- A Review of Relational Machine Learning for Knowledge Graphs Maximilian Nickel, Kevin Murphy, Volker Tresp, Evgeniy Gabrilovich paper
- What Can Neural Networks Reason About? ICLR 2020 spotlight Keyulu Xu, Jingling Li, Mozhi Zhang, Simon S. Du, Ken-ichi Kawarabayashi, Stefanie Jegelka paper
- On the Capabilities and Limitations of Reasoning for Natural Language Understanding Daniel Khashabi, Erfan Sadeqi Azer, Tushar Khot, Ashish Sabharwal, Dan Roth paper
- Turning 30: New Ideas in Inductive Logic Programming Andrew Cropper, Sebastijan Dumančić, Stephen H. Muggleton paper
- Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden etc. paper
- From Statistical Relational to Neuro-Symbolic Artificial Intelligence Luc De Raedt, Sebastijan Dumanˇci´c , Robin Manhaeve and Giuseppe Marra paper
- Learning an SAT Solver from Single-Bit Supervision Daniel Selsam, Matthew Lamm, Benedikt Bünz, Percy Liang, Leonardo de Moura, David L. Dill 2019 ICLR paper
- SATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solver Po-Wei Wang, Priya L. Donti, Bryan Wilder, Zico Kolter 2019 ICML paper
- ($\partial$ILP) Learning Explanatory Rules from Noisy Data. Richard Evans, Edward Grefenstette. paper
- NLProlog: Reasoning with Weak Unification for Natural Language Question Answering Leon Weber, Pasquale Minervini, Ulf Leser, Tim Rocktäschel ACL 2019 paper
- End-to-End Differentiable Proving Tim Rocktäschel, Sebastian Riedel NIPS 2017 paper
- DeepProbLog: Neural Probabilistic Logic Programming Robin Manhaeve Sebastijan Dumancic, Angelika Kimmig, Thomas Demeester, Luc De Raedt NIPS 2018 paper
- Probabilistic Logic Neural Networks for Reasoning. Meng Qu, Jian Tang. NeurIPS 2019. paper
- Neural Symbolic Reader: Scalable Integration of Distributed and Symbolic Representations for Reading Comprehension. Xinyuan Chen, Chen Liang, Adams Wei Yu, Denny Zhou, Dawn Song, Quoc V. Le ICLR 2020. paper code website note
- A Semantic Loss Function for Deep Learning with Symbolic Knowledge Jingyi Xu, Zilu Zhang, Tal Friedman, Yitao Liang, Guy Van den Broeck ICML 2018. paper
- Neural Module Networks for Reasoning over Text Nitish Gupta1, Kevin Lin2, Dan Roth, Sameer Singh & Matt Gardner ICLR 2020 paper
- Neural Logic Machines Honghua Dong, Jiayuan Mao, Tian Lin, Chong Wang, Lihong Li, Denny Zhou ICLR 2019 paper
- Efficient Probabilistic Logic Reasoning with Graph Neural Networks Yuyu Zhang, Xinshi Chen, Yuan Yang, Arun Ramamurthy, Bo Li, Yuan Qi, Le Song ICLR 2020 paper
- The Logical Expressiveness of Graph Neural Network Pablo Barcelo, Egor V. Kostylev, Mikael Monet, Jorge Perez, Juan Reutter, Juan-Pablo Silva ICLR 2020 paper
- Transformers as Soft Reasoners over Language Peter Clark, Oyvind Tafjord, Kyle Richardson paper demo
- (NLIL) Learn to Explain Efficiently via Neural Logic Inductive Learning Yuan Yang, Le Song ICLR 2020 paper
- Scalable Rule Learning via Learning Representation Pouya Ghiasnezhad Omran, Kewen Wang, Zhe Wang IJCAI 2018 paper
- Generating Logical Forms from Graph Representations of Text and Entities Peter Shaw, Philip Massey, Angelica Chen, Francesco Piccinno, Yasemin Altun ACL 2019 paper
- (NeuralLP) Differentiable Learning of Logical Rules for Knowledge Base Reasoning Fan Yang, Zhilin Yang, William W. Cohen NIPS 2017 paper
- (roundILP) Learning Explanatory Rules from Noisy Data Richard Evans, Edward Grefenstette JAIR 2017 paper
- Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning Wen Zhang, Bibek Paudel, Liang Wang, Jiaoyan Chen, Hai Zhu, Wei Zhang, Abraham Bernstein, Huajun Chen paper
- Differentiable Reasoning on Large Knowledge Bases and Natural Language Pasquale Minervini, Matko Bošnjak, Tim Rocktäschel, Sebastian Riedel, Edward Grefenstette paper
- Addressing a Question Answering Challenge by Combining Statistical Methods with Inductive Rule Learning and Reasoning Arindam Mitra, Chitta Baral AAAI 2016 paper
- Learning to Retrieve Reasoning Paths over Wikipedia Graph for Question Answering Akari Asai, Kazuma Hashimoto, Hannaneh Hajishirzi, Richard Socher, Caiming Xiong. ICLR 2020 paper code
