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Language models (LMs) are powerful yet mostly for text generation tasks.
Learning to parse database queries using inductive logic programming
John M Zelle and Raymond J Mooney · 1996
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Encapsulation is not information hiding
Wm. Paul Rogers · 2001
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Challenges of testing web services and security in soa implementations
Abbie Barbir, Chris Hobbs, Elisa Bertino, Frederick Hirsch, and Lorenzo Martino · 2007
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The probabilistic relevance framework: Bm25 and beyond
Stephen Robertson, Hugo Zaragoza, et al · 2009
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Artificial intelligence a modern approach
Stuart J Russell and Peter Norvig · 2010
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Animal tool behavior: the use and manufacture of tools by animals
Robert W Shumaker, Kristina R Walkup, and Benjamin B Beck · 2011
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Luke S Zettlemoyer and Michael Collins · 2012
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Semantic parsing on freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang · 2013
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Lambda dependency-based compositional semantics
Percy Liang · 2013
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Compositional semantic parsing on semi-structured tables
Panupong Pasupat and Percy Liang · 2015
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Deepcoder: Learning to write programs
Matej Balog, Alexander L Gaunt, Marc Brockschmidt, Sebastian Nowozin, and Daniel Tarlow · 2016
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Triviaqa: A large scale distantly supervised challenge dataset for reading comprehension
Mandar Joshi, Eunsol Choi, Daniel Weld, and Luke Zettlemoyer · 2017
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A syntactic neural model for general-purpose code generation
Pengcheng Yin and Graham Neubig · 2017
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Reinforcement learning on web interfaces using workflow-guided exploration
Evan Zheran Liu, Kelvin Guu, Panupong Pasupat, and Percy Liang · 2018
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Automated api testing
Abhinav Sharma, M Revathi, et al · 2018
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Tao Yu, Rui Zhang, Kai Yang, Michihiro Yasunaga, Dongxu Wang, Zifan Li, James Ma, Irene Li, Qingning Yao, Shanelle Roman, et al · 2018
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Gqa: A new dataset for real-world visual reasoning and compositional question answering
Drew A Hudson and Christopher D Manning · 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, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov · 2019
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A corpus for reasoning about natural language grounded in photographs
Alane Suhr, Stephanie Zhou, Ally Zhang, Iris Zhang, Huajun Bai, and Yoav Artzi · 2019
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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Alfred: A benchmark for interpreting grounded instructions for everyday tasks
Mohit Shridhar, Jesse Thomason, Daniel Gordon, Yonatan Bisk, Winson Han, Roozbeh Mottaghi, Luke Zettlemoyer, and Dieter Fox · 2020
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Ccnet: Extracting high quality monolingual datasets from web crawl data
Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzmán, Armand Joulin, and Edouard Grave · 2020
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Break it down: A question understanding benchmark
Tomer Wolfson, Mor Geva, Ankit Gupta, Matt Gardner, Yoav Goldberg, Daniel Deutch, and Jonathan Berant · 2020
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Evaluating large language models trained on code
Mark Chen, Jerry Tworek, Heewoo Jun, Qiming Yuan, Henrique Ponde de Oliveira Pinto, Jared Kaplan, Harri Edwards, Yuri Burda, Nicholas Joseph, Greg Brockman, et al · 2021
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Simcse: Simple contrastive learning of sentence embeddings
Tianyu Gao, Xingcheng Yao, and Danqi Chen · 2021
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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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Gpt-j-6b: A 6 billion parameter autoregressive language model, 2021
Ben Wang and Aran Komatsuzaki · 2021
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Leveraging language to learn program abstractions and search heuristics
Catherine Wong, Kevin M Ellis, Joshua Tenenbaum, and Jacob Andreas · 2021
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Hitab: A hierarchical table dataset for question answering and natural language generation
Zhoujun Cheng, Haoyu Dong, Zhiruo Wang, Ran Jia, Jiaqi Guo, Yan Gao, Shi Han, Jian-Guang Lou, and Dongmei Zhang · 2022
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Visual programming: Compositional visual reasoning without training
Tanmay Gupta and Aniruddha Kembhavi · 2022
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Internet-augmented dialogue generation
Mojtaba Komeili, Kurt Shuster, and Jason Weston · 2022
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Internet-augmented language models through few-shot prompting for open-domain question answering
Angeliki Lazaridou, Elena Gribovskaya, Wojciech Stokowiec, and Nikolai Grigorev · 2022
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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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Cheng Qian, Chi Han, Yi R. Fung, Yujia Qin, Zhiyuan Liu, and Heng Ji · 2023
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Tool learning with foundation models
