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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.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…