyundong Cho +1
As events progress, news articles often update with new information: if we are not cautious, we risk propagating outdated facts. In this work, we hypothesize that linguistic featur…
Explaining Mixtures of Sources in News Articles
Alexander Spangher, James Youn, Matt DeButts +3
Human writers plan, then write. For large language models (LLMs) to play a role in longer-form article generation, we must understand the planning steps humans make before writing.…
NewsInterview: a Dataset and a Playground to Evaluate LLMs' Ground Gap via Informational Interviews
Alexander Spangher, Michael Lu, Sriya Jeslyn Kalyan +3
Large Language Models (LLMs) have demonstrated impressive capabilities in generating coherent text but often struggle with grounding language and strategic dialogue. To address thi…
Are Large Language Models Capable of Generating Human-Level Narratives?
Yufei Tian, Tenghao Huang, Miri Liu +5
This paper investigates the capability of LLMs in storytelling, focusing on narrative development and plot progression. We introduce a novel computational framework to analyze narr…
Tracking the Newsworthiness of Public Documents
Alexander Spangher, Emilio Ferrara, Ben Welsh +3
Journalists must find stories in huge amounts of textual data (e.g. leaks, bills, press releases) as part of their jobs: determining when and why text becomes news can help us unde…