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Recently, there has been a surging interest in using large language models (LLMs) for Verilog code generation.
Attention is all you need
Vaswani et al · 2017
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Improving language understanding by generative pre-training
Radford et al · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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HardFails: Insights into Software-Exploitable hardware bugs
Dessouky et al · 2019
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Curriculum labeling: Revisiting pseudo-labeling for semi-supervised learning
Paola Cascante-Bonilla, Fuwen Tan, Yanjun Qi, and Vicente Ordonez · 2021
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Lamda: Language models for dialog applications
Cohen et al · 2022
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Benchmarking large language models for automated verilog rtl code generation
Thakur et al · 2022
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Invited paper: Verilogeval: Evaluating large language models for verilog code generation
Mingjie Liu, Nathaniel Pinckney, Brucek Khailany, and Haoxing Ren · 2023
Earlier work this paper cites.
Chipgpt: How far are we from natural language hardware design, 2023
Chang et al · 2023
Cited alongside, same era.
Rtllm: An open-source benchmark for design rtl generation with large language model, 2023
Yao Lu, Shang Liu, Qijun Zhang, and Zhiyao Xie · 2023
Cited alongside, same era.
Chip-chat: Challenges and opportunities in conversational hardware design
Jason Blocklove, Siddharth Garg, Ramesh Karri, and Hammond Pearce · 2023
Cited alongside, same era.
Gpt4aigchip: Towards next-generation ai accelerator design automation via large language models, 2023
Fu et al · 2023
Cited alongside, same era.
Chipnemo: Domain-adapted llms for chip design, 2023
Liu et al · 2023
Cited alongside, same era.
Autochip: Automating hdl generation using llm feedback, 2023
Thakur et al · 2023
System-on-chip message flow mining with masked-language models
Md Rubel Ahmed, Bardia Nadimi, and Hao Zheng · 2023
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Codegen: An open large language model for code with multi-turn program synthesis
Nijkamp et al · 2023
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Rtlfixer: Automatically fixing rtl syntax errors with large language models, 2024
Yun-Da Tsai, Mingjie Liu, and Haoxing Ren · 2024
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Rtlcoder: Outperforming gpt-3.5 in design rtl generation with our open-source dataset and lightweight solution, 2024
Liu et al · 2024
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When llm-based code generation meets the software development process, 2024
Feng Lin, Dong Jae Kim, Tse-Husn, and Chen · 2024
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Gemma: Open models based on gemini research and technology, 2024
Mesnard et al · 2024
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Cited alongside, same era.
Improving large language model hardware generating quality through post-LLM search
Chang et al · 2023
Cited alongside, same era.
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A survey on data selection for llm instruction tuning, 2024
Jiahao Wang, Bolin Zhang, Qianlong Du, Jiajun Zhang, and Dianhui Chu · 2024
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