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World models, which encapsulate the dynamics of how actions affect environments, are foundational to the functioning of intelligent agents.
Measuring nominal scale agreement among many raters
Joseph L Fleiss. 1971 · 1971
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition
Erik F. Tjong Kim Sang and Fien De Meulder. 2003 · 2003
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Learning high-level planning from text
S.R.K. Branavan, Nate Kushman, Tao Lei, and Regina Barzilay. 2012 · 2012
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Tracking state changes in procedural text: a challenge dataset and models for process paragraph comprehension
Bhavana Dalvi, Lifu Huang, Niket Tandon, Wen-tau Yih, and Peter Clark. 2018 · 2018
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Recurrent world models facilitate policy evolution
David Ha and Jürgen Schmidhuber. 2018 · 2018
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Sentence mover’s similarity: Automatic evaluation for multi-sentence texts
Elizabeth Clark, Asli Celikyilmaz, and Noah A. Smith. 2019 · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter. 2019 · 2019
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Atomic: An atlas of machine commonsense for if-then reasoning
Maarten Sap, Ronan Le Bras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A Smith, and Yejin Choi. 2019 · 2019
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Narrative planning model acquisition from text summaries and descriptions
Thomas Hayton, Julie Porteous, Joao Ferreira, and Alan Lindsay. 2020 · 2020
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Modeling preconditions in text with a crowd-sourced dataset
Heeyoung Kwon, Mahnaz Koupaee, Pratyush Singh, Gargi Sawhney, Anmol Shukla, Keerthi Kumar Kallur, Nathanael Chambers, and Niranjan Balasubramanian. 2020 · 2020
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Planning to explore via self-supervised world models
Ramanan Sekar, Oleh Rybkin, Kostas Daniilidis, Pieter Abbeel, Danijar Hafner, and Deepak Pathak. 2020 · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Cited alongside, same era.
Toward diverse precondition generation
Heeyoung Kwon, Nathanael Chambers, and Niranjan Balasubramanian. 2021 · 2021
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Neurosymbolic Automated Story Generation
Lara J Martin. 2021 · 2021
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World model as a graph: Learning latent landmarks for planning
Lunjun Zhang, Ge Yang, and Bradly C Stadie. 2021 · 2021
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Chatgpt: A large-scale opendomain chatbot
OpenAI. 2022 · 2022
Cited alongside, same era.
PaCo: Preconditions attributed to commonsense knowledge
Ehsan Qasemi, Filip Ilievski, Muhao Chen, and Pedro Szekely. 2022a · 2022
Learning action conditions from instructional manuals for instruction understanding
Te-Lin Wu, Caiqi Zhang, Qingyuan Hu, Alexander Spangher, and Nanyun Peng. 2023 · 2023
Later among the works it cites.
Explainable reinforcement learning via a causal world model
Zhongwei Yu, Jingqing Ruan, and Dengpeng Xing. 2023 · 2023
Later among the works it cites.
How do large language models capture the ever-changing world knowledge? a review of recent advances
Zihan Zhang, Meng Fang, Ling Chen, Mohammad-Reza Namazi-Rad, and Jun Wang. 2023 · 2023
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Berall: Towards generating retrieval-augmented state-based interactive fiction games
Rachel Chambers, Naomi Tack, Eliot Pearson, Lara J Martin, and Francis Ferraro. 2024 · 2024
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Yunxuan Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2024 · 2024
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Cited alongside, same era.
Learning temporally abstractworld models without online experimentation
Benjamin Freed, Siddarth Venkatraman, Guillaume Adrien Sartoretti, Jeff Schneider, and Howie Choset. 2023 · 2023
Cited alongside, same era.
Leveraging pre-trained large language models to construct and utilize world models for model-based task planning
Lin Guan, Karthik Valmeekam, Sarath Sreedharan, and Subbarao Kambhampati. 2023 · 2023
Cited alongside, same era.
Reasoning with language model is planning with world model
Shibo Hao, Yi Gu, Haodi Ma, Joshua Hong, Zhen Wang, Daisy Wang, and Zhiting Hu. 2023 · 2023
Cited alongside, same era.
Do embodied agents dream of pixelated sheep: Embodied decision making using language guided world modelling
Kolby Nottingham, Prithviraj Ammanabrolu, Alane Suhr, Yejin Choi, Hannaneh Hajishirzi, Sameer Singh, and Roy Fox. 2023 · 2023
Cited alongside, same era.
OpenAI, Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Cited alongside, same era.
Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
Cited alongside, same era.
Naruto: Automatically acquiring planning models from narrative texts
Ruiqi Li, Leyang Cui, Songtuan Lin, and Patrik Haslum. 2024 · 2024
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Hello gpt-4o
OpenAI. 2024 · 2024
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Unifying large language models and knowledge graphs: A roadmap
Shirui Pan, Linhao Luo, Yufei Wang, Chen Chen, Jiapu Wang, and Xindong Wu. 2024 · 2024
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Robust agents learn causal world models
Jonathan Richens and Tom Everitt. 2024 · 2024
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Mastering memory tasks with world models
Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran, and Sarath Chandar. 2024 · 2024
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Can language models serve as text-based world simulators?
Ruoyao Wang, Graham Todd, Ziang Xiao, Xingdi Yuan, Marc-Alexandre Côté, Peter Clark, and Peter Jansen. 2024 · 2024
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Language models meet world models: Embodied experiences enhance language models
Jiannan Xiang, Tianhua Tao, Yi Gu, Tianmin Shu, Zirui Wang, Zichao Yang, and Zhiting Hu. 2024 · 2024
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