collaborators

10 papers

cs.HC2026

Sycophantic AI makes human interaction feel more effortful and less satisfying over time

Lujain Ibrahim, Franziska Sofia Hafner, Myra Cheng +5

Millions of people now turn to artificial intelligence (AI) systems for personal advice, guidance, and support. Such systems can be sycophantic, frequently affirming users' views a…

cs.HC2026

Interactive visualizations for adolescents to understand and challenge algorithmic profiling in online platforms

Yui Kondo, Kevin Dunnell, Isobel Voysey +6

Social media platforms regularly track, aggregate, and monetize adolescents' data, yet provide them with little visibility or agency over how algorithms construct their digital ide…

cs.CL2025

Measuring what Matters: Construct Validity in Large Language Model Benchmarks

Andrew M. Bean, Ryan Othniel Kearns, Angelika Romanou +39

Evaluating large language models (LLMs) is crucial for both assessing their capabilities and identifying safety or robustness issues prior to deployment. Reliably measuring abstrac…

cs.CL2025

Framing Migration: A Computational Analysis of UK Parliamentary Discourse

Vahid Ghafouri, Robert McNeil, Teodor Yankov +4

We present a large-scale computational analysis of migration-related discourse in UK parliamentary debates spanning over 75 years and compare it with US congressional discourse. Us…

cs.CL2025

Into the crossfire: evaluating the use of a language model to crowdsource gun violence reports

Adriano Belisario, Scott A. Hale, Luc Rocher

Gun violence is a pressing human rights issue that affects nearly every dimension of the social fabric, from healthcare and education to psychology and the economy. Reliable data o…

cs.CL2025

Training language models to be warm and empathetic makes them less reliable and more sycophantic

Lujain Ibrahim, Franziska Sofia Hafner, Luc Rocher

Artificial intelligence (AI) developers are increasingly building language models with warm and empathetic personas that millions of people now use for advice, therapy, and compani…