8 papers · 1 filter
Language Bottleneck Models for Qualitative Knowledge State Modeling
Antonin Berthon, Mihaela van der Schaar
Accurately assessing student knowledge is central to education. Cognitive Diagnosis (CD) models estimate student proficiency at a fixed point in time, while Knowledge Tracing (KT)…
GameTalk: Training LLMs for Strategic Conversation
Victor Conchello Vendrell, Max Ruiz Luyten, Mihaela van der Schaar
Strategic decision-making in multi-agent settings is a key challenge for large language models (LLMs), particularly when coordination and negotiation must unfold over extended conv…
Visualizing token importance for black-box language models
Paulius Rauba, Qiyao Wei, Mihaela van der Schaar
We consider the problem of auditing black-box large language models (LLMs) to ensure they behave reliably when deployed in production settings, particularly in high-stakes domains…
Continuously Updating Digital Twins using Large Language Models
Harry Amad, Nicolás Astorga, Mihaela van der Schaar
Digital twins are models of real-world systems that can simulate their dynamics in response to potential actions. In complex settings, the state and action variables, and available…
Statistical Hypothesis Testing for Auditing Robustness in Language Models
Paulius Rauba, Qiyao Wei, Mihaela van der Schaar
Consider the problem of testing whether the outputs of a large language model (LLM) system change under an arbitrary intervention, such as an input perturbation or changing the mod…
The Synergy of LLMs & RL Unlocks Offline Learning of Generalizable Language-Conditioned Policies with Low-fidelity Data
Thomas Pouplin, Katarzyna Kobalczyk, Hao Sun +1
Developing autonomous agents capable of performing complex, multi-step decision-making tasks specified in natural language remains a significant challenge, particularly in realisti…