2 citations · 6 across the 23 of their papers we have counts for
3 papers · 1 filter
Workspace Optimization: How to Train Your Agent
Elad Sarafian, Gal Kaplun, Ron Banner +2
Modern agents built on frontier language models often cannot adapt their weights. What, then, remains trainable? We argue it is the agent's \emph{workspace}, the structured externa…
The Challenge of Teaching Reasoning to LLMs Without RL or Distillation
Wei Du, Branislav Kisacanin, George Armstrong +22
Reasoning-capable language models achieve state-of-the-art performance in diverse complex tasks by generating long, explicit Chain-of-Thought (CoT) traces. While recent works show…
Scoring Verifiers: Evaluating Synthetic Verification for Code and Reasoning
Aleksander Ficek, Somshubra Majumdar, Vahid Noroozi +1
Synthetic verification techniques such as generating test cases and reward modelling are common ways to enhance the coding capabilities of large language models (LLM) beyond predef…