4 papers
A Graph Signal Processing Perspective on Numerical Sequence Representations in LLM In-Context Learning
Jiajun Bao, Zihao Qi, Toni J. B. Liu +6
Pretrained large language models (LLMs) have demonstrated in-context learning (ICL) capabilities for numerical inference over sequences serialized as text. Prior work has identifie…
ClawsBench: Evaluating Capability and Safety of LLM Productivity Agents in Simulated Workspaces
Xiangyi Li, Kyoung Whan Choe, Yimin Liu +12
Large language model (LLM) agents are increasingly deployed to automate productivity tasks (e.g., email, scheduling, document management), but evaluating them on live services is r…
Text-Trained LLMs Can Zero-Shot Extrapolate PDE Dynamics, Revealing a Three-Stage In-Context Learning Mechanism
Jiajun Bao, Nicolas Boullé, Toni J. B. Liu +2
Large language models (LLMs) have demonstrated emergent in-context learning (ICL) capabilities across a range of tasks, including zero-shot time-series forecasting. We show that te…
Toward Machine Interpreting: Lessons from Human Interpreting Studies
Matthias Sperber, Maureen de Seyssel, Jiajun Bao +1
Current speech translation systems, while having achieved impressive accuracies, are rather static in their behavior and do not adapt to real-world situations in ways human interpr…