Evaluating Distributional Distortion in Neural Language Modeling. - Benjamin LeBrun; Alessandro Sordoni; Timothy J. O'Donnell (ICLR, 2022)

Detecting the corruption of online questionnaires by artificial intelligence. - Benjamin LeBrun; Sharon Temtsin; Andrew J. Vonasch; Christoph Bartneck (Frontiers Robotics AI, 2023)

Too good to be true: People reject free gifts from robots because they infer bad intentions. - Benjamin LeBrun; Andrew J. Vonasch; Christoph Bartneck (CoRR, 2024)

From Language Models over Tokens to Language Models over Characters. - Tim Vieira; Benjamin LeBrun; Mario Giulianelli; Juan Luis Gastaldi; Brian DuSell; John Terilla; Timothy J. O'Donnell; Ryan Cotterell (CoRR, 2024)

Buying the news: A quantitative study of the effects of corporate acquisition on local news. - Benjamin LeBrun; Kaitlyn Todd; Andrew Piper (New Media Soc., 2024)

Phantom Costs in Human-Robot Interaction: A Replication Study. - Benjamin LeBrun; Christoph Bartneck; Andrew J. Vonasch (HRI, 2025)

Syntactic and Semantic Control of Large Language Models via Sequential Monte Carlo. - João Loula; Benjamin LeBrun; Li Du; Ben Lipkin; Clemente Pasti; Gabriel Grand; Tianyu Liu 004; Yahya Emara; Marjorie Freedman; Jason Eisner; Ryan Cotterell; Vikash Mansinghka 001; et al. (ICLR, 2025)

Fast Controlled Generation from Language Models with Adaptive Weighted Rejection Sampling. - Benjamin Lipkin; Benjamin LeBrun; Jacob Hoover Vigly; João Loula; David R. MacIver; Li Du; Jason Eisner; Ryan Cotterell; Vikash Mansinghka 001; Timothy J. O'Donnell; Alexander K. Lew; Tim Vieira (CoRR, 2025)

Language Models over Canonical Byte-Pair Encodings. - Tim Vieira; Tianyu Liu 004; Clemente Pasti; Yahya Emara; Brian DuSell; Benjamin LeBrun; Mario Giulianelli; Juan Luis Gastaldi; Timothy J. O'Donnell; Ryan Cotterell (CoRR, 2025)