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Evaluating Generative Patent Language Models
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Evaluating Generative Patent Language Models

Jieh-Sheng Lee
    ELM
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Papers citing "Evaluating Generative Patent Language Models"

6 / 6 papers shown
Title
Large Language Models are Zero-Shot Reasoners
Large Language Models are Zero-Shot Reasoners
Takeshi Kojima
S. Gu
Machel Reid
Yutaka Matsuo
Yusuke Iwasawa
ReLMLRM
532
4,077
0
24 May 2022
CodeFill: Multi-token Code Completion by Jointly Learning from Structure and Naming Sequences
CodeFill: Multi-token Code Completion by Jointly Learning from Structure and Naming Sequences
Maliheh Izadi
Roberta Gismondi
Georgios Gousios
76
102
0
14 Feb 2022
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Leo Gao
Stella Biderman
Sid Black
Laurence Golding
Travis Hoppe
...
Horace He
Anish Thite
Noa Nabeshima
Shawn Presser
Connor Leahy
AIMat
476
2,121
0
31 Dec 2020
Prior Art Search and Reranking for Generated Patent Text
Prior Art Search and Reranking for Generated Patent Text
Jieh-Sheng Lee
J. Hsiang
37
12
0
19 Sep 2020
Language Models are Few-Shot Learners
Language Models are Few-Shot Learners
Tom B. Brown
Benjamin Mann
Nick Ryder
Melanie Subbiah
Jared Kaplan
...
Christopher Berner
Sam McCandlish
Alec Radford
Ilya Sutskever
Dario Amodei
BDL
889
42,463
0
28 May 2020
Patent Claim Generation by Fine-Tuning OpenAI GPT-2
Patent Claim Generation by Fine-Tuning OpenAI GPT-2
Jieh-Sheng Lee
J. Hsiang
131
148
0
01 Jul 2019