6 papers
The Parts Are Greater Than the Sum: Automated Task Sequencing for Efficient Training of Multi-Policy LLMs
Jiajia Tang, Sizhe Yuen, Francisco Gomez Medina +2
Parameter-Efficient Fine-Tuning (PEFT) commonly adapts large language models using a single shared Low-Rank Adapter (LoRA). This shared optimization space often suffers from interf…
Intrinsic Memory Agents: Heterogeneous Multi-Agent LLM Systems through Structured Contextual Memory
Sizhe Yuen, Francisco Gomez Medina, Ting Su +2
Multi-agent systems built on Large Language Models (LLMs) show exceptional promise for complex collaborative problem-solving, yet they face fundamental challenges stemming from con…
HAVA: Hybrid Approach to Value-Alignment through Reward Weighing for Reinforcement Learning
Kryspin Varys, Federico Cerutti, Adam Sobey +1
Our society is governed by a set of norms which together bring about the values we cherish such as safety, fairness or trustworthiness. The goal of value-alignment is to create age…
Automatic Dataset Generation for Knowledge Intensive Question Answering Tasks
Sizhe Yuen, Ting Su, Ziyang Wang +2
A question-answering (QA) system is to search suitable answers within a knowledge base. Current QA systems struggle with queries requiring complex reasoning or real-time knowledge…
CHIRPs: Change-Induced Regret Proxy metrics for Lifelong Reinforcement Learning
John Birkbeck, Adam Sobey, Federico Cerutti +2
Reinforcement learning (RL) agents are costly to train and fragile to environmental changes. They often perform poorly when there are many changing tasks, prohibiting their widespr…
Collaborating in a competitive world: Heterogeneous Multi-Agent Decision Making in Symbiotic Supply Chain Environments
Wan Wang, Haiyan Wang, Adam J. Sobey
Supply networks require collaboration in a competitive environment. To achieve this, nodes in the network often form symbiotic relationships as they can be adversely effected by th…