7.4k citations · 28.3k across the 205 of their papers we have counts for
9 papers · 1 filter
Multimodal Graph Learning for Generative Tasks
Minji Yoon, Jing Yu Koh, Bryan Hooi +1
Multimodal learning combines multiple data modalities, broadening the types and complexity of data our models can utilize: for example, from plain text to image-caption pairs. Most…
SPRING: Studying the Paper and Reasoning to Play Games
Yue Wu, Shrimai Prabhumoye, So Yeon Min +5
Open-world survival games pose significant challenges for AI algorithms due to their multi-tasking, deep exploration, and goal prioritization requirements. Despite reinforcement le…
Reasoning Over Virtual Knowledge Bases With Open Predicate Relations
Haitian Sun, Pat Verga, Bhuwan Dhingra +2
We present the Open Predicate Query Language (OPQL); a method for constructing a virtual KB (VKB) trained entirely from text. Large Knowledge Bases (KBs) are indispensable for a wi…
Planning with Submodular Objective Functions
Ruosong Wang, Hanrui Zhang, Devendra Singh Chaplot +2
We study planning with submodular objective functions, where instead of maximizing the cumulative reward, the goal is to maximize the objective value induced by a submodular functi…
On Emergent Communication in Competitive Multi-Agent Teams
Paul Pu Liang, Jeffrey Chen, Ruslan Salakhutdinov +2
Several recent works have found the emergence of grounded compositional language in the communication protocols developed by mostly cooperative multi-agent systems when learned end…
Search on the Replay Buffer: Bridging Planning and Reinforcement Learning
Benjamin Eysenbach, Ruslan Salakhutdinov, Sergey Levine
The history of learning for control has been an exciting back and forth between two broad classes of algorithms: planning and reinforcement learning. Planning algorithms effectivel…