Fetching the paper…
Reading the bibliography…
Knowledge Graph Question Answering (KGQA) methods seek to answer Natural Language questions using the relational information stored in Knowledge Graphs (KGs).
Socialiqa: Commonsense reasoning about social interactions
Maarten Sap, Hannah Rashkin, Derek Chen, Ronan LeBras, and Yejin Choi. 2019 · 1904
Earlier work this paper cites.
Rql: a declarative query language for rdf
Gregory Karvounarakis, Sofia Alexaki, Vassilis Christophides, Dimitris Plexousakis, and Michel Scholl. 2002 · 2002
Earlier work this paper cites.
Dense passage retrieval for open-domain question answering
Vladimir Karpukhin, Barlas Oğuz, Sewon Min, Patrick Lewis, Ledell Wu, Sergey Edunov, Danqi Chen, and Wen-tau Yih. 2020 · 2004
Earlier work this paper cites.
Protoqa: A question answering dataset for prototypical common-sense reasoning
Michael Boratko, Xiang Lorraine Li, Rajarshi Das, Tim O’Gorman, Dan Le, and Andrew McCallum. 2020 · 2005
Earlier work this paper cites.
Approximate nearest neighbor negative contrastive learning for dense text retrieval
Lee Xiong, Chenyan Xiong, Ye Li, Kwok-Fung Tang, Jialin Liu, Paul Bennett, Junaid Ahmed, and Arnold Overwijk. 2020 · 2007
Earlier work this paper cites.
Sparql query language for rdf. w3c recommendation
Eric Prud’hommeaux and Andy Seaborne. 2008 · 2008
Earlier work this paper cites.
Efficient one-pass end-to-end entity linking for questions
Belinda Z Li, Sewon Min, Srinivasan Iyer, Yashar Mehdad, and Wen-tau Yih. 2020 · 2010
Earlier work this paper cites.
Semantic parsing on freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013a · 2013
Earlier work this paper cites.
Semantic parsing on freebase from question-answer pairs
Jonathan Berant, Andrew Chou, Roy Frostig, and Percy Liang. 2013b · 2013
Earlier work this paper cites.
The value of semantic parse labeling for knowledge base question answering
Wen-tau Yih, Matthew Richardson, Christopher Meek, Ming-Wei Chang, and Jina Suh. 2016 · 2016
Earlier work this paper cites.
Lc-quad: A corpus for complex question answering over knowledge graphs
Priyansh Trivedi, Gaurav Maheshwari, Mohnish Dubey, and Jens Lehmann. 2017 · 2017
Earlier work this paper cites.
Natural language question/answering: Let users talk with the knowledge graph
Weiguo Zheng, Hong Cheng, Lei Zou, Jeffrey Xu Yu, and Kangfei Zhao. 2017 · 2017
Earlier work this paper cites.
Commonsenseqa: A question answering challenge targeting commonsense knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, and Jonathan Berant. 2018 · 2018
Earlier work this paper cites.
Piqa: Reasoning about physical commonsense in natural language
Yonatan Bisk, Rowan Zellers, Jianfeng Gao, Yejin Choi, et al. 2020 · 2020
Earlier work this paper cites.
Mpnet: Masked and permuted pre-training for language understanding
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu. 2020 · 2020
Earlier work this paper cites.
Retrack: A flexible and efficient framework for knowledge base question answering
Shuang Chen, Qian Liu, Zhiwei Yu, Chin-Yew Lin, Jian-Guang Lou, and Feng Jiang. 2021 · 2021
Earlier work this paper cites.
Beyond I.I.D.: three levels of generalization for question answering on knowledge bases
Yu Gu, Sue Kase, Michelle Vanni, Brian M. Sadler, Percy Liang, Xifeng Yan, and Yu Su. 2021 · 2021
Earlier work this paper cites.
A survey on complex knowledge base question answering: Methods, challenges and solutions
Yunshi Lan, Gaole He, Jinhao Jiang, Jing Jiang, Wayne Xin Zhao, and Ji-Rong Wen. 2021 · 2021
Cited alongside, same era.
Generated knowledge prompting for commonsense reasoning
Jiacheng Liu, Alisa Liu, Ximing Lu, Sean Welleck, Peter West, Ronan Le Bras, Yejin Choi, and Hannaneh Hajishirzi. 2021 · 2021
Cited alongside, same era.
CREAK: A dataset for commonsense reasoning over entity knowledge
Yasumasa Onoe, Michael J. Q. Zhang, Eunsol Choi, and Greg Durrett. 2021a · 2021
Cited alongside, same era.
On the generalization abilities of fine-tuned commonsense language representation models
Ke Shen and Mayank Kejriwal. 2021 · 2021
Cited alongside, same era.
Ask me anything: A simple strategy for prompting language models
The future landscape of large language models in medicine
Jan Clusmann, Fiona R Kolbinger, Hannah Sophie Muti, Zunamys I Carrero, Jan-Niklas Eckardt, Narmin Ghaffari Laleh, Chiara Maria Lavinia Löffler, Sophie-Caroline Schwarzkopf, Michaela Unger, Gregory P Veldhuizen, et al. 2023 · 2023
Later among the works it cites.
