13 papers
Heuresis: Search Strategies for Autonomous AI Research Agents Across Quality, Diversity and Novelty
Antonis Antoniades, Deepak Nathani, Ritam Saha +6
Autonomous AI Research promises to accelerate the scientific progress of machine learning. To realise this goal, current Large Language Model (LLM)-based agents need to go beyond j…
Learning POMDP World Models from Observations with Language-Model Priors
Valentin Six, Frederik Panse, Mathis Fajeau +7
Whether navigating a building, operating a robot, or playing a game, an agent that acts effectively in an environment must first learn an internal model of how that environment wor…
Planning to Explore: Curiosity-Driven Planning for LLM Test Generation
Alfonso Amayuelas, Firas Laakom, Piotr PiÄkos +5
The use of LLMs for code generation has naturally extended to code testing and evaluation. As codebases grow in size and complexity, so does the need for automated test generation.…
Grounding LLM Reasoning with Knowledge Graphs
Alfonso Amayuelas, Joy Sain, Simerjot Kaur +1
Large Language Models (LLMs) excel at generating natural language answers, yet their outputs often remain unverifiable and difficult to trace. Knowledge Graphs (KGs) offer a comple…
LeMat-Synth: a multi-modal toolbox to curate broad synthesis procedure databases from scientific literature
Magdalena Lederbauer, Siddharth Betala, Xiyao Li +16
The development of synthesis procedures remains a fundamental challenge in materials discovery, with procedural knowledge scattered across decades of scientific literature in unstr…
Agents of Change: Self-Evolving LLM Agents for Strategic Planning
Nikolas Belle, Dakota Barnes, Alfonso Amayuelas +3
We address the long-horizon gap in large language model (LLM) agents by enabling them to sustain coherent strategies in adversarial, stochastic environments. Settlers of Catan prov…