2 citations · 2 across the 4 of their papers we have counts for
4 papers
SemanticST: Spatially Informed Semantic Graph Learning for Clustering, Integration, and Scalable Analysis of Spatial Transcriptomics
Roxana Zahedi, Ahmadreza Argha, Nona Farbehi +4
Spatial transcriptomics (ST) technologies enable gene expression profiling with spatial resolution, offering unprecedented insights into tissue organization and disease heterogenei…
CLaSp: In-Context Layer Skip for Self-Speculative Decoding
Longze Chen, Renke Shan, Huiming Wang +6
Speculative decoding (SD) is a promising method for accelerating the decoding process of Large Language Models (LLMs). The efficiency of SD primarily hinges on the consistency betw…
CollectiveSFT: Scaling Large Language Models for Chinese Medical Benchmark with Collective Instructions in Healthcare
Jingwei Zhu, Minghuan Tan, Min Yang +2
The rapid progress in Large Language Models (LLMs) has prompted the creation of numerous benchmarks to evaluate their capabilities.This study focuses on the Comprehensive Medical B…
Empowering Precision Medicine: AI-Driven Schizophrenia Diagnosis via EEG Signals: A Comprehensive Review from 2002-2023
Mahboobeh Jafari, Delaram Sadeghi, Afshin Shoeibi +6
Schizophrenia (SZ) is a prevalent mental disorder characterized by cognitive, emotional, and behavioral changes. Symptoms of SZ include hallucinations, illusions, delusions, lack o…