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Images contain rich relational knowledge that can help machines understand the world.
Automatic ontology-based knowledge extraction from web documents
Harith Alani, Sanghee Kim, David E Millard, Mark J Weal, Wendy Hall, Paul H Lewis, and Nigel R Shadbolt · 2003
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Automatic knowledge extraction from documents
James Fan, Aditya Kalyanpur, David C Gondek, and David A Ferrucci · 2012
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A novel tf-idf weighting scheme for effective ranking
Jiaul H Paik · 2013
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Faster r-cnn: Towards real-time object detection with region proposal networks
Shaoqing Ren, Kaiming He, Ross Girshick, and Jian Sun · 2015
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Viske: Visual knowledge extraction and question answering by visual verification of relation phrases
Fereshteh Sadeghi, Santosh K Kumar Divvala, and Ali Farhadi · 2015
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Densecap: Fully convolutional localization networks for dense captioning
Justin Johnson, Andrej Karpathy, and Li Fei-Fei · 2016
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Visual genome: Connecting language and vision using crowdsourced dense image annotations
Ranjay Krishna, Yuke Zhu, Oliver Groth, Justin Johnson, Kenji Hata, Joshua Kravitz, Stephanie Chen, Yannis Kalantidis, Li-Jia Li, David A Shamma, et al · 2017
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Conceptnet 5.5: An open multilingual graph of general knowledge
Robyn Speer, Joshua Chin, and Catherine Havasi · 2017
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Scene graph generation by iterative message passing
Danfei Xu, Yuke Zhu, Christopher Choy, and Li Fei-Fei · 2017
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Scene graph generation by iterative message passing
Danfei Xu, Yuke Zhu, Christopher B Choy, and Li Fei-Fei · 2017
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Current advances, trends and challenges of machine learning and knowledge extraction: from machine learning to explainable ai
Andreas Holzinger, Peter Kieseberg, Edgar Weippl, and A Min Tjoa · 2018
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Neural motifs: Scene graph parsing with global context
Rowan Zellers, Mark Yatskar, Sam Thomson, and Yejin Choi · 2018
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COMET: commonsense transformers for automatic knowledge graph construction
Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz, and Yejin Choi · 2019
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Dense relational captioning: Triple-stream networks for relationship-based captioning
Dong-Jin Kim, Jinsoo Choi, Tae-Hyun Oh, and In So Kweon · 2019
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Mmkg: multi-modal knowledge graphs
Ye Liu, Hui Li, Alberto Garcia-Duran, Mathias Niepert, Daniel Onoro-Rubio, and David S Rosenblum · 2019
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Decoupled weight decay regularization
Ilya Loshchilov and Frank Hutter · 2019
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Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 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
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Neural text generation with unlikelihood training, 2019
Sean Welleck, Ilia Kulikov, Stephen Roller, Emily Dinan, Kyunghyun Cho, and Jason Weston · 2019
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From recognition to cognition: Visual commonsense reasoning
Rowan Zellers, Yonatan Bisk, Ali Farhadi, and Yejin Choi · 2019
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Gaia: A fine-grained multimedia knowledge extraction system
Manling Li, Alireza Zareian, Ying Lin, Xiaoman Pan, Spencer Whitehead, Brian Chen, Bo Wu, Heng Ji, Shih-Fu Chang, Clare Voss, et al · 2020
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Grounded situation recognition
Sarah Pratt, Mark Yatskar, Luca Weihs, Ali Farhadi, and Aniruddha Kembhavi · 2020
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Vl-bert: Pre-training of generic visual-linguistic representations
Weijie Su, Xizhou Zhu, Yue Cao, Bin Li, Lewei Lu, Furu Wei, and Jifeng Dai · 2020
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Unbiased scene graph generation from biased training
Kaihua Tang, Yulei Niu, Jianqiang Huang, Jiaxin Shi, and Hanwang Zhang · 2020
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Inductive relation prediction by subgraph reasoning
Komal Teru, Etienne Denis, and Will Hamilton · 2020
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Language models are open knowledge graphs
Chenguang Wang, Xiao Liu, and Dawn Song · 2020
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Generative data augmentation for commonsense reasoning
Yiben Yang, Chaitanya Malaviya, Jared Fernandez, Swabha Swayamdipta, Ronan Le Bras, Ji Ping Wang, Chandra Bhagavatula, Yejin Choi, and Doug Downey · 2020
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Bridging knowledge graphs to generate scene graphs
