人間のフィードバックによる強化学習 (Japanese Wikipedia)

Analysis of information sources in references of the Wikipedia article "人間のフィードバックによる強化学習" in Japanese language version.

refsWebsite

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6arxiv.org

69^th place

227^th place

2huggingface.co

low place

2openreview.net

low place

2techcrunch.com

187^th place

440^th place

2openai.com

1,559^th place

1,682^nd place

1acm.org

1,185^th place

2,667^th place

1doi.org

2^nd place

6^th place

1arstechnica.com

388^th place

1,331^st place

1venturebeat.com

616^th place

2,168^th place

1neurips.cc

low place

1deepmind.com

low place

1nips.cc

low place

1alignmentforum.org

low place

1springer.com

274^th place

596^th place

1princeton.edu

741^st place

1,856^th place

1ibm.com

1,131^st place

838^th place

acm.org

dl.acm.org

MacGlashan, James; Ho, Mark K; Loftin, Robert; Peng, Bei; Wang, Guan; Roberts, David L.; Taylor, Matthew E.; Littman, Michael L. (6 August 2017). “Interactive learning from policy-dependent human feedback”. Proceedings of the 34th International Conference on Machine Learning - Volume 70 (JMLR.org): 2285–2294. arXiv:1701.06049.
- Warnell, Garrett; Waytowich, Nicholas; Lawhern, Vernon; Stone, Peter (25 April 2018). “Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces”. Proceedings of the AAAI Conference on Artificial Intelligence 32 (1). doi:10.1609/aaai.v32i1.11485.

alignmentforum.org

“Thoughts on the impact of RLHF research” (英語). 2023年3月4日閲覧。

arstechnica.com

“OpenAI invites everyone to test ChatGPT, a new AI-powered chatbot—with amusing results” (英語). Ars Technica (2022年12月1日). 2023年3月4日閲覧。

arxiv.org

Ziegler, Daniel M.; Stiennon, Nisan; Wu, Jeffrey; Brown, Tom B.; Radford, Alec; Amodei, Dario; Christiano, Paul; Irving, Geoffrey (2019). Fine-Tuning Language Models from Human Preferences. arXiv:1909.08593.
MacGlashan, James; Ho, Mark K; Loftin, Robert; Peng, Bei; Wang, Guan; Roberts, David L.; Taylor, Matthew E.; Littman, Michael L. (6 August 2017). “Interactive learning from policy-dependent human feedback”. Proceedings of the 34th International Conference on Machine Learning - Volume 70 (JMLR.org): 2285–2294. arXiv:1701.06049.
- Warnell, Garrett; Waytowich, Nicholas; Lawhern, Vernon; Stone, Peter (25 April 2018). “Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces”. Proceedings of the AAAI Conference on Artificial Intelligence 32 (1). doi:10.1609/aaai.v32i1.11485.
- Ouyang, Long; Wu, Jeffrey; Jiang, Xu; Almeida, Diogo; Wainwright, Carroll; Mishkin, Pamela; Zhang, Chong; Agarwal, Sandhini et al. (31 October 2022) (英語). Training language models to follow instructions with human feedback. arXiv:2203.02155.
- Patrick Fernandes, Aman Madaan, Emmy Liu, António Farinhas, Pedro Henrique Martins, Amanda Bertsch, José G. C. de Souza, Shuyan Zhou, Tongshuang Wu, Graham Neubig, André F. T. Martins. “Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation”. arXiv:2305.00955.{{cite arXiv}}: CS1メンテナンス: authors引数 (カテゴリ)
- Ouyang, Long; Wu, Jeff; Jiang, Xu; Almeida, Diogo; Wainwright, Carroll L.; Mishkin, Pamela; Zhang, Chong; Agarwal, Sandhini et al. (2022). Training language models to follow instructions with human feedback. arXiv:2203.02155.
  - Nisan, Stiennon; Long, Ouyang; Jeffrey, Wu; Daniel, Ziegler; Ryan, Lowe; Chelsea, Voss; Alec, Radford; Dario, Amodei et al. (2020). “Learning to summarize with human feedback” (英語). Advances in Neural Information Processing Systems 33.
  - Glaese, Amelia; McAleese, Nat; Trębacz, Maja; Aslanides, John; Firoiu, Vlad; Ewalds, Timo; Rauh, Maribeth; Weidinger, Laura et al. (2022). Improving alignment of dialogue agents via targeted human judgements. arXiv:2209.14375.

