MRF-Chat: Improving Dialogue with Markov Random Fields

no code implementations • EMNLP 2021 • Ishaan Grover, Matthew Huggins, Cynthia Breazeal, Hae Won Park

Recent state-of-the-art approaches in open-domain dialogue include training end-to-end deep-learning models to learn various conversational features like emotional content of response, symbolic transitions of dialogue contexts in a knowledge graph and persona of the agent and the user, among others.

Retrieval

Look Around! Unexpected gains from training on environments in the vicinity of the target

no code implementations • 29 Jan 2024 • Serena Bono, Spandan Madan, Ishaan Grover, Mao Yasueda, Cynthia Breazeal, Hanspeter Pfister, Gabriel Kreiman

Here we present a new methodology to evaluate such generalization of RL agents under small shifts in the transition probabilities.

Atari Games Reinforcement Learning (RL)