Alireza Zareian, Svebor Karaman, and Shih-Fu Chang · 2020
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Aser: A large-scale eventuality knowledge graph
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa · 2022
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Co-training improves prompt-based learning for large language models
Hunter Lang, Monica N Agrawal, Yoon Kim, and David Sontag · 2022
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BLIP: bootstrapping language-image pre-training for unified vision-language understanding and generation
Junnan Li, Dongxu Li, Caiming Xiong, and Steven C. H. Hoi · 2022
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Quark: Controllable text generation with reinforced unlearning
Ximing Lu, Sean Welleck, Jack Hessel, Liwei Jiang, Lianhui Qin, Peter West, Prithviraj Ammanabrolu, and Yejin Choi · 2022
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Image segmentation using text and image prompts
Timo Lüddecke and Alexander Ecker · 2022
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A contrastive framework for neural text generation
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Hongming Zhang, Xin Liu, Haojie Pan, Yangqiu Song, and Cane Wing-Ki Leung · 2020
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Comprehensive image captioning via scene graph decomposition
Yiwu Zhong, Liwei Wang, Jianshu Chen, Dong Yu, and Yin Li · 2020
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Salkg: Learning from knowledge graph explanations for commonsense reasoning
Aaron Chan, Jiashu Xu, Boyuan Long, Soumya Sanyal, Tanishq Gupta, and Xiang Ren · 2021
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby · 2021
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Making pre-trained language models better few-shot learners
Tianyu Gao, Adam Fisch, and Danqi Chen · 2021
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Zero-shot scene graph relation prediction through commonsense knowledge integration
Xuan Kan, Hejie Cui, and Carl Yang · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Yixuan Su, Tian Lan, Yan Wang, Dani Yogatama, Lingpeng Kong, and Nigel Collier · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou · 2022
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Counterfactual and factual reasoning over hypergraphs for interpretable clinical predictions on ehr
Ran Xu, Yue Yu, Chao Zhang, Mohammed K Ali, Joyce C Ho, and Carl Yang · 2022
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Yue Yu, Rongzhi Zhang, Ran Xu, Jieyu Zhang, Jiaming Shen, and Chao Zhang · 2022
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Star: Bootstrapping reasoning with reasoning
Eric Zelikman, Yuhuai Wu, Jesse Mu, and Noah Goodman · 2022
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Prompt consistency for zero-shot task generalization
Chunting Zhou, Junxian He, Xuezhe Ma, Taylor Berg-Kirkpatrick, and Graham Neubig · 2022
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Conditional prompt learning for vision-language models
Kaiyang Zhou, Jingkang Yang, Chen Change Loy, and Ziwei Liu · 2022
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PV2TEA: Patching visual modality to textual-established information extraction
Hejie Cui, Rongmei Lin, Nasser Zalmout, Chenwei Zhang, Jingbo Shang, Carl Yang, and Xian Li · 2023
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A survey on knowledge graphs for healthcare: Resources, application progress, and promise
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Plausible may not be faithful: Probing object hallucination in vision-language pre-training
Wenliang Dai, Zihan Liu, Ziwei Ji, Dan Su, and Pascale Fung · 2023
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From images to textual prompts: Zero-shot vqa with frozen large language models
Jiaxian Guo, Junnan Li, Dongxu Li, Anthony Meng Huat Tiong, Boyang Li, Dacheng Tao, and Steven CH Hoi · 2023
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Survey of hallucination in natural language generation
Ziwei Ji, Nayeon Lee, Rita Frieske, Tiezheng Yu, Dan Su, Yan Xu, Etsuko Ishii, Ye Jin Bang, Andrea Madotto, and Pascale Fung · 2023
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi · 2023
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Visual classification via description from large language models
Sachit Menon and Carl Vondrick · 2023
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Neighborhood-regularized self-training for learning with few labels
Ran Xu, Yue Yu, Hejie Cui, Xuan Kan, Yanqiao Zhu, Joyce Ho, Chao Zhang, and Carl Yang · 2023
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Weakly-supervised scientific document classification via retrieval-augmented multi-stage training
Ran Xu, Yue Yu, Joyce Ho, and Carl Yang · 2023
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Large language model as attributed training data generator: A tale of diversity and bias
Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, and Chao Zhang · 2023
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