Search Results for author: Alexander Spangher

Found 15 papers, 5 papers with code

Tracking the Newsworthiness of Public Documents

no code implementations16 Nov 2023 Alexander Spangher, Emilio Ferrara, Ben Welsh, Nanyun Peng, Serdar Tumgoren, Jonathan May

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 understand coverage patterns and help us build assistive tools.

Retrieval

Stay on topic with Classifier-Free Guidance

no code implementations30 Jun 2023 Guillaume Sanchez, Honglu Fan, Alexander Spangher, Elad Levi, Pawan Sasanka Ammanamanchi, Stella Biderman

Classifier-Free Guidance (CFG) has recently emerged in text-to-image generation as a lightweight technique to encourage prompt-adherence in generations.

Code Generation Common Sense Reasoning +7

Identifying Informational Sources in News Articles

1 code implementation24 May 2023 Alexander Spangher, Nanyun Peng, Jonathan May, Emilio Ferrara

News articles are driven by the informational sources journalists use in reporting.

Text Generation

Sequentially Controlled Text Generation

no code implementations5 Jan 2023 Alexander Spangher, Xinyu Hua, Yao Ming, Nanyun Peng

While GPT-2 generates sentences that are remarkably human-like, longer documents can ramble and do not follow human-like writing structure.

Text Generation

If it Bleeds, it Leads: A Computational Approach to Covering Crime in Los Angeles

no code implementations14 Jun 2022 Alexander Spangher, Divya Choudhary

Developing and improving computational approaches to covering news can increase journalistic output and improve the way stories are covered.

NewsEdits: A News Article Revision Dataset and a Document-Level Reasoning Challenge

1 code implementation14 Jun 2022 Alexander Spangher, Xiang Ren, Jonathan May, Nanyun Peng

News article revision histories provide clues to narrative and factual evolution in news articles.

StateCensusLaws.org: A Web Application for Consuming and Annotating Legal Discourse Learning

no code implementations20 Apr 2021 Alexander Spangher, Jonathan May

In this work, we create a web application to highlight the output of NLP models trained to parse and label discourse segments in law text.

NewsEdits: A Dataset of Revision Histories for News Articles (Technical Report: Data Processing)

no code implementations19 Apr 2021 Alexander Spangher, Jonathan May

In this work, we present, to our knowledge, the first publicly available dataset of news article revision histories, or NewsEdits.

"Don't quote me on that": Finding Mixtures of Sources in News Articles

1 code implementation19 Apr 2021 Alexander Spangher, Nanyun Peng, Jonathan May, Emilio Ferrara

Journalists publish statements provided by people, or \textit{sources} to contextualize current events, help voters make informed decisions, and hold powerful individuals accountable.

Clustering

Modeling "Newsworthiness" for Lead-Generation Across Corpora

no code implementations19 Apr 2021 Alexander Spangher, Nanyun Peng, Jonathan May, Emilio Ferrara

Journalists obtain "leads", or story ideas, by reading large corpora of government records: court cases, proposed bills, etc.

Multitask Learning for Class-Imbalanced Discourse Classification

no code implementations2 Jan 2021 Alexander Spangher, Jonathan May, Sz-Rung Shiang, Lingjia Deng

Small class-imbalanced datasets, common in many high-level semantic tasks like discourse analysis, present a particular challenge to current deep-learning architectures.

Classification General Classification +1

Actionable Recourse in Linear Classification

3 code implementations18 Sep 2018 Berk Ustun, Alexander Spangher, Yang Liu

We present integer programming tools to ensure recourse in linear classification problems without interfering in model development.

Classification Credit score +2

Bayesian Nonparametrics in Topic Modeling: A Brief Tutorial

no code implementations16 Jan 2015 Alexander Spangher

Using nonparametric methods has been increasingly explored in Bayesian hierarchical modeling as a way to increase model flexibility.

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