- Transformer-XH: Multi-Evidence Reasoning with eXtra Hop Attention Chen Zhao, Chenyan Xiong, Corby Rosset, Xia Song, Paul Bennett, Saurabh Tiwary. ICLR 2020 paper
- Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs. Ming Tu, Guangtao Wang, Jing Huang, Yun Tang, Xiaodong He, Bowen Zhou. ACL 2019. paper code
- Cognitive Graph for Multi-Hop Reading Comprehension at Scale Ming Ding, Chang Zhou, Qibin Chen, Hongxia Yang, Jie Tang. ACL 2019 paper
- Dynamically Fused Graph Network for Multi-hop Reasoning. Yunxuan Xiao, Yanru Qu, Lin Qiu, Hao Zhou, Lei Li, Weinan Zhang, Yong Yu ACL 2019. paper
- A Multi-Type Multi-Span Network for Reading Comprehension that Requires Discrete Reasoning. Minghao Hu, Yuxing Peng, Zhen Huang, Dongsheng Li. EMNLP 2019. paper code
- Multi-range Reasoning for Machine Comprehension. Yi Tay, Luu Anh Tuan, and Siu Cheung Hui paper
- Differentiable Reasoning Over A Virtual Knowledge Base Bhuwan Dhingra, Manzil Zaheer, Vidhisha Balachandran, Graham Neubig, Ruslan Salakhutdinov1, William W. Cohen. ICLR 2020 paper
- Scalable Neural Methods for Reasoning With a Symbolic Knowledge Base William W. Cohen, Haitian Sun, R. Alex Hofer, Matthew Siegler ICLR 2020 paper
- Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering Sewon Min, Danqi Chen, Luke Zettlemoyer, Hannaneh Hajishirzi paper
- (OpenIE) Leveraging Linguistic Structure For Open Domain Information Extraction Gabor Angeli, Melvin Johnson Premkumar, Christopher D. Manning paper
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Deep Neural Networks with Massive Learned Knowledge Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Eric Xing EMNLP 2016 paper
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Deep Generative Models with Learnable Knowledge Constraints Zhiting Hu, Zichao Yang, Ruslan Salakhutdinov, Xiaodan Liang, Lianhui Qin, Haoye Dong, Eric Xing NIPS 2018 paper
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Toward Controlled Generation of Text Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, Eric P. Xing ICML 2017 paper
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Harnessing Deep Neural Networks with Logic Rules Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, Eric Xing 2016 ACL paper
- GEAR: Graph-based Evidence Aggregating and Reasoning for Fact Verification Jie Zhou, Xu Han, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li, Maosong Sun. ACL 2019 paper
- DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs. Dheeru Dua, Yizhong Wang, Pradeep Dasigi, Gabriel Stanovsky, Sameer Singh, and Matt Gardner. NAACL 2019. paper data website
- (bAbI)Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M. Rush, Bart van Merriënboer, Armand Joulin, Tomas Mikolov ICLR 2016 paper website
- HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering Zhilin Yang, Peng Qi, Saizheng Zhang, Yoshua Bengio, William W. Cohen, Ruslan Salakhutdinov, Christopher D. Manning. EMNLP 2018 paper website
- ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning. Weihao Yu, Zihang Jiang, Yanfei Dong, Jiashi Feng. ICLR 2020. paper code website note
- RC-QED: Evaluating Natural Language Derivations in Multi-Hop Reading Comprehension Naoya Inoue, Pontus Stenetorp, Kentaro Inui paper
- Counterfactual Story Reasoning and Generation Lianhui Qin, Antoine Bosselut, Ari Holtzman, Chandra Bhagavatula, Elizabeth Clark, Yejin Choi EMNLP 2019 paper
- Abductive Commonsense Reasoning Chandra Bhagavatula, Ronan Le Bras, Chaitanya Malaviya, Keisuke Sakaguchi, Ari Holtzman, Hannah Rashkin, Doug Downey, Scott Wen-tau Yih, Yejin Choi paper website
- PIQA: Reasoning about Physical Commonsense in Natural Language. Yonatan Bisk, Rowan Zellers, Ronan Le Bras, Jianfeng Gao, Yejin Choi. AAAI 2020 paper
- CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text. Koustuv Sinha, Shagun Sodhani, Jin Dong, Joelle Pineau, William L. Hamilton EMNLP 2019 paper code website
- COSMOS QA: Machine Reading Comprehension with Contextual Commonsense Reasoning Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi EMNLP 2019 paper website