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Chain-of-Thought (CoT) guides large language models (LLMs) to reason step-by-step, and can motivate their logical reasoning ability.
The leap of thinking: A comparison of heidegger and the zen master dogen
Carl Olson · 1981
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Measuring creative thinking: An activity-based approach
Joanna Kitto, David Lok, and Elizabeth Rudowicz · 1994
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Mental leaps: analogy in creative thought
Keith J Holyoak, Paul Thagard, and Stuart Sutherland · 1995
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A review of mental leaps: analogy in creative thought
Douglas Hofstadter · 1995
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Mental leaps: Analogy in creative thought
Keith J Holyoak and Paul Thagard · 1996
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Eeg complexity and performance measures of creative thinking
Matthias Mölle, Lisa Marshall, Britta Wolf, Horst L Fehm, and Jan Born · 1999
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Cumulated gain-based evaluation of ir techniques
Kalervo Järvelin and Jaana Kekäläinen · 2002
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Computational humor
Kim Binsted, Anton Nijholt, Oliviero Stock, Carlo Strapparava, G Ritchie, R Manurung, H Pain, Annalu Waller, and D O’Mara · 2006
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Natural language processing with Python: analyzing text with the natural language toolkit
Steven Bird, Ewan Klein, and Edward Loper · 2009
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Comparing the sensitivity of information retrieval metrics
Filip Radlinski and Nick Craswell · 2010
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Thinking, fast and slow
Daniel Kahneman · 2011
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Mental leap
JungMi Lee · 2012
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Cognitive science: Leap of thought, 2013
Ewen Callaway · 2013
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“let everything turn well in your wife”: generation of adult humor using lexical constraints
Alessandro Valitutti, Hannu Toivonen, Antoine Doucet, and Jukka M Toivanen · 2013
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Development and validation of team creativity measures: A complex systems perspective
Hui Jiang and Qing-pu Zhang · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher D Manning · 2014
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Inside jokes: Identifying humorous cartoon captions
Dafna Shahaf, Eric Horvitz, and Robert Mankoff · 2015
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Scoring divergent thinking tests by computer with a semantics-based algorithm
Kenes Beketayev and Mark A Runco · 2016
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Ranking distillation: Learning compact ranking models with high performance for recommender system
Jiaxi Tang and Ke Wang · 2018
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Gender and the evaluation of humor at work
Jonathan B Evans, Jerel E Slaughter, Aleksander PJ Ellis, and Jessi M Rivin · 2019
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Julian Salazar, Davis Liang, Toan Q Nguyen, and Katrin Kirchhoff · 2019
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Leap-of-thought: Teaching pre-trained models to systematically reason over implicit knowledge
Alon Talmor, Oyvind Tafjord, Peter Clark, Yoav Goldberg, and Jonathan Berant · 2020
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A survey on approaches to computational humor generation
Miriam Amin and Manuel Burghardt · 2020
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Let’s be humorous: Knowledge enhanced humor generation
Hang Zhang, Dayiheng Liu, Jiancheng Lv, and Cheng Luo · 2020
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Stimulating creativity with funlines: A case study of humor generation in headlines
Nabil Hossain, John Krumm, Tanvir Sajed, and Henry Kautz · 2020
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Handwritten optical character recognition (ocr): A comprehensive systematic literature review (slr)
Jamshed Memon, Maira Sami, Rizwan Ahmed Khan, and Mueen Uddin · 2020
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Neural machine translation: A review
Felix Stahlberg · 2020
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A survey of deep learning techniques for neural machine translation
Shuoheng Yang, Yuxin Wang, and Xiaowen Chu · 2020
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le · 2021
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Naming unrelated words predicts creativity
Jay A Olson, Johnny Nahas, Denis Chmoulevitch, Simon J Cropper, and Margaret E Webb · 2021
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Stiffness-aware neural network for learning hamiltonian systems
Senwei Liang, Zhongzhan Huang, and Hong Zhang · 2021
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Story centaur: Large language model few shot learning as a creative writing tool
Ben Swanson, Kory Mathewson, Ben Pietrzak, Sherol Chen, and Monica Dinalescu · 2021
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Mumor: A multimodal dataset for humor detection in conversations
Jiaming Wu, Hongfei Lin, Liang Yang, and Bo Xu · 2021
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“cats be outside, how about meow”: Multimodal humor and creativity in an internet meme
Camilla Vásquez and Erhan Aslan · 2021
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Towards conversational humor analysis and design
Tanishq Chaudhary, Mayank Goel, and Radhika Mamidi · 2021
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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 · 2021
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Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, and Douwe Kiela · 2021
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Data efficient masked language modeling for vision and language
Yonatan Bitton, Gabriel Stanovsky, Michael Elhadad, and Roy Schwartz · 2021
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Tree of thoughts: Deliberate problem solving with large language models, may 2023
Shunyu Yao, Dian Yu, Jeffrey Zhao, Izhak Shafran, Thomas L Griffiths, Yuan Cao, and Karthik Narasimhan · 2023
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Large language model guided tree-of-thought
Jieyi Long · 2023
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Papers and patents are becoming less disruptive over time
Michael Park, Erin Leahey, and Russell J Funk · 2023
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Glossary of owarai terms
Wikimedia · 2023
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Cogvlm: Visual expert for pretrained language models
Weihan Wang, Qingsong Lv, Wenmeng Yu, Wenyi Hong, Ji Qi, Yan Wang, Junhui Ji, Zhuoyi Yang, Lei Zhao, Xixuan Song, Jiazheng Xu, Bin Xu, Juanzi Li, Yuxiao Dong, Ming Ding, and Jie Tang · 2023
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alphaXiv searches the wider corpus for related work and actual follow-ups.