Yujia Qin, Shengding Hu, Yankai Lin, Weize Chen, Ning Ding, Ganqu Cui, Zheni Zeng, Yufei Huang, Chaojun Xiao, Chi Han, Yi Ren Fung, Yusheng Su, Huadong Wang, Cheng Qian, Runchu Tian, Kunlun Zhu, Shihao Liang, Xingyu Shen, Bokai Xu, Zhen Zhang, Yining Ye, Bowen Li, Ziwei Tang, Jing Yi, Yuzhang Zhu, Zhenning Dai, Lan Yan, Xin Cong, Yaxi Lu, Weilin Zhao, Yuxiang Huang, Junxi Yan, Xu Han, Xian Sun, Dahai Li, Jason Phang, Cheng Yang, Tongshuang Wu, Heng Ji, Zhiyuan Liu, and Maosong Sun · 2023
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ChatGPT MT: Competitive for high- (but not low-) resource languages
Nathaniel Robinson, Perez Ogayo, David R. Mortensen, and Graham Neubig · 2023
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Talm: Tool augmented language models
Aaron Parisi, Yao Zhao, and Noah Fiedel · 2022
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Progprompt: Generating situated robot task plans using large language models
Ishika Singh, Valts Blukis, Arsalan Mousavian, Ankit Goyal, Danfei Xu, Jonathan Tremblay, Dieter Fox, Jesse Thomason, and Animesh Garg · 2022
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Lamda: Language models for dialog applications
Romal Thoppilan, Daniel De Freitas, Jamie Hall, Noam Shazeer, Apoorv Kulshreshtha, Heng-Tze Cheng, Alicia Jin, Taylor Bos, Leslie Baker, Yu Du, YaGuang Li, Hongrae Lee, Huaixiu Steven Zheng, Amin Ghafouri, Marcelo Menegali, Yanping Huang, Maxim Krikun, Dmitry Lepikhin, James Qin, Dehao Chen, Yuanzhong Xu, Zhifeng Chen, Adam Roberts, Maarten Bosma, Vincent Zhao, Yanqi Zhou, Chung-Ching Chang, Igor Krivokon, Will Rusch, Marc Pickett, Pranesh Srinivasan, Laichee Man, Kathleen Meier-Hellstern, Meredith Ringel Morris, Tulsee Doshi, Renelito Delos Santos, Toju Duke, Johnny Soraker, Ben Zevenbergen, Vinodkumar Prabhakaran, Mark Diaz, Ben Hutchinson, Kristen Olson, Alejandra Molina, Erin Hoffman-John, Josh Lee, Lora Aroyo, Ravi Rajakumar, Alena Butryna, Matthew Lamm, Viktoriya Kuzmina, Joe Fenton, Aaron Cohen, Rachel Bernstein, Ray Kurzweil, Blaise Aguera-Arcas, Claire Cui, Marian Croak, Ed Chi, and Quoc Le · 2022
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Webshop: Towards scalable real-world web interaction with grounded language agents
Shunyu Yao, Howard Chen, John Yang, and Karthik Narasimhan · 2022
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Software testing, 2022
Kinza Yasar · 2022
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Retrieval-based language models and applications
Akari Asai, Sewon Min, Zexuan Zhong, and Danqi Chen · 2023
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Beyond the imitation game: Quantifying and extrapolating the capabilities of language models
BIG bench authors · 2023
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Toolformer: Language models can teach themselves to use tools
Timo Schick, Jane Dwivedi-Yu, Roberto Dessì, Roberta Raileanu, Maria Lomeli, Luke Zettlemoyer, Nicola Cancedda, and Thomas Scialom · 2023
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Vipergpt: Visual inference via python execution for reasoning
Dídac Surís, Sachit Menon, and Carl Vondrick · 2023
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Toolalpaca: Generalized tool learning for language models with 3000 simulated cases
Qiaoyu Tang, Ziliang Deng, Hongyu Lin, Xianpei Han, Qiao Liang, Boxi Cao, and Le Sun · 2023
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Prompt2model: Generating deployable models from natural language instructions
Vijay Viswanathan, Chenyang Zhao, Amanda Bertsch, Tongshuang Wu, and Graham Neubig · 2023
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Voyager: An open-ended embodied agent with large language models
Guanzhi Wang, Yuqi Xie, Yunfan Jiang, Ajay Mandlekar, Chaowei Xiao, Yuke Zhu, Linxi Fan, and Anima Anandkumar · 2023
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Execution-based evaluation for open-domain code generation
Zhiruo Wang, Shuyan Zhou, Daniel Fried, and Graham Neubig · 2023
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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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On the tool manipulation capability of open-source large language models
Qiantong Xu, Fenglu Hong, Bo Li, Changran Hu, Zhengyu Chen, and Jian Zhang · 2023
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Mm-react: Prompting chatgpt for multimodal reasoning and action
Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Ehsan Azarnasab, Faisal Ahmed, Zicheng Liu, Ce Liu, Michael Zeng, and Lijuan Wang · 2023
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik R Narasimhan, and Yuan Cao · 2023
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Language to rewards for robotic skill synthesis
Wenhao Yu, Nimrod Gileadi, Chuyuan Fu, Sean Kirmani, Kuang-Huei Lee, Montse Gonzalez Arenas, Hao-Tien Lewis Chiang, Tom Erez, Leonard Hasenclever, Jan Humplik, et al · 2023
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Craft: Customizing llms by creating and retrieving from specialized toolsets
Lifan Yuan, Yangyi Chen, Xingyao Wang, Yi R. Fung, Hao Peng, and Heng Ji · 2023
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Toolcoder: Teach code generation models to use api search tools
Kechi Zhang, Huangzhao Zhang, Ge Li, Jia Li, Zhuo Li, and Zhi Jin · 2023
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Docprompting: Generating code by retrieving the docs
Shuyan Zhou, Uri Alon, Frank F. Xu, Zhiruo Wang, Zhengbao Jiang, and Graham Neubig · 2023
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Toolqa: A dataset for llm question answering with external tools
Yuchen Zhuang, Yue Yu, Kuan Wang, Haotian Sun, and Chao Zhang · 2023
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Metatool benchmark for large language models: Deciding whether to use tools and which to use
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Regal: Refactoring programs to discover generalizable abstractions
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Webarena: A realistic web environment for building autonomous agents
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