794 citations · 2.7k across the 93 of their papers we have counts for
96 papers
Multi-Turn Evaluation of Deep Research Agents Under Process-Level Feedback
Rishabh Sabharwal, Hongru Wang, Amos Storkey +1
Existing benchmarks for deep research agents (DRAs) assess only single-shot outputs, ignoring a key question: can DRAs improve their reports when guided by feedback? To investigate…
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…
Adapting Time Series Foundation Models through Data Mixtures
Thomas L. Lee, Edoardo M. Ponti, Amos Storkey
Time series foundation models (TSFMs) have become increasingly popular for zero-shot forecasting. However, for a new time series domain not fully covered by the pretraining set, pe…
Signature-Kernel Based Evaluation Metrics for Robust Probabilistic and Tail-Event Forecasting
Benjamin R. Redhead, Thomas L. Lee, Peng Gu +2
Probabilistic forecasting is increasingly critical across high-stakes domains, from finance and epidemiology to climate science. However, current evaluation frameworks lack a conse…
Probing Dec-POMDP Reasoning in Cooperative MARL
Kale-ab Tessera, Leonard Hinckeldey, Riccardo Zamboni +2
Cooperative multi-agent reinforcement learning (MARL) is typically framed as a decentralised partially observable Markov decision process (Dec-POMDP), a setting whose hardness stem…
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…