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Found 6 papers, 1 papers with code
An Attention-driven Two-stage Clustering Method for Unsupervised Person Re-Identification
By iteratively learning with the two strategies, the attentive regions are gradually shifted from the background to the foreground and the features become more discriminative.
ATG: Benchmarking Automated Theorem Generation for Generative Language Models
We conduct extensive experiments to investigate whether current LMs can generate theorems in the library and benefit the problem theorems proving.
MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data
Recent large language models (LLMs) have witnessed significant advancement in various tasks, including mathematical reasoning and theorem proving.
Machine-Learned Invertible Coarse Graining for Multiscale Molecular Modeling
Multiscale molecular modeling is widely applied in scientific research of molecular properties over large time and length scales.
DSDP: A Blind Docking Strategy Accelerated by GPUs
In this study, we take the advantage of both traditional and machine-learning based methods, and present a method Deep Site and Docking Pose (DSDP) to improve the performance of blind docking.
Spatiotemporal Information Processing with a Reservoir Decision-making Network
Spatiotemporal information processing is fundamental to brain functions.
