111 citations · 325 across the 16 of their papers we have counts for
4 papers · 1 filter
Human-Level Performance in No-Press Diplomacy via Equilibrium Search
Jonathan Gray, Adam Lerer, Anton Bakhtin +1
Prior AI breakthroughs in complex games have focused on either the purely adversarial or purely cooperative settings. In contrast, Diplomacy is a game of shifting alliances that in…
Combining Deep Reinforcement Learning and Search for Imperfect-Information Games
Noam Brown, Anton Bakhtin, Adam Lerer +1
The combination of deep reinforcement learning and search at both training and test time is a powerful paradigm that has led to a number of successes in single-agent settings and p…
Residual Energy-Based Models for Text Generation
Yuntian Deng, Anton Bakhtin, Myle Ott +2
Text generation is ubiquitous in many NLP tasks, from summarization, to dialogue and machine translation. The dominant parametric approach is based on locally normalized models whi…
Residual Energy-Based Models for Text
Anton Bakhtin, Yuntian Deng, Sam Gross +3
Current large-scale auto-regressive language models display impressive fluency and can generate convincing text. In this work we start by asking the question: Can the generations o…