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Research.md 4.6 kB

Agent notebook example with human feedback; Support shell command and multiple code blocks; Improve the system message for assistant agent; Improve utility functions for config lists; reuse docker image (#1056) * add agent notebook and documentation * fix bug * set flush to True when printing msg in agent * add a math problem in agent notebook * remove * header * improve notebook doc * notebook update * improve notebook example * improve doc * agent notebook example with user feedback * log * log * improve notebook doc * improve print * doc * human_input_mode * human_input_mode str * indent * indent * Update flaml/autogen/agent/user_proxy_agent.py Co-authored-by: Chi Wang <wang.chi@microsoft.com> * shell command and multiple code blocks * Update notebook/autogen_agent.ipynb Co-authored-by: Chi Wang <wang.chi@microsoft.com> * Update notebook/autogen_agent.ipynb Co-authored-by: Chi Wang <wang.chi@microsoft.com> * Update notebook/autogen_agent.ipynb Co-authored-by: Chi Wang <wang.chi@microsoft.com> * coding agent * math notebook * renaming and doc format * typo * infer lang * sh * docker * docker * reset consecutive autoreply counter * fix explanation * paper talk * human feedback * web info * rename test * config list explanation * link to blogpost * installation * homepage features * features * features * rename agent * remove notebook * notebook test * docker command * notebook update * lang -> cmd * notebook * make it work for gpt-3.5 * return full log * quote * docker * docker * docker * docker * docker * docker image list * notebook * notebook * use_docker * use_docker * use_docker * doc * agent * doc * abs path * pandas * docker * reuse docker image * context window * news * print format * pyspark version in py3.8 * pyspark in py3.8 * pyspark and ray * quote * pyspark * pyspark * pyspark --------- Co-authored-by: Qingyun Wu <qingyun.wu@psu.edu>
3 years ago
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  1. # Research
  2. For technical details, please check our research publications.
  3. * [FLAML: A Fast and Lightweight AutoML Library](https://www.microsoft.com/en-us/research/publication/flaml-a-fast-and-lightweight-automl-library/). Chi Wang, Qingyun Wu, Markus Weimer, Erkang Zhu. MLSys 2021.
  4. ```bibtex
  5. @inproceedings{wang2021flaml,
  6. title={FLAML: A Fast and Lightweight AutoML Library},
  7. author={Chi Wang and Qingyun Wu and Markus Weimer and Erkang Zhu},
  8. year={2021},
  9. booktitle={MLSys},
  10. }
  11. ```
  12. * [Frugal Optimization for Cost-related Hyperparameters](https://arxiv.org/abs/2005.01571). Qingyun Wu, Chi Wang, Silu Huang. AAAI 2021.
  13. ```bibtex
  14. @inproceedings{wu2021cfo,
  15. title={Frugal Optimization for Cost-related Hyperparameters},
  16. author={Qingyun Wu and Chi Wang and Silu Huang},
  17. year={2021},
  18. booktitle={AAAI},
  19. }
  20. ```
  21. * [Economical Hyperparameter Optimization With Blended Search Strategy](https://www.microsoft.com/en-us/research/publication/economical-hyperparameter-optimization-with-blended-search-strategy/). Chi Wang, Qingyun Wu, Silu Huang, Amin Saied. ICLR 2021.
  22. ```bibtex
  23. @inproceedings{wang2021blendsearch,
  24. title={Economical Hyperparameter Optimization With Blended Search Strategy},
  25. author={Chi Wang and Qingyun Wu and Silu Huang and Amin Saied},
  26. year={2021},
  27. booktitle={ICLR},
  28. }
  29. ```
  30. * [An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models](https://aclanthology.org/2021.acl-long.178.pdf). Susan Xueqing Liu, Chi Wang. ACL 2021.
