1 citations · 1 across the 4 of their papers we have counts for
4 papers
A PPA-Driven 3D-IC Partitioning Selection Framework with Surrogate Models
Shang Wang, Shuai Liu, Owen Randall +1
3D-IC netlist partitioning is commonly optimized using proxy objectives, while final PPA is treated as a costly evaluation rather than an optimization signal. This proxy-driven par…
The Evolving Landscape of LLM- and VLM-Integrated Reinforcement Learning
Sheila Schoepp, Masoud Jafaripour, Yingyue Cao +6
Reinforcement learning (RL) has shown impressive results in sequential decision-making tasks. Meanwhile, Large Language Models (LLMs) and Vision-Language Models (VLMs) have emerged…
FPGA Divide-and-Conquer Placement using Deep Reinforcement Learning
Shang Wang, Deepak Ranganatha Sastry Mamillapalli, Tianpei Yang +1
This paper introduces the problem of learning to place logic blocks in Field-Programmable Gate Arrays (FPGAs) and a learning-based method. In contrast to previous search-based plac…
LaFFi: Leveraging Hybrid Natural Language Feedback for Fine-tuning Language Models
Qianxi Li, Yingyue Cao, Jikun Kang +4
Fine-tuning Large Language Models (LLMs) adapts a trained model to specific downstream tasks, significantly improving task-specific performance. Supervised Fine-Tuning (SFT) is a c…