5 papers
Beyond Context Length: Characterising the Difficulty of Long-Context Reasoning
Shiwen Qin, Cameron Barker, Henry Gouk +4
Long-context language models support ever longer context windows, and evaluations typically treat context length as the main indicator of difficulty. However, context length alone…
Heterogeneous Structured Pruning Under Resource Constraints for Hardware-Efficient Large Language Models
Cameron Barker, Andreas Paraskeva, Jan N. van Rijn +2
Training-free pruning removes weights from pretrained large language models to reduce their deployment cost. However, existing approaches typically consider only the total number o…
Benchmarking Open-Ended Multi-Agent Coordination in Language Agents
Kale-ab Abebe Tessera, Andras Szecsenyi, Cameron Barker +7
As language models are increasingly deployed as autonomous agents, they must coordinate with others over long horizons in open-ended interactive tasks. Yet existing evaluations rar…
Kalman Linear Attention: Parallel Bayesian Filtering For Efficient Language Modelling and State Tracking
Vaisakh Shaj, Cameron Barker, Aidan Scannell +3
State-space language models such as Mamba and gated linear attention (GLA) offer linear-complexity, parallelisable alternatives to transformers, but their linear state updates limi…
Demonstration of a Logical Architecture Uniting Motion and In-Place Entanglement
Rich Rines, Benjamin Hall, Mariesa H. Teo +35
We demonstrate a logical neutral atom architecture that integrates atom motion with in-place entanglement to achieve lower overheads than entangling-zone approaches. Using a 114-qu…