collaborators

11 papers

cs.RO2026

Navi-Agent: Unlocalized Monocular Navigation Agent

Wenyuan Xie, Mengyang Hong, Yongzhong Wang +9

Vision-Language Navigation in Continuous Environments (VLN-CE) requires an embodied agent to execute long-horizon instructions in unknown environments. Existing zero-shot VLN-CE sy…

cs.MA2026

MAPLE-Guard: Memory-Aware Link Enforcement Against Memory-Link Poisoning in Multi-Agent Systems

Wenjun Xiong, Yijin Zhou, Jiaqian Wang +6

LLM-based multi-agent systems (MAS) increasingly rely on persistent private and shared memories for long-horizon coordination. This memory layer improves continuity, but it also gi…

cs.RO2026

MVP-Nav: Multi-layer Value Map Planner Navigator

Wenyuan Xie, Shaokai Wu, Yijin Zhou +7

Zero-shot Object Goal Navigation (ZSON) with RGB-only perception poses a fundamental challenge for embodied agents, as the absence of explicit depth information introduces severe p…

cs.CL2026

FraudSMSWalker: Benchmarking Agentic Large Language Models for SMS-to-Webpage Fraud Detection

Y. H. Zhou, Z. M. Ma, Y. J. Zhou +12

SMS fraud is increasingly cross-channel: a message directs the user to a webpage, and the final risk depends on how the SMS claim aligns with the page content and requested user ac…

cs.AI2026

Exploring Agentic Tool-Calling Decisions via Uncertainty-Aligned Reinforcement Learning

Yijin Zhou, Linqian Zeng, Xiaoya Lu +4

Large language model (LLM)-based agents often make suboptimal tool-use decisions, including unsupported tool invocation and hallucinated direct responses, which may accumulate erro…

cs.CV2026

HomeGuard: VLM-based Embodied Safeguard for Identifying Contextual Risk in Household Task

Xiaoya Lu, Yijin Zhou, Zeren Chen +6

Vision-Language Models (VLMs) empower embodied agents to execute complex instructions, yet they remain vulnerable to contextual safety risks where benign commands become hazardous…

cs.AI2026

Frontier AI Risk Management Framework in Practice: A Risk Analysis Technical Report v1.5

Dongrui Liu, Yi Yu, Jie Zhang +18

To understand and identify the unprecedented risks posed by rapidly advancing artificial intelligence (AI) models, Frontier AI Risk Management Framework in Practice presents a comp…

cs.CL2026

DeepSight: An All-in-One LM Safety Toolkit

Bo Zhang, Jiaxuan Guo, Lijun Li +17

As the development of Large Models (LMs) progresses rapidly, their safety is also a priority. In current Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) s…

cs.MA2026

INFA-Guard: Mitigating Malicious Propagation via Infection-Aware Safeguarding in LLM-Based Multi-Agent Systems

Yijin Zhou, Xiaoya Lu, Dongrui Liu +2

The rapid advancement of Large Language Model (LLM)-based Multi-Agent Systems (MAS) has introduced significant security vulnerabilities, where malicious influence can propagate vir…

cs.AI2025

Geometrically-Constrained Agent for Spatial Reasoning

Zeren Chen, Xiaoya Lu, Zhijie Zheng +6

Vision Language Models (VLMs) exhibit a fundamental semantic-to-geometric gap in spatial reasoning: they excel at qualitative semantic inference but their reasoning operates within…

cs.AI2025

IS-Bench: Evaluating Interactive Safety of VLM-Driven Embodied Agents in Daily Household Tasks

Xiaoya Lu, Zeren Chen, Xuhao Hu +5

Flawed planning from VLM-driven embodied agents poses significant safety hazards, hindering their deployment in real-world household tasks. However, existing static, non-interactiv…