Evaluating the logical reasoning ability of chatgpt and gpt-4
Hanmeng Liu, Ruoxi Ning, Zhiyang Teng, Jian Liu, Qiji Zhou, and Yue Zhang. 2023 · 2023
Later among the works it cites.
Factscore: Fine-grained atomic evaluation of factual precision in long form text generation
Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, and Hannaneh Hajishirzi. 2023 · 2023
Later among the works it cites.
Robots that ask for help: Uncertainty alignment for large language model planners
Allen Z Ren, Anushri Dixit, Alexandra Bodrova, Sumeet Singh, Stephen Tu, Noah Brown, Peng Xu, Leila Takayama, Fei Xia, Jake Varley, et al. 2023 · 2023
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Simran Arora, Avanika Narayan, Mayee F Chen, Laurel Orr, Neel Guha, Kush Bhatia, Ines Chami, Frederic Sala, and Christopher Ré. 2022 · 2022
Cited alongside, same era.
Refined: An efficient zero-shot-capable approach to end-to-end entity linking
Tom Ayoola, Shubhi Tyagi, Joseph Fisher, Christos Christodoulopoulos, and Andrea Pierleoni. 2022 · 2022
Cited alongside, same era.
Nlp in human rights research: Extracting knowledge graphs about police and army units and their commanders
Daniel Bauer, Tom Longley, Yueen Ma, and Tony Wilson. 2022 · 2022
Cited alongside, same era.
Binding language models in symbolic languages
Zhoujun Cheng, Tianbao Xie, Peng Shi, Chengzu Li, Rahul Nadkarni, Yushi Hu, Caiming Xiong, Dragomir Radev, Mari Ostendorf, Luke Zettlemoyer, et al. 2022 · 2022
Cited alongside, same era.
Yu Gu and Yu Su. 2022 · 2022
Cited alongside, same era.
A medical question answering system using large language models and knowledge graphs
Quan Guo, Shuai Cao, and Zhang Yi. 2022 · 2022
Cited alongside, same era.
Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
Cited alongside, same era.
Tiara: Multi-grained retrieval for robust question answering over large knowledge bases
Yiheng Shu, Zhiwei Yu, Yuhan Li, Börje F Karlsson, Tingting Ma, Yuzhong Qu, and Chin-Yew Lin. 2022 · 2022
Cited alongside, same era.
An experimental study measuring the generalization of fine-tuned language representation models across commonsense reasoning benchmarks
Ke Shen and Mayank Kejriwal. 2023 · 2023
Later among the works it cites.
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 · 2023
Later among the works it cites.
Bayesian knowledge-driven critiquing with indirect evidence
Armin Toroghi, Griffin Floto, Zhenwei Tang, and Scott Sanner. 2023 · 2023
Later among the works it cites.
Car: Conceptualization-augmented reasoner for zero-shot commonsense question answering
Weiqi Wang, Tianqing Fang, Wenxuan Ding, Baixuan Xu, Xin Liu, Yangqiu Song, and Antoine Bosselut. 2023 · 2023
Later among the works it cites.
Yudong Xu, Wenhao Li, Pashootan Vaezipoor, Scott Sanner, and Elias B Khalil. 2023 · 2023
Later among the works it cites.
Cognitive mirage: A review of hallucinations in large language models
Hongbin Ye, Tong Liu, Aijia Zhang, Wei Hua, and Weiqiang Jia. 2023 · 2023
Later among the works it cites.
How well do large language models perform in arithmetic tasks?
Zheng Yuan, Hongyi Yuan, Chuanqi Tan, Wei Wang, and Songfang Huang. 2023 · 2023
Later among the works it cites.
Recipe-mpr: A test collection for evaluating multi-aspect preference-based natural language retrieval
Haochen Zhang, Anton Korikov, Parsa Farinneya, Mohammad Mahdi Abdollah Pour, Manasa Bharadwaj, Ali Pesaranghader, Xi Yu Huang, Yi Xin Lok, Zhaoqi Wang, Nathan Jones, et al. 2023 · 2023
Later among the works it cites.
Willis Guo, Armin Toroghi, and Scott Sanner. 2024 · 2024
Closest in time.
A comprehensive survey of hallucination mitigation techniques in large language models
SM Tonmoy, SM Zaman, Vinija Jain, Anku Rani, Vipula Rawte, Aman Chadha, and Amitava Das. 2024 · 2024
Closest in time.
Bayesian inference with complex knowledge graph evidence
Armin Toroghi and Scott Sanner. 2024 · 2024
Closest in time.
Knowledge graph prompting for multi-document question answering
Yu Wang, Nedim Lipka, Ryan A Rossi, Alexa Siu, Ruiyi Zhang, and Tyler Derr. 2024 · 2024
Closest in time.
Large language models as commonsense knowledge for large-scale task planning
Zirui Zhao, Wee Sun Lee, and David Hsu. 2024 · 2024
Closest in time.