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Pamela Mishkin
Pamela Mishkin
OpenAI
Email verificata su openai.com
Titolo
Citata da
Citata da
Anno
Learning transferable visual models from natural language supervision
A Radford, JW Kim, C Hallacy, A Ramesh, G Goh, S Agarwal, G Sastry, ...
International conference on machine learning, 8748-8763, 2021
248212021
Training language models to follow instructions with human feedback
L Ouyang, J Wu, X Jiang, D Almeida, C Wainwright, P Mishkin, C Zhang, ...
Advances in neural information processing systems 35, 27730-27744, 2022
103022022
Gpt-4 technical report
J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ...
arXiv preprint arXiv:2303.08774, 2023
57272023
Evaluating large language models trained on code
M Chen, J Tworek, H Jun, Q Yuan, HPDO Pinto, J Kaplan, H Edwards, ...
arXiv preprint arXiv:2107.03374, 2021
33102021
Glide: Towards photorealistic image generation and editing with text-guided diffusion models
A Nichol, P Dhariwal, A Ramesh, P Shyam, P Mishkin, B McGrew, ...
arXiv preprint arXiv:2112.10741, 2021
31052021
Gpts are gpts: An early look at the labor market impact potential of large language models
T Eloundou, S Manning, P Mishkin, D Rock
arXiv preprint arXiv:2303.10130, 2023
8702023
Point-e: A system for generating 3d point clouds from complex prompts
A Nichol, H Jun, P Dhariwal, P Mishkin, M Chen
arXiv preprint arXiv:2212.08751, 2022
4412022
Training language models to follow instructions with human feedback, 2022
L Ouyang, J Wu, X Jiang, D Almeida, CL Wainwright, P Mishkin, C Zhang, ...
URL https://arxiv. org/abs/2203.02155 13, 1, 2022
2542022
Training language models to follow instructions with human feedback. arXiv
L Ouyang, J Wu, X Jiang, D Almeida, CL Wainwright, P Mishkin, C Zhang, ...
arXiv preprint arXiv:2203.02155, 2022
1162022
DALL· E: Creating images from text
A Ramesh, M Pavlov, G Goh, S Gray, M Chen, R Child, V Misra, P Mishkin, ...
OpenAI blog 2, 2021
1002021
Learning transferable visual models from natural language supervision. arXiv
A Radford, JW Kim, C Hallacy, A Ramesh, G Goh, S Agarwal, G Sastry, ...
arXiv preprint arXiv:2103.00020, 2021
922021
International conference on machine learning
A Radford, JW Kim, C Hallacy, A Ramesh, G Goh, S Agarwal, G Sastry, ...
PMLR, 2021
582021
Learning Transferable Visual Models From Natural Language Supervision, Feb. 2021
A Radford, JW Kim, C Hallacy, A Ramesh, G Goh, S Agarwal, G Sastry, ...
URL http://arxiv. org/abs/2103.00020, 0
57
GPTs are GPTs: An Early Look at the Labor Market Impact Potential of Large Language Models.” arXiv
T Eloundou, S Manning, P Mishkin, D Rock
arXiv preprint arXiv:2303.10130, 2023
562023
Evaluating large language models trained on code. arXiv 2021
M Chen, J Tworek, H Jun, Q Yuan, HPO Pinto, J Kaplan, H Edwards, ...
arXiv preprint arXiv:2107.03374 10, 2021
552021
Training language models to follow instructions with human feedback, March 2022
L Ouyang, J Wu, X Jiang, D Almeida, CL Wainwright, P Mishkin, C Zhang, ...
URL http://arxiv. org/abs/2203.02155 92, 0
51
DALL·E 2 Preview - Risks and Limitations
P Mishkin, L Ahmad, M Brundage, G Krueger, G Sastry
https://github.com/openai/dalle-2-preview/blob/main/system-card_04062022.md, 2022
432022
Practices for governing agentic AI systems
Y Shavit, S Agarwal, M Brundage, S Adler, C O’Keefe, R Campbell, T Lee, ...
Research Paper, OpenAI, December, 2023
342023
GPTs are GPTs: Labor market impact potential of LLMs
T Eloundou, S Manning, P Mishkin, D Rock
Science 384 (6702), 1306-1308, 2024
302024
A hazard analysis framework for code synthesis large language models
H Khlaaf, P Mishkin, J Achiam, G Krueger, M Brundage
arXiv preprint arXiv:2207.14157, 2022
222022
Il sistema al momento non può eseguire l'operazione. Riprova più tardi.
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