activity
20202026
most citedProgressive Tandem Learning for Pattern Recognition with Deep Spiking Neural Networks

14 citations · 31 across the 7 of their papers we have counts for

collaborators

7 papers

quant-ph2026★ 11 cited

A building block of quantum repeaters for scalable quantum networks

Wen-Zhao Liu, Ya-Bin Zhou, Jiu-Peng Chen +26

Quantum networks, integrating quantum communication, quantum metrology, and distributed quantum computing, could provide secure and efficient information transfer, high-resolution…

hep-ex2025★ 3 cited

First measurement of reactor neutrino oscillations at JUNO

Angel Abusleme, Thomas Adam, Kai Adamowicz +1131

Neutrino oscillations, a quantum effect manifesting at macroscopic scales, are governed by lepton flavor mixing angles and neutrino mass-squared differences that are fundamental pa…

hep-ex2025★ 1 cited

Initial performance results of the JUNO detector

Angel Abusleme, Thomas Adam, Kai Adamowicz +1131

The Jiangmen Underground Neutrino Observatory (JUNO) started physics data taking on 26 August 2025. JUNO consists of a 20-kton liquid scintillator central detector, surrounded by a…

cs.CL2025

Optimal Aggregation of LLM and PRM Signals for Efficient Test-Time Scaling

Peng Kuang, Yanli Wang, Xiaoyu Han +3

Process reward models (PRMs) are a cornerstone of test-time scaling (TTS), designed to verify and select the best responses from large language models (LLMs). However, this promise…

cs.CL2025

LexPro-1.0 Technical Report

Haotian Chen, Yanyu Xu, Boyan Wang +5

In this report, we introduce our first-generation reasoning model, LexPro-1.0, a large language model designed for the highly specialized Chinese legal domain, offering comprehensi…

cs.CL2024★ 2 cited

ChemSafetyBench: Benchmarking LLM Safety on Chemistry Domain

Haochen Zhao, Xiangru Tang, Ziran Yang +8

The advancement and extensive application of large language models (LLMs) have been remarkable, including their use in scientific research assistance. However, these models often g…

cs.NE2020★ 14 cited

Progressive Tandem Learning for Pattern Recognition with Deep Spiking Neural Networks

Jibin Wu, Chenglin Xu, Daquan Zhou +2

Spiking neural networks (SNNs) have shown clear advantages over traditional artificial neural networks (ANNs) for low latency and high computational efficiency, due to their event-…