2 citations · 7 across the 16 of their papers we have counts for
6 papers · 1 filter
ERMoE: Eigen-Reparameterized Mixture-of-Experts for Stable Routing and Interpretable Specialization
Anzhe Cheng, Shukai Duan, Shixuan Li +8
Mixture-of-Experts (MoE) architectures expand model capacity by sparsely activating experts but face two core challenges: misalignment between router logits and each expert's inter…
VeriMoA: A Mixture-of-Agents Framework for Spec-to-HDL Generation
Heng Ping, Arijit Bhattacharjee, Peiyu Zhang +8
Automation of Register Transfer Level (RTL) design can help developers meet increasing computational demands. Large Language Models (LLMs) show promise for Hardware Description Lan…
HGFM: Towards unifying Homogeneity and Heterogeneity on Text-Attributed Graphs
Trung-Kien Nguyen, Heng Ping, Shixuan Li +4
The growing interests and applications of graph learning in diverse domains have propelled the development of a unified model generalizing well across different graphs and tasks, k…
HDLCoRe: A Training-Free Framework for Mitigating Hallucinations in LLM-Generated HDL
Heng Ping, Shixuan Li, Peiyu Zhang +8
Recent advances in large language models (LLMs) have demonstrated remarkable capabilities in code generation tasks. However, when applied to hardware description languages (HDL), t…
MaskAttn-UNet: A Mask Attention-Driven Framework for Universal Low-Resolution Image Segmentation
Anzhe Cheng, Chenzhong Yin, Yu Chang +4
Low-resolution image segmentation is crucial in real-world applications such as robotics, augmented reality, and large-scale scene understanding, where high-resolution data is ofte…
Network-informed Prompt Engineering against Organized Astroturf Campaigns under Extreme Class Imbalance
Nikos Kanakaris, Heng Ping, Xiongye Xiao +4
Detecting organized political campaigns is of paramount importance in fighting against disinformation on social media. Existing approaches for the identification of such organized…