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AutoGen is an open-source framework that allows developers to build LLM applications via multiple agents that can converse with each other to accomplish tasks.
Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych · 1908
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The first law of robotics (a call to arms)
Daniel S. Weld and Oren Etzioni · 1994
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Principles of mixed-initiative user interfaces
Eric Horvitz · 1999
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ALFWorld: Aligning Text and Embodied Environments for Interactive Learning
Mohit Shridhar, Xingdi Yuan, Marc-Alexandre Côté, Yonatan Bisk, Adam Trischler, and Matthew Hausknecht · 2010
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Playing atari with deep reinforcement learning
Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, and Martin Riedmiller · 2013
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Concrete problems in ai safety, 2016
Dario Amodei, Chris Olah, Jacob Steinhardt, Paul Christiano, John Schulman, and Dan Mané · 2016
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Deal or no deal? end-to-end learning for negotiation dialogues
Mike Lewis, Denis Yarats, Yann N Dauphin, Devi Parikh, and Dhruv Batra · 2017
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World of bits: An open-domain platform for web-based agents
Tianlin Shi, Andrej Karpathy, Linxi Fan, Jonathan Hernandez, and Percy Liang · 2017
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Starcraft ii: A new challenge for reinforcement learning
Oriol Vinyals, Timo Ewalds, Sergey Bartunov, Petko Georgiev, Alexander Sasha Vezhnevets, Michelle Yeo, Alireza Makhzani, Heinrich Küttler, John Agapiou, Julian Schrittwieser, et al · 2017
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Reinforcement learning on web interfaces using workflow-guided exploration
Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, Tianlin Shi, and Percy Liang · 2018
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Guidelines for human-ai interaction
Saleema Amershi, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, Paul N Bennett, Kori Inkpen, et al · 2019
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”hello ai”: Uncovering the onboarding needs of medical practitioners for human-ai collaborative decision-making
Carrie J. Cai, Samantha Winter, David F. Steiner, Lauren Wilcox, and Michael Terry · 2019
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Natural questions: a benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, et al · 2019
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Retrieval-augmented generation for knowledge-intensive nlp tasks
Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, et al · 2020
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Measuring mathematical problem solving with the math dataset
Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt · 2021
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Retrieval augmented code generation and summarization
Md Rizwan Parvez, Wasi Uddin Ahmad, Saikat Chakraborty, Baishakhi Ray, and Kai-Wei Chang · 2021
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igibson 1.0: A simulation environment for interactive tasks in large realistic scenes
Bokui Shen, Fei Xia, Chengshu Li, Roberto Martín-Martín, Linxi Fan, Guanzhi Wang, Claudia Pérez-D’Arpino, Shyamal Buch, Sanjana Srivastava, Lyne Tchapmi, et al · 2021
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Flaml: A fast and lightweight automl library
Chi Wang, Qingyun Wu, Markus Weimer, and Erkang Zhu · 2021
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LlamaIndex, November 2022
Jerry Liu · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2022
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Guidance
Guidance · 2023
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Sirui Hong, Xiawu Zheng, Jonathan Chen, Yuheng Cheng, Ceyao Zhang, Zili Wang, Steven Ka Shing Yau, Zijuan Lin, Liyang Zhou, Chenyu Ran, et al · 2023
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Transformers agent
HuggingFace · 2023
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Language models can solve computer tasks
Geunwoo Kim, Pierre Baldi, and Stephen McAleer · 2023
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Introduction — langchain
LangChain · 2023
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Encouraging divergent thinking in large language models through multi-agent debate, 2023
Tian Liang, Zhiwei He, Wenxiang Jiao, Xing Wang, Yan Wang, Rui Wang, Yujiu Yang, Zhaopeng Tu, and Shuming Shi · 2023
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Vaibhav Adlakha, Parishad BehnamGhader, Xing Han Lu, Nicholas Meade, and Siva Reddy · 2023
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Documentation — auto-gpt
AutoGPT · 2023
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Github — babyagi
BabyAGI · 2023
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Tianle Cai, Xuezhi Wang, Tengyu Ma, Xinyun Chen, and Denny Zhou · 2023
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Chromadb
Chroma · 2023
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LIDA: A tool for automatic generation of grammar-agnostic visualizations and infographics using large language models
Victor Dibia · 2023
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Self-collaboration code generation via chatgpt
Yihong Dong, Xue Jiang, Zhi Jin, and Ge Li · 2023
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Biases in large language models: Origins, inventory and discussion
Roberto Navigli, Simone Conia, and Björn Ross · 2023
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ChatGPT plugins
OpenAI · 2023
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Generative agents: Interactive simulacra of human behavior
Joon Sung Park, Joseph C O’Brien, Carrie J Cai, Meredith Ringel Morris, Percy Liang, and Michael S Bernstein · 2023
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Gorilla: Large language model connected with massive apis
Shishir G. Patil, Tianjun Zhang, Xin Wang, and Joseph E. Gonzalez · 2023
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Semantic kernel
Semantic-Kernel · 2023
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Langchain problem
Max Woolf · 2023
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An empirical study on challenging math problem solving with gpt-4
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The rise and potential of large language model based agents: A survey
Zhiheng Xi, Wenxiang Chen, Xin Guo, Wei He, Yiwen Ding, Boyang Hong, Ming Zhang, Junzhe Wang, Senjie Jin, Enyu Zhou, et al · 2023
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