1.2k citations · 4.5k across the 78 of their papers we have counts for
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Selective Perception: Optimizing State Descriptions with Reinforcement Learning for Language Model Actors
Kolby Nottingham, Yasaman Razeghi, Kyungmin Kim +4
Large language models (LLMs) are being applied as actors for sequential decision making tasks in domains such as robotics and games, utilizing their general world knowledge and pla…
Interpretable Joint Event-Particle Reconstruction for Neutrino Physics at NOvA with Sparse CNNs and Transformers
Alexander Shmakov, Alejandro Yankelevich, Jianming Bian +1
The complex events observed at the NOvA long-baseline neutrino oscillation experiment contain vital information for understanding the most elusive particles in the standard model.…
Feasible Adversarial Robust Reinforcement Learning for Underspecified Environments
JB Lanier, Stephen McAleer, Pierre Baldi +1
Robust reinforcement learning (RL) considers the problem of learning policies that perform well in the worst case among a set of possible environment parameter values. In real-worl…
The Quarks of Attention
Pierre Baldi, Roman Vershynin
Attention plays a fundamental role in both natural and artificial intelligence systems. In deep learning, attention-based neural architectures, such as transformer architectures, a…
Rxn Hypergraph: a Hypergraph Attention Model for Chemical Reaction Representation
Mohammadamin Tavakoli, Alexander Shmakov, Francesco Ceccarelli +1
It is fundamental for science and technology to be able to predict chemical reactions and their properties. To achieve such skills, it is important to develop good representations…
Tourbillon: a Physically Plausible Neural Architecture
Mohammadamin Tavakoli, Peter Sadowski, Pierre Baldi
In a physical neural system, backpropagation is faced with a number of obstacles including: the need for labeled data, the violation of the locality learning principle, the need fo…