Deep Learning
Soft ascent-descent as a stable and flexible alternative to flooding Matthew J. Holland
While many such candidates are indeed essentially "optimal"
Learnability Matters: Active Learning for Video Captioning
This work focuses on the active learning in video captioning.
ALPS: Improved Optimization for Highly Sparse One-Shot Pruning for Large Language Models
One-shot pruning techniques offer a way to alleviate these burdens by removing redundant weights without the need for retraining. Y et, the massive scale of LLMs often forces current pruning approaches to rely on heuristics instead of optimization-based techniques, potentially resulting in suboptimal compression.
MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
Multiple Sequence Alignment (MSA) plays a pivotal role in unveiling the evolutionary trajectories of protein families.
Towards Exact Gradient-based Training on Analog In-memory Computing
While inference on analog accelerators has been studied recently, the training perspective is underexplored. Recent studies have shown that the "workhorse" of digital AI training - stochastic gradient descent (
