Laure Soulier

A Reinforcement Learning-driven Translation Model for Search-Oriented Conversational Systems

2018

Search-oriented conversational systems rely on information needs expressed in natural language (NL). We focus here on the understanding of NL expressions for building keywordbased queries. We propose a reinforcementlearning-driven translation model framework able to 1) …

A Reinforcement Learning-driven Translation Model for Search-Oriented\n Conversational Systems

2018 · arXiv (Cornell University)

Search-oriented conversational systems rely on information needs expressed in\nnatural language (NL). We focus here on the understanding of NL expressions for\nbuilding keyword-based queries. We propose a reinforcement-learning-driven\ntranslation model framework able to 1) learn the translation …

Building a Subspace of Policies for Scalable Continual Learning

2022 · arXiv (Cornell University)

The ability to continuously acquire new knowledge and skills is crucial for autonomous agents. Existing methods are typically based on either fixed-size models that struggle to learn a large number of diverse behaviors, or growing-size …

Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards

2023 · arXiv (Cornell University)

Foundation models are first pre-trained on vast unsupervised datasets and then fine-tuned on labeled data. Reinforcement learning, notably from human feedback (RLHF), can further align the network with the intended usage. Yet the imperfections in …