2 citations · 5 across the 6 of their papers we have counts for
3 papers · 1 filter
Bayesian Reward Models for LLM Alignment
Adam X. Yang, Maxime Robeyns, Thomas Coste +4
To ensure that large language model (LLM) responses are helpful and non-toxic, a reward model trained on human preference data is usually used. LLM responses with high rewards are…
Bayesian Low-rank Adaptation for Large Language Models
Adam X. Yang, Maxime Robeyns, Xi Wang +1
Low-rank adaptation (LoRA) has emerged as a new paradigm for cost-efficient fine-tuning of large language models (LLMs). However, fine-tuned LLMs often become overconfident especia…
Taylor TD-learning
Michele Garibbo, Maxime Robeyns, Laurence Aitchison
Many reinforcement learning approaches rely on temporal-difference (TD) learning to learn a critic. However, TD-learning updates can be high variance. Here, we introduce a model-ba…