3 papers
cs.LG2025
Provable Benefits of In-Tool Learning for Large Language Models
Sam Houliston, Ambroise Odonnat, Charles Arnal +1
Tool-augmented language models, equipped with retrieval, memory, or external APIs, are reshaping AI, yet their theoretical advantages remain underexplored. In this paper, we addres…
cs.AI2025
Reasoning Language Models: A Blueprint
Maciej Besta, Julia Barth, Eric Schreiber +16
Reasoning language models (RLMs), also known as Large Reasoning Models (LRMs), such as OpenAI's o1 and o3, DeepSeek-R1, and Alibaba's QwQ, have redefined AI's problem-solving capab…
cs.LG2024
Uncertainty-Penalized Direct Preference Optimization
Sam Houliston, Alizée Pace, Alexander Immer +1
Aligning Large Language Models (LLMs) to human preferences in content, style, and presentation is challenging, in part because preferences are varied, context-dependent, and someti…