collaborators

6 papers

cs.CV2026

MSGNav: Unleashing the Power of Multi-modal 3D Scene Graph for Zero-Shot Embodied Navigation

Xun Huang, Shijia Zhao, Yunxiang Wang +6

Embodied navigation is a fundamental capability for robotic agents operating. Real-world deployment requires open vocabulary generalization and low training overhead, motivating ze…

cs.CV2026

Embed-RL: Reinforcement Learning for Reasoning-Driven Multimodal Embeddings

Haonan Jiang, Yuji Wang, Yongjie Zhu +5

Leveraging Multimodal Large Language Models (MLLMs) has become pivotal for advancing Universal Multimodal Embeddings (UME) in addressing diverse cross-modal tasks. Recent studies d…

cs.AI2026

OmegaUse: Building a General-Purpose GUI Agent for Autonomous Task Execution

Le Zhang, Yixiong Xiao, Xinjiang Lu +12

Graphical User Interface (GUI) agents show great potential for enabling foundation models to complete real-world tasks, revolutionizing human-computer interaction and improving hum…

cs.CL2025

INSEva: A Comprehensive Chinese Benchmark for Large Language Models in Insurance

Shisong Chen, Qian Zhu, Wenyan Yang +15

Insurance, as a critical component of the global financial system, demands high standards of accuracy and reliability in AI applications. While existing benchmarks evaluate AI capa…

cs.CL2025

EL4NER: Ensemble Learning for Named Entity Recognition via Multiple Small-Parameter Large Language Models

Yuzhen Xiao, Jiahe Song, Yongxin Xu +6

In-Context Learning (ICL) technique based on Large Language Models (LLMs) has gained prominence in Named Entity Recognition (NER) tasks for its lower computing resource consumption…

cs.CR2025

SeqAR: Jailbreak LLMs with Sequential Auto-Generated Characters

Yan Yang, Zeguan Xiao, Xin Lu +5

The widespread applications of large language models (LLMs) have brought about concerns regarding their potential misuse. Although aligned with human preference data before release…