9 papers
Log-Averaged Mirror Prox for Fast, Large-Scale Optimal Transport in Linear Space
Matthew X. Burns, Jiaming Liang
We propose Log-Averaged Mirror Prox (LAMP), a linear-space primal-dual method for large-scale optimal transport. LAMP implements primal mirror prox updates by tracking an averaged…
Constrained and Composite Sampling via Proximal Sampler
Thanh Dang, Jiaming Liang
We study two log-concave sampling problems: constrained sampling and composite sampling. First, we consider sampling from a target distribution with density proportional to $\exp(-…
Oracle-based Uniform Sampling from Convex Bodies
Thanh Dang, Jiaming Liang
We propose new Markov chain Monte Carlo algorithms to sample a uniform distribution on a convex body . Our algorithms are based on the proximal sampler, which uses Gibbs samplin…
SafeNeuron: Neuron-Level Safety Alignment for Large Language Models
Zhaoxin Wang, Jiaming Liang, Fengbin Zhu +5
Large language models (LLMs) and multimodal LLMs are typically safety-aligned before release to prevent harmful content generation. However, recent studies show that safety behavio…
Prune, Don't Rebuild: Efficiently Tuning -Reachable Graphs for Nearest Neighbor Search
Tian Zhang, Ashwin Padaki, Jiaming Liang +2
Vector similarity search is an essential primitive in modern AI and ML applications. Most vector databases adopt graph-based approximate nearest neighbor (ANN) search algorithms, s…
GreatSplicing: A Semantically Rich Splicing Dataset
Jiaming Liang, Yuwan Xue, Haowei Liu +9
In existing splicing forgery datasets, the insufficient semantic variety of spliced regions causes trained detection models to overfit semantic features rather than learn genuine s…