Africa
Zero-Shot Transfer with Deictic Object-Oriented Representation in Reinforcement Learning
Object-oriented representations in reinforcement learning have shown promise in transfer learning, with previous research introducing a propositional objectoriented framework that has provably efficient learning bounds with respect to samplecomplexity.
Stochastic Cubic Regularization for Fast Nonconvex Optimization
Nilesh Tripuraneni, Mitchell Stern, Chi Jin, Jeffrey Regier, Michael I. Jordan
Neural Information Processing Systems http://nips.cc/
MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention Huiqiang Jiang, Yucheng Li
Existing methods for speeding up pre-filling often fail to maintain acceptable accuracy or efficiency when applied to long-context LLMs.
Predictive Attractor Models
The task of sequential memory is considered challenging for models operating under biological constraints (i.e., local synaptic computations) for many reasons, including catastrophic forgetting,
5c7465e4a236b56226ca221f3d16bf2b-Paper-Conference.pdf
Text-to-Image (T2I) has witnessed significant advancements, demonstrating superior performance for various generative tasks.
A Tensorized Transformer for Language Modeling
Xindian Ma, Peng Zhang, Shuai Zhang, Nan Duan, Yuexian Hou, Ming Zhou, Dawei Song
Neural Information Processing Systems http://nips.cc/
Conditional Independence Testing using Generative Adversarial Networks
Alexis Bellot, Mihaela van der Schaar
Neural Information Processing Systems http://nips.cc/