9 papers
Efficient Reasoning on the Edge
Yelysei Bondarenko, Thomas Hehn, Rob Hesselink +15
Large language models (LLMs) with chain-of-thought reasoning achieve state-of-the-art performance across complex problem-solving tasks, but their verbose reasoning traces and large…
Fundamental bounds on efficiency-confidence trade-off for transductive conformal prediction
Arash Behboodi, Alvaro H. C. Correia, Fabio Valerio Massoli +1
Transductive conformal prediction addresses the simultaneous prediction for multiple data points. Given a desired confidence level, the objective is to construct a prediction set t…
Memory-Efficient Looped Transformer: Decoupling Compute from Memory in Looped Language Models
Victor Conchello Vendrell, Arnau Padres Masdemont, Niccolò Grillo +3
Recurrent LLM architectures have emerged as a promising approach for improving reasoning, as they enable multi-step computation in the embedding space without generating intermedia…
Reasoning as Compression: Unifying Budget Forcing via the Conditional Information Bottleneck
Fabio Valerio Massoli, Andrey Kuzmin, Arash Behboodi
\ac{CoT} prompting improves LLM accuracy on complex tasks but often increases token usage and inference cost. Existing ``Budget Forcing'' methods reduce cost via fine-tuning with h…
LUMINA: Long-horizon Understanding for Multi-turn Interactive Agents
Amin Rakhsha, Thomas Hehn, Pietro Mazzaglia +3
Large language models can perform well on many isolated tasks, yet they continue to struggle on multi-turn, long-horizon agentic problems that require skills such as planning, stat…
An Information Theoretic Perspective on Conformal Prediction
Alvaro H. C. Correia, Fabio Valerio Massoli, Christos Louizos +1
Conformal Prediction (CP) is a distribution-free uncertainty estimation framework that constructs prediction sets guaranteed to contain the true answer with a user-specified probab…