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20232026
most citedAre Large Language Models Capable of Generating Human-Level Narratives?

5 citations · 7 across the 10 of their papers we have counts for

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9 papers · 1 filter

cs.CL2026

Evaluating Commercial AI Chatbots as News Intermediaries

Mirac Suzgun, Emily Shen, Federico Bianchi +5

AI chatbots are rapidly shaping how people encounter the news, yet no prior study has systematically measured how accurately these systems, with their proprietary search integratio…

cs.CL2025

WebDS: An End-to-End Benchmark for Web-based Data Science

Ethan Hsu, Hong Meng Yam, Ines Bouissou +9

Many real-world data science tasks involve complex web-based interactions: finding appropriate data available on the internet, synthesizing multimodal data from different locations…

cs.CL2025

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…

cs.CL2024

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As events progress, news articles often update with new information: if we are not cautious, we risk propagating outdated facts.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…

cs.CL20242 cited

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…

cs.CL2024

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.…