4 citations · 18 across the 25 of their papers we have counts for
8 papers · 1 filter
SpecLens: LLM-Based Verilog Generation with Specification-Derived Constraints via Behavioral Divergence
Wen Bing, Bing Li
Large language models (LLMs) have recently shown promise in Verilog generation, but producing functionally correct RTL directly from natural-language specifications remains a highl…
DiffLUT-Net: Differentiable Training of FPGA LUT Networks with Learnable Connectivity
Jiaqi Ye, Xinrui Gong, Jingcun Wang +3
Field-programmable gate arrays (FPGAs) enable efficient neural-network inference, but most deployment flows either accelerate multiply-accumulate operations or convert pretrained q…
VClare: Resolving Imperfect Specifications in LLM-Based Verilog Generation
Zhuorui Zhao, Bing Li, Yu Li +2
Large language models (LLMs) have demonstrated promising capabilities in generating Verilog code from natural language specifications. However, human-written specifications often c…
LLM for EDA in Front-End Design: Challenges and Opportunities
Kangwei Xu, Bing Li, Ulf Schlichtmann
As chip complexity increases and time-to-market pressures grow, front-end design has become a critical bottleneck in chip development. Recently, Large Language Models (LLMs) have s…
CompressKV: Semantic-Retrieval-Guided KV-Cache Compression for Resource-Efficient Long-Context LLM Inference
Xiaolin Lin, Jingcun Wang, Olga Kondrateva +3
Long-context large language model (LLM) inference is increasingly constrained by the memory footprint and decoding cost of key-value (KV) caches, limiting sustainable deployment on…
KV Packet: Recomputation-Free Context-Independent KV Caching for LLMs
Chuangtao Chen, Grace Li Zhang, Xunzhao Yin +3
Large Language Models (LLMs) rely heavily on Key-Value (KV) caching to minimize inference latency. However, standard KV caches are context-dependent: reusing a cached document in a…
Seedance 2.0: Advancing Video Generation for World Complexity
Team Seedance, De Chen, Liyang Chen +168
Seedance 2.0 is a new native multi-modal audio-video generation model, officially released in China in early February 2026. Compared with its predecessors, Seedance 1.0 and 1.5 Pro…
Late Breaking Results: Conversion of Neural Networks into Logic Flows for Edge Computing
Daniel Stein, Shaoyi Huang, Rolf Drechsler +2
Neural networks have been successfully applied in various resource-constrained edge devices, where usually central processing units (CPUs) instead of graphics processing units exis…