3 papers
cs.AI2026
Thomson: Continual Learning of Frontier Models for SovereignAI
Shengzhuang Chen, Jerrod Parker, Yejin Bang +23
The development of frontier models is commonly perceived to be the exclusive remit of a small number of heavily funded players, creating an information, economic and power asymmetr…
cs.CL2026
Test-Time Scaling in the Wild: Why Exploitation, Not Exploration, Is the Bottleneck
Davide Romano, Kanak Raj, Jerrod Parker +1
Test-time scaling (TTS) improves language model outputs by spending additional inference compute - generating multiple candidates, searching over partial sequences, or iteratively…
cs.CL2025
Evaluating the Role of Verifiers in Test-Time Scaling for Legal Reasoning Tasks
Davide Romano, Jonathan Schwarz, Daniele Giofré
Test-time scaling (TTS) techniques can improve the performance of large language models (LLMs) at the expense of additional computation and latency. While TTS has proven effective…