collaborators

10 papers

cs.AI2026

LiveBrowseComp: Are Search Agents Searching, or Just Verifying What They Already Know?

HuiMing Fan, Xiao Wang, Zheng Chu +5

Are LLM-based search agents genuinely searching, or using the web to verify what they already know? We study this question on BrowseComp with three diagnostics. Our analysis reveal…

cs.SE2026

The Evolution of Tool Use in LLM Agents: From Single-Tool Call to Multi-Tool Orchestration

Haoyuan Xu, Chang Li, Xinyan Ma +12

Tool use enables large language models (LLMs) to access external information, invoke software systems, and act in digital environments beyond what can be solved from model paramete…

cs.CV2026

Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models

Wenxuan Huang, Yu Zeng, Qiuchen Wang +14

Multimodal large language models (MLLMs) have achieved remarkable success across a broad range of vision tasks. However, constrained by the capacity of their internal world knowled…

cs.CL2026

Scalable Multilingual Multimodal Machine Translation with Speech-Text Fusion

Yexing Du, Youcheng Pan, Zekun Wang +7

Multimodal Large Language Models (MLLMs) have achieved notable success in enhancing translation performance by integrating multimodal information. However, existing research primar…

cs.AI2026

REDSearcher: A Scalable and Cost-Efficient Framework for Long-Horizon Search Agents

Zheng Chu, Xiao Wang, Jack Hong +11

Large language models are transitioning from generalpurpose knowledge engines to realworld problem solvers, yet optimizing them for deep search tasks remains challenging. The centr…

cs.CL2026

CCFQA: A Benchmark for Cross-Lingual and Cross-Modal Speech and Text Factuality Evaluation

Yexing Du, Kaiyuan Liu, Youcheng Pan +5

As Large Language Models (LLMs) are increasingly popularized in the multilingual world, ensuring hallucination-free factuality becomes markedly crucial. However, existing benchmark…