Deep Learning
Revealing the unseen: Benchmarking video action recognition under occlusion
In this work, we study the effect of occlusion on video action recognition.
Memory-Efficient Gradient Unrolling for Large-Scale Bi-level Optimization
U, which achieves an unbiased stochastic approximation of the meta gradient for bi-level optimization.
Response Length Perception and Sequence Scheduling: An LLM-Empowered LLM Inference Pipeline
Large language models (LLMs) have revolutionized the field of AI, demonstrating unprecedented capacity across various tasks.
Gradient Guidance for Diffusion Models: An Optimization Perspective
We establish a mathematical framework for guided diffusion to systematically study its optimization theory and algorithmic design.
ImitatingLanguagevia ScalableInverseReinforcementLearning
The majority of language model training builds on imitation learning.
AT extbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis
While deep networks have achieved broad success in analyzing natural images, when applied to medical scans, they often fail in unexpected situations.