12 papers
VeriPilot: An LLM-Powered Verilog Debugging Framework
Yihan Wang, Cheng Liu, Jiazheng Zhang +4
Verilog debugging remains one of the most time-consuming stages in digital circuit design. Recent advances in Large Language Models (LLMs) have enabled automated debugging; however…
Extracting Training Data from Diffusion Language Models via Infilling
Yihan Wang, N. Asokan
Memorization in large language models has been studied almost exclusively through prefix-conditioned extraction, a natural choice for autoregressive models. However, diffusion lang…
Are Targeted Data Poisoning Attacks as Effective as We Think?
William Xu, Chenyu Zhang, Yihan Wang +5
Targeted data poisoning attacks manipulate model predictions on specific test samples by injecting malicious data into training. Yet existing evaluations report average attack succ…
AnalogRetriever: Learning Cross-Modal Representations for Analog Circuit Retrieval
Yihan Wang, Lei Li, Yao Lai +2
Analog circuit design relies heavily on reusing existing intellectual property (IP), yet searching across heterogeneous representations such as SPICE netlists, schematics, and func…
Towards Robust Content Watermarking Against Removal and Forgery Attacks
Yifan Zhu, Yihan Wang, Xiao-Shan Gao
Generated contents have raised serious concerns about copyright protection, image provenance, and credit attribution. A potential solution for these problems is watermarking. Recen…
Safer by Diffusion, Broken by Context: Diffusion LLM's Safety Blessing and Its Failure Mode
Zeyuan He, Yupeng Chen, Lang Lin +7
Diffusion large language models (D-LLMs) offer an alternative to autoregressive LLMs (AR-LLMs) and have demonstrated advantages in generation efficiency. Beyond the utility benefit…