Search Results for author: Nathaniel Pinckney

Found 3 papers, 2 papers with code

Revisiting VerilogEval: Newer LLMs, In-Context Learning, and Specification-to-RTL Tasks

1 code implementation • 20 Aug 2024 • Nathaniel Pinckney, Christopher Batten, Mingjie Liu, Haoxing Ren, Brucek Khailany

To address this gap, the open-source VerilogEval benchmark was released in 2023, providing a consistent evaluation framework for LLMs on code completion tasks.

Code Completion Code Generation +2

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ChipNeMo: Domain-Adapted LLMs for Chip Design

no code implementations • 31 Oct 2023 • Mingjie Liu, Teodor-Dumitru Ene, Robert Kirby, Chris Cheng, Nathaniel Pinckney, Rongjian Liang, Jonah Alben, Himyanshu Anand, Sanmitra Banerjee, Ismet Bayraktaroglu, Bonita Bhaskaran, Bryan Catanzaro, Arjun Chaudhuri, Sharon Clay, Bill Dally, Laura Dang, Parikshit Deshpande, Siddhanth Dhodhi, Sameer Halepete, Eric Hill, Jiashang Hu, Sumit Jain, Ankit Jindal, Brucek Khailany, George Kokai, Kishor Kunal, Xiaowei Li, Charley Lind, Hao liu, Stuart Oberman, Sujeet Omar, Ghasem Pasandi, Sreedhar Pratty, Jonathan Raiman, Ambar Sarkar, Zhengjiang Shao, Hanfei Sun, Pratik P Suthar, Varun Tej, Walker Turner, Kaizhe Xu, Haoxing Ren

ChipNeMo aims to explore the applications of large language models (LLMs) for industrial chip design.

Chatbot Domain Adaptation +2

Paper
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VerilogEval: Evaluating Large Language Models for Verilog Code Generation

1 code implementation • 14 Sep 2023 • Mingjie Liu, Nathaniel Pinckney, Brucek Khailany, Haoxing Ren

The increasing popularity of large language models (LLMs) has paved the way for their application in diverse domains.

Benchmarking Code Generation

158

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Code

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