activity
20152026
most citedGCNs-Net: A Graph Convolutional Neural Network Approach for Decoding Time-resolved EEG Motor Imagery Signals

180 citations · 1.1k across the 125 of their papers we have counts for

collaborators

127 papers

cs.SE2026

EvoConfig: Self-Evolving Multi-Agent Systems for Efficient Autonomous Environment Configuration

Xinshuai Guo, Jiayi Kuang, Linyue Pan +6

A reliable executable environment is the foundation for ensuring that large language models solve software engineering tasks. Due to the complex and tedious construction process, l…

cs.CL2026

Youtu-LLM: Unlocking the Native Agentic Potential for Lightweight Large Language Models

Junru Lu, Jiarui Qin, Lingfeng Qiao +35

We introduce Youtu-LLM, a lightweight yet powerful language model that harmonizes high computational efficiency with native agentic intelligence. Unlike typical small models that r…

cs.CV2026

TangramPuzzle: Evaluating Multimodal Large Language Models with Compositional Spatial Reasoning

Daixian Liu, Jiayi Kuang, Yinghui Li +8

Multimodal Large Language Models (MLLMs) have achieved remarkable progress in visual recognition and semantic understanding, yet precise compositional spatial reasoning under geome…

cs.SE2025

Process-Level Trajectory Evaluation for Environment Configuration in Software Engineering Agents

Jiayi Kuang, Yinghui Li, Xin Zhang +5

Large language model-based agents show promise for software engineering, but environment configuration remains a bottleneck due to heavy manual effort and scarce large-scale, high-…

cs.LG2025★ 2 cited

SDG-L: A Semiparametric Deep Gaussian Process based Framework for Battery Capacity Prediction

Hanbing Liu, Yanru Wu, Yang Li +2

Lithium-ion batteries are becoming increasingly omnipresent in energy supply. However, the durability of energy storage using lithium-ion batteries is threatened by their dropping…

cs.CL2025

MDIT: A Model-free Data Interpolation Method for Diverse Instruction Tuning

Yangning Li, Zihua Lan, Lv Qingsong +2

As Large Language Models (LLMs) are increasingly applied across various tasks, instruction tuning has emerged as a critical method for enhancing model performance. However, current…