collaborators

7 papers

cs.SE2026

LiveFMBench: Unveiling the Power and Limits of Agentic Workflows in Specification Generation

Dong Xu, Jialun Cao, Guozhao Mo +9

Formal specification is essential for rigorous program verification, yet writing correct specifications remains costly and difficult to automate. Although large language models (LL…

cs.CL2026

All Languages Matter: Understanding and Mitigating Language Bias in Multilingual RAG

Dan Wang, Guozhao Mo, Yafei Shi +9

Multilingual Retrieval-Augmented Generation (mRAG) leverages cross-lingual evidence to ground Large Language Models (LLMs) in global knowledge. However, we show that current mRAG s…

cs.AI2026

DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation

Hao Zheng, Guozhao Mo, Xinru Yan +7

Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing presentation agents often rely on p…

cs.AI2026

LiveMCPBench: Can Agents Navigate an Ocean of MCP Tools?

Guozhao Mo, Wenliang Zhong, Jiawei Chen +7

Model Context Protocol (MCP) has become a key infrastructure for connecting LLMs with external tools, scaling to 10,000+ MCP servers with diverse tools. Unfortunately, there is sti…

cs.CL2025

Beyond Isolated Dots: Benchmarking Structured Table Construction as Deep Knowledge Extraction

Tianyun Zhong, Guozhao Mo, Yanjiang Liu +9

With the emergence of large language models (LLMs), there is an expectation that LLMs can effectively extract explicit information from complex real-world documents (e.g., papers,…

cs.CL2025

ConsistentChat: Building Skeleton-Guided Consistent Multi-Turn Dialogues for Large Language Models from Scratch

Jiawei Chen, Xinyan Guan, Qianhao Yuan +7

Current instruction data synthesis methods primarily focus on single-turn instructions and often neglect cross-turn coherence, resulting in context drift and reduced task completio…