12 citations · 21 across the 15 of their papers we have counts for
5 papers · 1 filter
Beyond On-Policy vs. Off-Policy: At What Level Should LLM Agent Distillation Follow the Student?
Ya Gao, Zhengtao Zou, Pekka Marttinen
Distilling interactive LLM agents requires choosing between teacher-generated demonstrations and student-generated experience, corresponding broadly to off-policy and on-policy dis…
Edit Knowledge, Not Just Facts via Multi-Step Reasoning over Background Stories
Ya Gao, Kalle Kujanpää, Pekka Marttinen +2
Enabling artificial intelligence systems, particularly large language models, to update knowledge and flexibly apply it during reasoning remains a central challenge. Existing knowl…
Recursive Decomposition with Dependencies for Generic Divide-and-Conquer Reasoning
Sergio Hernández-Gutiérrez, Minttu Alakuijala, Alexander V. Nikitin +1
Reasoning tasks are crucial in many domains, especially in science and engineering. Although large language models (LLMs) have made progress in reasoning tasks using techniques suc…
ViPlan: A Benchmark for Visual Planning with Symbolic Predicates and Vision-Language Models
Matteo Merler, Nicola Dainese, Minttu Alakuijala +5
Integrating Large Language Models with symbolic planners is a promising direction for obtaining verifiable and grounded plans, with recent works extending this idea to visual domai…
Generating Code World Models with Large Language Models Guided by Monte Carlo Tree Search
Nicola Dainese, Matteo Merler, Minttu Alakuijala +1
In this work we consider Code World Models, world models generated by a Large Language Model (LLM) in the form of Python code for model-based Reinforcement Learning (RL). Calling c…