3 citations · 5 across the 12 of their papers we have counts for
12 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…
Symbol and Footprint Database for Electronic Components by Agentic Recognition and Generation
Yichen Shi, Yuzhi Liu, Zhuofu Tao +4
A rich and recognizable component library is the cornerstone of printed circuit board (PCB) design and generation. Traditionally, engineers manually create symbols and footprints a…
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-q: Unsupervised Circuit Identification and Performance Labeling for AMS Circuits
Ze Zhang, Junzhuo Zhou, Yichen Shi +6
Analog and mixed-signal (AMS) circuit design remains heavily reliant on expert knowledge. While recent AI-driven automation tools can generate candidate topologies, they critically…
CL-VISTA: Benchmarking Continual Learning in Video Large Language Models
Haiyang Guo, Yichen Shi, Fei Zhu +6
Video Large Language Models (Video-LLMs) require continual learning to adapt to non-stationary real-world data. However, existing benchmarks fall short of evaluating modern foundat…
Automated SAR ADC Sizing Using Analytical Equations
Zhongyi Li, Zhuofu Tao, Yanze Zhou +4
Conventional analog and mixed-signal (AMS) circuit designs heavily rely on manual effort, which is time-consuming and labor-intensive. This paper presents a fully automated design…
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…
AMSnet-KG: A Netlist Dataset for LLM-based AMS Circuit Auto-Design Using Knowledge Graph RAG
Yichen Shi, Zhuofu Tao, Yuhao Gao +9
High-performance analog and mixed-signal (AMS) circuits are mainly full-custom designed, which is time-consuming and labor-intensive. A significant portion of the effort is experie…
AMSNet: Netlist Dataset for AMS Circuits
Zhuofu Tao, Yichen Shi, Yiru Huo +8
Today's analog/mixed-signal (AMS) integrated circuit (IC) designs demand substantial manual intervention. The advent of multimodal large language models (MLLMs) has unveiled signif…
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…