  31. ```bibtex
  32. @inproceedings{liuwang2021hpolm,
  33. title={An Empirical Study on Hyperparameter Optimization for Fine-Tuning Pre-trained Language Models},
  34. author={Susan Xueqing Liu and Chi Wang},
  35. year={2021},
  36. booktitle={ACL},
  37. }
  38. ```
  39. * [ChaCha for Online AutoML](https://www.microsoft.com/en-us/research/publication/chacha-for-online-automl/). Qingyun Wu, Chi Wang, John Langford, Paul Mineiro and Marco Rossi. ICML 2021.
  40. ```bibtex
  41. @inproceedings{wu2021chacha,
  42. title={ChaCha for Online AutoML},
  43. author={Qingyun Wu and Chi Wang and John Langford and Paul Mineiro and Marco Rossi},
  44. year={2021},
  45. booktitle={ICML},
  46. }
  47. ```
  48. * [Fair AutoML](https://arxiv.org/abs/2111.06495). Qingyun Wu, Chi Wang. ArXiv preprint arXiv:2111.06495 (2021).
  49. ```bibtex
  50. @inproceedings{wuwang2021fairautoml,
  51. title={Fair AutoML},
  52. author={Qingyun Wu and Chi Wang},
  53. year={2021},
  54. booktitle={ArXiv preprint arXiv:2111.06495},
  55. }
  56. ```
  57. * [Mining Robust Default Configurations for Resource-constrained AutoML](https://arxiv.org/abs/2202.09927). Moe Kayali, Chi Wang. ArXiv preprint arXiv:2202.09927 (2022).
  58. ```bibtex
  59. @inproceedings{kayaliwang2022default,
  60. title={Mining Robust Default Configurations for Resource-constrained AutoML},
  61. author={Moe Kayali and Chi Wang},
  62. year={2022},
  63. booktitle={ArXiv preprint arXiv:2202.09927},
  64. }
  65. ```
  66. * [Targeted Hyperparameter Optimization with Lexicographic Preferences Over Multiple Objectives](https://openreview.net/forum?id=0Ij9_q567Ma). Shaokun Zhang, Feiran Jia, Chi Wang, Qingyun Wu. ICLR 2023 (notable-top-5%).
  67. ```bibtex
  68. @inproceedings{zhang2023targeted,
  69. title={Targeted Hyperparameter Optimization with Lexicographic Preferences Over Multiple Objectives},
  70. author={Shaokun Zhang and Feiran Jia and Chi Wang and Qingyun Wu},
  71. booktitle={International Conference on Learning Representations},
  72. year={2023},
  73. url={https://openreview.net/forum?id=0Ij9_q567Ma},
  74. }
  75. ```
  76. * [Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference](https://arxiv.org/abs/2303.04673). Chi Wang, Susan Xueqing Liu, Ahmed H. Awadallah. ArXiv preprint arXiv:2303.04673 (2023).
  77. ```bibtex
  78. @inproceedings{wang2023EcoOptiGen,
  79. title={Cost-Effective Hyperparameter Optimization for Large Language Model Generation Inference},
  80. author={Chi Wang and Susan Xueqing Liu and Ahmed H. Awadallah},
  81. year={2023},
  82. booktitle={ArXiv preprint arXiv:2303.04673},
  83. }
  84. ```
  85. * [An Empirical Study on Challenging Math Problem Solving with GPT-4](https://arxiv.org/abs/2306.01337). Yiran Wu, Feiran Jia, Shaokun Zhang, Hangyu Li, Erkang Zhu, Yue Wang, Yin Tat Lee, Richard Peng, Qingyun Wu, Chi Wang. ArXiv preprint arXiv:2306.01337 (2023).
  86. ```bibtex
  87. @inproceedings{wu2023empirical,
  88. title={An Empirical Study on Challenging Math Problem Solving with GPT-4},
  89. author={Yiran Wu and Feiran Jia and Shaokun Zhang and Hangyu Li and Erkang Zhu and Yue Wang and Yin Tat Lee and Richard Peng and Qingyun Wu and Chi Wang},
  90. year={2023},
  91. booktitle={ArXiv preprint arXiv:2306.01337},
  92. }
  93. ```