1 citations · 1 across the 9 of their papers we have counts for
9 papers
SafeAtlas-VL: Beyond Binary Multimodal Safety with Large-Scale Data and Guard Models
Zongrui Wang, Xiangyang Zhu, Sicheng Wang +13
Multimodal safety moderation requires distinguishing risks arising from visual content, user intent, and assistant behavior. Existing safeguards, however, are typically trained for…
ALL-FEM: Agentic Large Language models Fine-tuned for Finite Element Methods
Rushikesh Deotale, Adithya Srinivasan, Yuan Tian +3
Finite element (FE) analysis guides the design and verification of nearly all manufactured objects. It is at the core of computational engineering, enabling simulation of complex p…
SafeSci: Safety Evaluation of Large Language Models in Science Domains and Beyond
Xiangyang Zhu, Yuan Tian, Qi Jia +14
The success of large language models (LLMs) in scientific domains has heightened safety concerns, prompting numerous benchmarks to evaluate their scientific safety. Existing benchm…
Do LLM-Driven Agents Exhibit Engagement Mechanisms? Controlled Tests of Information Load, Descriptive Norms, and Popularity Cues
Tai-Quan Peng, Yuan Tian, Songsong Liang +2
Large language models make agent-based simulation more behaviorally expressive, but they also sharpen a basic methodological tension: fluent, human-like output is not, by itself, e…
Automated Safety Benchmarking: A Multi-agent Pipeline for LVLMs
Xiangyang Zhu, Yuan Tian, Zicheng Zhang +6
Large vision-language models (LVLMs) exhibit remarkable capabilities in cross-modal tasks but face significant safety challenges, which undermine their reliability in real-world ap…
Embodied Image Compression
Chunyi Li, Rui Qing, Jianbo Zhang +6
Image Compression for Machines (ICM) has emerged as a pivotal research direction in the field of visual data compression. However, with the rapid evolution of machine intelligence,…
MedOmni-45°: A Safety-Performance Benchmark for Reasoning-Oriented LLMs in Medicine
Kaiyuan Ji, Yijin Guo, Zicheng Zhang +4
With the increasing use of large language models (LLMs) in medical decision-support, it is essential to evaluate not only their final answers but also the reliability of their reas…
SafetyFlow: An Agent-Flow System for Automated LLM Safety Benchmarking
Xiangyang Zhu, Yuan Tian, Chunyi Li +3
The rapid proliferation of large language models (LLMs) has intensified the requirement for reliable safety evaluation to uncover model vulnerabilities. To this end, numerous LLM s…
SDEval: Safety Dynamic Evaluation for Multimodal Large Language Models
Hanqing Wang, Yuan Tian, Mingyu Liu +2
In the rapidly evolving landscape of Multimodal Large Language Models (MLLMs), the safety concerns of their outputs have earned significant attention. Although numerous datasets ha…