2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2026
Intent-aligned Formal Specification Synthesis via Traceable Refinement
Zhe Ye, Aidan Z. H. Yang, Huangyuan Su +6
Large language models are increasingly used to generate code from natural language, but ensuring correctness remains challenging. Formal verification offers a principled way to obt…
cs.LG2026
Learning Adaptive LLM Decoding
Chloe H. Su, Zhe Ye, Samuel Tenka +3
Decoding from large language models (LLMs) typically relies on fixed sampling hyperparameters (e.g., temperature, top-p), despite substantial variation in task difficulty and uncer…
cs.AI2024★ 2 cited
Active Inference as a Model of Agency
Lancelot Da Costa, Samuel Tenka, Dominic Zhao +1
Is there a canonical way to think of agency beyond reward maximisation? In this paper, we show that any type of behaviour complying with physically sound assumptions about how macr…