4 papers
Exploration Structure in LLM Agents for Multi-File Change Localization
Akeela Darryl Fattha, Kia Ying Chua, Lingxiao Jiang +1
Software engineering tools increasingly rely on LLM based agents to localize files to change to resolve a software issue. Most AI agents explore repositories linearly, that is, vis…
Quantum-Inspired Trace-Augmented Evidence Selection for Reasoning over Structured Hypothesis Spaces
Laura Wynter, Nirvik Sahoo, Paul Griffin
Large language models (LLMs) now solve a wide range of expert-level exams at or above human level, yet remain brittle on specialised, evidence-intensive domains such as law. On the…
Declarative Skills for AI Agents in Knowledge-Grounded Tool-Use Workflows
M. Danish Lim, I. Danial Bin Sharudin, Wen Han Chen +2
We study orchestration mechanisms for tool-using AI agents in realistic customer-service workflows over an unstructured knowledge base. We argue that declarative agents -- AI agent…
Collaboratively adding new knowledge to an LLM
Rhui Dih Lee, Laura Wynter
We address the question of how to successively add new knowledge to an LLM whilst retaining previously-added knowledge. We consider two settings, semi-cooperative and fully-coopera…