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Large Language Models(LLMs) have shown remarkable emergent abilities in unifying almost all (if not every) NLP tasks.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Understanding inverse document frequency: on theoretical arguments for idf
Stephen Robertson · 2004
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Cider: Consensus-based image description evaluation
Ramakrishna Vedantam, C Lawrence Zitnick, and Devi Parikh · 2015
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Learning a bidirectional mapping between human whole-body motion and natural language using deep recurrent neural networks
Matthias Plappert, Christian Mandery, and Tamim Asfour · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al · 2019
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, 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, et al · 2020
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Action2motion: Conditioned generation of 3d human motions
Chuan Guo, Xinxin Zuo, Sen Wang, Shihao Zou, Qingyao Sun, Annan Deng, Minglun Gong, and Li Cheng · 2020
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J Liu · 2020
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Action-conditioned 3d human motion synthesis with transformer vae
Mathis Petrovich, Michael J Black, and Gül Varol · 2021
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Infogcn: Representation learning for human skeleton-based action recognition
Hyung-gun Chi, Myoung Hoon Ha, Seunggeun Chi, Sang Wan Lee, Qixing Huang, and Karthik Ramani · 2022
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Tm2t: Stochastic and tokenized modeling for the reciprocal generation of 3d human motions and texts
Chuan Guo, Xinxin Xuo, Sen Wang, and Li Cheng · 2022
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LoRA: Low-rank adaptation of large language models
Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen · 2022
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Language models as zero-shot planners: Extracting actionable knowledge for embodied agents
Wenlong Huang, Pieter Abbeel, Deepak Pathak, and Igor Mordatch · 2022
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Training language models to follow instructions with human feedback, 2022
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Videochat: Chat-centric video understanding
Kunchang Li, Yinan He, Yi Wang, Yizhuo Li, Wenhai Wang, Ping Luo, Yali Wang, Limin Wang, and Yu Qiao · 2023
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Llm+ p: Empowering large language models with optimal planning proficiency
Bo Liu, Yuqian Jiang, Xiaohan Zhang, Qiang Liu, Shiqi Zhang, Joydeep Biswas, and Peter Stone · 2023
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Chatgpt. accessed: 2023-05-15
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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Tmr: Text-to-motion retrieval using contrastive 3d human motion synthesis
Mathis Petrovich, Michael J Black, and Gül Varol · 2023
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Cited alongside, same era.
Temos: Generating diverse human motions from textual descriptions
Mathis Petrovich, Michael J Black, and Gül Varol · 2022
Cited alongside, same era.
A generalist agent, 2022
Scott Reed, Konrad Zolna, Emilio Parisotto, Sergio Gomez Colmenarejo, Alexander Novikov, Gabriel Barth-Maron, Mai Gimenez, Yury Sulsky, Jackie Kay, Jost Tobias Springenberg, Tom Eccles, Jake Bruce, Ali Razavi, Ashley Edwards, Nicolas Heess, Yutian Chen, Raia Hadsell, Oriol Vinyals, Mahyar Bordbar, and Nando de Freitas · 2022
Cited alongside, same era.
Guy Tevet, Sigal Raab, Brian Gordon, Yonatan Shafir, Daniel Cohen-Or, and Amit H Bermano · 2022
Cited alongside, same era.
Finetuned language models are zero-shot learners, 2022
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le · 2022
Cited alongside, same era.
Executing your commands via motion diffusion in latent space
Xin Chen, Biao Jiang, Wen Liu, Zilong Huang, Bin Fu, Tao Chen, and Gang Yu · 2023
Cited alongside, same era.
Motiongpt: Human motion as a foreign language
Biao Jiang, Xin Chen, Wen Liu, Jingyi Yu, Gang Yu, and Tao Chen · 2023
Cited alongside, same era.
Guided motion diffusion for controllable human motion synthesis
Korrawe Karunratanakul, Konpat Preechakul, Supasorn Suwajanakorn, and Siyu Tang · 2023
Cited alongside, same era.
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Human motion diffusion as a generative prior
Yonatan Shafir, Guy Tevet, Roy Kapon, and Amit H Bermano · 2023
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Llm-planner: Few-shot grounded planning for embodied agents with large language models
Chan Hee Song, Jiaman Wu, Clayton Washington, Brian M Sadler, Wei-Lun Chao, and Yu Su · 2023
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Adaplanner: Adaptive planning from feedback with language models, 2023
Haotian Sun, Yuchen Zhuang, Lingkai Kong, Bo Dai, and Chao Zhang · 2023
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Unified human-scene interaction via prompted chain-of-contacts
Zeqi Xiao, Tai Wang, Jingbo Wang, Jinkun Cao, Wenwei Zhang, Bo Dai, Dahua Lin, and Jiangmiao Pang · 2023
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Physdiff: Physics-guided human motion diffusion model
Ye Yuan, Jiaming Song, Umar Iqbal, Arash Vahdat, and Jan Kautz · 2023
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Ude: A unified driving engine for human motion generation
Zixiang Zhou and Baoyuan Wang · 2023
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Motionbert: A unified perspective on learning human motion representations
Wentao Zhu, Xiaoxuan Ma, Zhaoyang Liu, Libin Liu, Wayne Wu, and Yizhou Wang · 2023
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