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Pamela Mishkin
Pamela Mishkin
OpenAI
Bestätigte E-Mail-Adresse bei openai.com
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Zitiert von
Zitiert von
Jahr
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
211482021
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
86702022
Gpt-4 technical report
J Achiam, S Adler, S Agarwal, L Ahmad, I Akkaya, FL Aleman, D Almeida, ...
arXiv preprint arXiv:2303.08774, 2023
34642023
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
27652021
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
27152021
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
7562023
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
3872022
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
2032022
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
972022
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
932021
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
732021
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
502023
International conference on machine learning
A Radford, JW Kim, C Hallacy, A Ramesh, G Goh, S Agarwal, G Sastry, ...
PMLR, 2021
482021
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
422021
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
372022
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
202023
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
182022
GPTs are GPTs: Labor market impact potential of LLMs
T Eloundou, S Manning, P Mishkin, D Rock
Science 384 (6702), 1306-1308, 2024
102024
Contextual Confidence and Generative AI
S Jain, Z Hitzig, P Mishkin
arXiv preprint arXiv:2311.01193, 2023
52023
A research agenda for assessing the economic impacts of code generation models
S Manning, P Mishkin, G Hadfield, T Eloundou, E Eisner
22022
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