6 citations · 10 across the 7 of their papers we have counts for
7 papers
FAS-R1: A Unified Multi-Task MLLM for Reasoning Face Anti-Spoofing
Hongyang Wang, Yichen Shi, Hongrui Li +3
Face anti-spoofing (FAS) is increasingly expected to provide not only bona fide/spoof decisions, but also attack semantics and image-grounded evidence for human inspection. Existin…
UniShield: Unified Face Attack Detection via KG-Informed Multimodal Reasoning
Hongrui Li, Yichen Shi, Hongyang Wang +4
Unified face attack detection (UAD) requires recognizing physical spoofing and digital forgery within a shared decision space, yet existing discriminative or prompt-based methods l…
AMSnet 2.0: A Large AMS Database with AI Segmentation for Net Detection
Yichen Shi, Zhuofu Tao, Yuhao Gao +5
Current multimodal large language models (MLLMs) struggle to understand circuit schematics due to their limited recognition capabilities. This could be attributed to the lack of hi…
AMSbench: A Comprehensive Benchmark for Evaluating MLLM Capabilities in AMS Circuits
Yichen Shi, Ze Zhang, Hongyang Wang +10
Analog/Mixed-Signal (AMS) circuits play a critical role in the integrated circuit (IC) industry. However, automating Analog/Mixed-Signal (AMS) circuit design has remained a longsta…
FaceShield: Explainable Face Anti-Spoofing with Multimodal Large Language Models
Hongyang Wang, Yichen Shi, Zhuofu Tao +7
Face anti-spoofing (FAS) is crucial for protecting facial recognition systems from presentation attacks. Previous methods approached this task as a classification problem, lacking…
GM-DF: Generalized Multi-Scenario Deepfake Detection
Yingxin Lai, Zitong Yu, Jing Yang +3
Existing face forgery detection usually follows the paradigm of training models in a single domain, which leads to limited generalization capacity when unseen scenarios and unknown…
SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models
Yichen Shi, Yuhao Gao, Yingxin Lai +7
Multimodal large language models (MLLMs) have demonstrated strong capabilities in vision-related tasks, capitalizing on their visual semantic comprehension and reasoning capabiliti…