deepmind.com

“Learning through human feedback” (英語). www.deepmind.com. 2023年3月4日閲覧。

doi.org

MacGlashan, James; Ho, Mark K; Loftin, Robert; Peng, Bei; Wang, Guan; Roberts, David L.; Taylor, Matthew E.; Littman, Michael L. (6 August 2017). “Interactive learning from policy-dependent human feedback”. Proceedings of the 34th International Conference on Machine Learning - Volume 70 (JMLR.org): 2285–2294. arXiv:1701.06049.
- Warnell, Garrett; Waytowich, Nicholas; Lawhern, Vernon; Stone, Peter (25 April 2018). “Deep TAMER: Interactive Agent Shaping in High-Dimensional State Spaces”. Proceedings of the AAAI Conference on Artificial Intelligence 32 (1). doi:10.1609/aaai.v32i1.11485.

huggingface.co

“Illustrating Reinforcement Learning from Human Feedback (RLHF)”. huggingface.co. 2023年3月4日閲覧。
“Illustrating Reinforcement Learning from Human Feedback (RLHF)”. Hugging Face. 2023年7月2日閲覧。

ibm.com

“What is overfitting?”. IBM. 2023年7月2日閲覧。

neurips.cc

proceedings.neurips.cc

Ouyang, Long; Wu, Jeff; Jiang, Xu; Almeida, Diogo; Wainwright, Carroll L.; Mishkin, Pamela; Zhang, Chong; Agarwal, Sandhini et al. (2022). Training language models to follow instructions with human feedback. arXiv:2203.02155.
- Nisan, Stiennon; Long, Ouyang; Jeffrey, Wu; Daniel, Ziegler; Ryan, Lowe; Chelsea, Voss; Alec, Radford; Dario, Amodei et al. (2020). “Learning to summarize with human feedback” (英語). Advances in Neural Information Processing Systems 33.

nips.cc

papers.nips.cc

Christiano, Paul F; Leike, Jan; Brown, Tom; Martic, Miljan; Legg, Shane; Amodei, Dario (2017). “Deep Reinforcement Learning from Human Preferences”. Advances in Neural Information Processing Systems (Curran Associates, Inc.) 30 2023年3月4日閲覧。.

openai.com

“Learning from human preferences”. openai.com. 2023年3月4日閲覧。
“Faulty reward functions in the wild”. OpenAI. 2023年7月2日閲覧。

openreview.net

Ouyang, Long; Wu, Jeffrey; Jiang, Xu; Almeida, Diogo; Wainwright, Carroll; Mishkin, Pamela; Zhang, Chong; Agarwal, Sandhini et al. (31 October 2022) (英語). Training language models to follow instructions with human feedback. arXiv:2203.02155.
“Understanding deep learning requires rethinking generalization”. International Conference on Learning Representations. 2023年7月2日閲覧。

princeton.edu

cs.princeton.edu

“Training Language Models to Follow Instructions with Human Feedback”. Princeton. 2023年7月2日閲覧。

springer.com

link.springer.com

Belenguer, Lorenzo (2022年). “AI bias: exploring discriminatory algorithmic decision-making models and the application of possible machine-centric solutions adapted from the pharmaceutical industry”. AI Ethics

techcrunch.com

“Can AI really be protected from text-based attacks?”. TechCrunch (2023年2月24日). 2023年3月4日閲覧。
“Can AI really be protected from text-based attacks?”. TechCrunch (2023年2月24日). 2023年3月4日閲覧。

venturebeat.com

“Getting stakeholder engagement right in responsible AI”. VentureBeat (2023年2月5日). 2023年3月4日閲覧。