Education
The Closeness of In-Context Learning and Weight Shifting for Softmax Regression
Large language models (LLMs) are known for their exceptional performance in natural language processing, making them highly effective in many human life-related tasks.
The Mamba in the Llama: Distilling and Accelerating Hybrid Models
Linear RNN architectures, like Mamba, can be competitive with Transformer models in language modeling while having advantageous deployment characteristics. Given the focus on training large-scale Transformer models, we consider the challenge of converting these pretrained models for deployment.
On Sampling Strategies for Spectral Model Sharding
The general recipe for each communication round is composed of three steps.
Exploring the Edges of Latent State Clusters for Goal-Conditioned Reinforcement Learning
Exploring unknown environments efficiently is a fundamental challenge in unsupervised goal-conditioned reinforcement learning.
Neural Conditional Probability for Uncertainty Quantification Vladimir R. Kostic
We introduce Neural Conditional Probability (NCP), an operator-theoretic approach to learning conditional distributions with a focus on statistical inference tasks.
HW-Aware-GPT-Bench
This energy usage is comparable to that of around 180,000 U.S. households, each