3 citations · 3 across the 2 of their papers we have counts for
4 papers
Towards Comprehensive Stage-wise Benchmarking of Large Language Models in Fact-Checking
Hongzhan Lin, Zixin Chen, Zhiqi Shen +5
Large Language Models (LLMs) are increasingly deployed in real-world fact-checking systems, yet existing evaluations focus predominantly on claim verification and overlook the broa…
MCP-SafetyBench: A Benchmark for Safety Evaluation of Large Language Models with Real-World MCP Servers
Xuanjun Zong, Zhiqi Shen, Lei Wang +2
Large language models (LLMs) are evolving into agentic systems that reason, plan, and operate external tools. The Model Context Protocol (MCP) is a key enabler of this transition,…
MCP-Universe: Benchmarking Large Language Models with Real-World Model Context Protocol Servers
Ziyang Luo, Zhiqi Shen, Wenzhuo Yang +7
The Model Context Protocol has emerged as a transformative standard for connecting large language models to external data sources and tools, rapidly gaining adoption across major A…
Aria: An Open Multimodal Native Mixture-of-Experts Model
Dongxu Li, Yudong Liu, Haoning Wu +17
Information comes in diverse modalities. Multimodal native AI models are essential to integrate real-world information and deliver comprehensive understanding. While proprietary mu…