collaborators

8 papers

cs.LG2026

A Behavioural and Representational Evaluation of Goal-Directedness in Language Model Agents

Raghu Arghal, Fade Chen, Niall Dalton +6

Understanding an agent's goals helps explain and predict its behaviour, yet there is no established methodology for reliably attributing goals to agentic systems. We propose a fram…

cs.CL2026

Surprisal Minimisation over Goal-directed Alternatives Predicts Production Choice in Dialogue

Tom Utting, Mario Giulianelli, Arabella Sinclair

We model utterance production as probabilistic cost-sensitive choice over contextual alternatives, using information-theoretic notions of cost. We distinguish between goal-directed…

cs.CL2026

Probing for Reading Times

Eleftheria Tsipidi, Samuel Kiegeland, Francesco Ignazio Re +4

Probing has shown that language model representations encode rich linguistic information, but it remains unclear whether they also capture cognitive signals about human processing.…

cs.LG2026

Skewed Score: A statistical framework to assess autograders

Magda Dubois, Harry Coppock, Mario Giulianelli +3

The evaluation of large language model (LLM) outputs is increasingly performed by other LLMs, a setup commonly known as "LLM-as-a-judge", or autograders. While autograders offer a…

cs.LG2026

Reasoning aligns language models to human cognition

Gonçalo Guiomar, Elia Torre, Pehuen Moure +4

Do language models make decisions under uncertainty like humans do, and what role does chain-of-thought (CoT) reasoning play in the underlying decision process? We introduce an act…

cs.CL2025

Structure-Conditional Minimum Bayes Risk Decoding

Bryan Eikema, Anna Rutkiewicz, Mario Giulianelli

Minimum Bayes Risk (MBR) decoding has seen renewed interest as an alternative to traditional generation strategies. While MBR has proven effective in machine translation, where the…