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Guile Wu, Shaogang Gong, and Pan Li · 2021
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Altersgd: Finding flat minima for continual learning by alternative training
Zhongzhan Huang, Mingfu Liang, Senwei Liang, and Wei He · 2021
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al · 2022
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Language models are greedy reasoners: A systematic formal analysis of chain-of-thought
Abulhair Saparov and He He · 2022
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Socratic models: Composing zero-shot multimodal reasoning with language
Andy Zeng, Maria Attarian, Brian Ichter, Krzysztof Choromanski, Adrian Wong, Stefan Welker, Federico Tombari, Aveek Purohit, Michael Ryoo, Vikas Sindhwani, et al · 2022
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Automatic chain of thought prompting in large language models
Zhuosheng Zhang, Aston Zhang, Mu Li, and Alex Smola · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Improved baselines with visual instruction tuning, 2023
Haotian Liu, Chunyuan Li, Yuheng Li, and Yong Jae Lee · 2023
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Minigpt-v2: large language model as a unified interface for vision-language multi-task learning
Jun Chen, Deyao Zhu, Xiaoqian Shen, Xiang Li, Zechu Liu, Pengchuan Zhang, Raghuraman Krishnamoorthi, Vikas Chandra, Yunyang Xiong, and Mohamed Elhoseiny · 2023
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TOA: Task-oriented active VQA
Xiaoying Xing, Mingfu Liang, and Ying Wu · 2023
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Zhan Ling, Yunhao Fang, Xuanlin Li, Tongzhou Mu, Mingu Lee, Reza Pourreza, Roland Memisevic, and Hao Su · 2023
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Brainstorm, then select: a generative language model improves its creativity score
Douglas Summers-Stay, Clare R Voss, and Stephanie M Lukin · 2023
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Inspire creativity with oriba: Transform artists’ original characters into chatbots through large language model
Yuqian Sun, Xingyu Li, Jun Peng, and Ze Gao · 2023
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Cam: A large language model-based creative analogy mining framework
Bhavya Bhavya, Jinjun Xiong, and Chengxiang Zhai · 2023
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On fast simulation of dynamical system with neural vector enhanced numerical solver
Zhongzhan Huang, Senwei Liang, Hong Zhang, Haizhao Yang, and Liang Lin · 2023
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Co-writing screenplays and theatre scripts with language models: Evaluation by industry professionals
Piotr Mirowski, Kory W Mathewson, Jaylen Pittman, and Richard Evans · 2023
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Choice over control: How users write with large language models using diegetic and non-diegetic prompting
Hai Dang, Sven Goller, Florian Lehmann, and Daniel Buschek · 2023
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Funqa: Towards surprising video comprehension
Binzhu Xie, Sicheng Zhang, Zitang Zhou, Bo Li, Yuanhan Zhang, Jack Hessel, Jingkang Yang, and Ziwei Liu · 2023
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Memecap: A dataset for captioning and interpreting memes
EunJeong Hwang and Vered Shwartz · 2023
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Oxfordtvg-hic: Can machine make humorous captions from images?
Runjia Li, Shuyang Sun, Mohamed Elhoseiny, and Philip Torr · 2023
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Does ai have a sense of humor? clef 2023 joker tasks 1, 2 and 3: using bloom, gpt, simplet5, and more for pun detection, location, interpretation and translation
Olga Popova and Petra Dadić · 2023
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Mhadig: A multilingual humor-aided multiparty dialogue generation in multimodal conversational setting
Dushyant Singh Chauhan, Gopendra Vikram Singh, Asif Ekbal, and Pushpak Bhattacharyya · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
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Will large-scale generative models corrupt future datasets?
Ryuichiro Hataya, Han Bao, and Hiromi Arai · 2023
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Model dementia: Generated data makes models forget
Ilia Shumailov, Zakhar Shumaylov, Yiren Zhao, Yarin Gal, Nicolas Papernot, and Ross Anderson · 2023
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Instructblip: Towards general-purpose vision-language models with instruction tuning
Wenliang Dai, Junnan Li, and et al · 2023
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Otter: A multi-modal model with in-context instruction tuning
Bo Li, Yuanhan Zhang, Liangyu Chen, Jinghao Wang, Jingkang Yang, and Ziwei Liu · 2023
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Baichuan 2: Open large-scale language models
Baichuan · 2023
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Do androids laugh at electric sheep? Humor “understanding” benchmarks from The New Yorker Caption Contest
Jack Hessel, Ana Marasović, Jena D. Hwang, Lillian Lee, Jeff Da, Rowan Zellers, Robert Mankoff, and Yejin Choi · 2023
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Scalelong: Towards more stable training of diffusion model via scaling network long skip connection
Zhongzhan Huang, Pan Zhou, Shuicheng YAN, and Liang Lin · 2023
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Exploring compositional visual generation with latent classifier guidance
Changhao Shi, Haomiao Ni, Kai Li, Shaobo Han, Mingfu Liang, and Martin Renqiang Min · 2023
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Trocr: Transformer-based optical character recognition with pre-trained models
Minghao Li, Tengchao Lv, Jingye Chen, Lei Cui, Yijuan Lu, Dinei Florencio, Cha Zhang, Zhoujun Li, and Furu Wei · 2023
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Poisson image editing
Patrick Pérez, Michel Gangnet, and Andrew Blake · 2023
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Investigating the catastrophic forgetting in multimodal large language models
Yuexiang Zhai, Shengbang Tong, Xiao Li, Mu Cai, Qing Qu, Yong Jae Lee, and Yi Ma · 2023
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