5 citations · 12 across the 8 of their papers we have counts for
7 papers · 1 filter
DiscoSum: Discourse-aware News Summarization
Alexander Spangher, Tenghao Huang, Jialiang Gu +2
Recent advances in text summarization have predominantly leveraged large language models to generate concise summaries. However, language models often do not maintain long-term dis…
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As events progress, news articles often update with new information: if we are not cautious, we risk propagating outdated facts.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…
PatentEdits: Framing Patent Novelty as Textual Entailment
Ryan Lee, Alexander Spangher, Xuezhe Ma
A patent must be deemed novel and non-obvious in order to be granted by the US Patent Office (USPTO). If it is not, a US patent examiner will cite the prior work, or prior art, tha…
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.…
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…