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Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph [article]

Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, Xiaoyan Zhu, Minlie Huang
2020 arXiv   pre-print
In this paper, we propose Generation with Multi-Hop Reasoning Flow (GRF) that enables pre-trained models with dynamic multi-hop reasoning on multi-relational paths extracted from the external commonsense  ...  Despite the success of generative pre-trained language models on a series of text generation tasks, they still suffer in cases where reasoning over underlying commonsense knowledge is required during generation  ...  Acknowledgments This work was jointly supported by the NSFC projects (key project with No. 61936010 and regular project with No. 61876096), and the Guoqiang Institute of Tsinghua University with Grant  ... 
arXiv:2009.11692v1 fatcat:kgkqobuexze2ncb3q6mioqnbhe

Language Generation with Multi-Hop Reasoning on Commonsense Knowledge Graph

Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, Xiaoyan Zhu, Minlie Huang
2020 Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)   unpublished
In this paper, we propose Generation with Multi-Hop Reasoning Flow (GRF) that enables pre-trained models with dynamic multi-hop reasoning on multirelational paths extracted from the external commonsense  ...  Despite the success of generative pre-trained language models on a series of text generation tasks, they still suffer in cases where reasoning over underlying commonsense knowledge is required during generation  ...  Acknowledgments This work was jointly supported by the NSFC projects (key project with No. 61936010 and regular project with No. 61876096), and the Guoqiang Institute of Tsinghua University with Grant  ... 
doi:10.18653/v1/2020.emnlp-main.54 fatcat:ud44lmg27fbptovjribqvv6izm

Dynamic Neuro-Symbolic Knowledge Graph Construction for Zero-shot Commonsense Question Answering [article]

Antoine Bosselut, Ronan Le Bras, Yejin Choi
2020 arXiv   pre-print
Therefore, we present a novel approach that generates contextually-relevant symbolic knowledge structures on demand using generative neural commonsense knowledge models.  ...  In this paper, we present initial studies toward zero-shot commonsense question answering by formulating the task as inference over dynamically generated commonsense knowledge graphs.  ...  generating an intermediate commonsense knowledge graph (i.e., reasoning with COMET with no inference hops).  ... 
arXiv:1911.03876v2 fatcat:whj7yqj4tzapvmwhhblirxujgq

Generating Commonsense Explanation by Extracting Bridge Concepts from Reasoning Paths [article]

Haozhe Ji, Pei Ke, Shaohan Huang, Furu Wei, Minlie Huang
2020 arXiv   pre-print
To facilitate the reasoning process, we utilize external commonsense knowledge to build the connection between a statement and the bridge concepts by extracting and pruning multi-hop paths to build a subgraph  ...  We conduct experiments on the commonsense explanation generation task and our model outperforms the state-of-the-art baselines in both automatic and human evaluation.  ...  Acknowledgments This work was jointly supported by the NSFC projects (key project with No. 61936010 and regular project with No. 61876096), and the Guoqiang Institute of Tsinghua University with Grant  ... 
arXiv:2009.11753v1 fatcat:ozuvtlqvkrdm5israbssbv4sja

A Survey on Explainability in Machine Reading Comprehension [article]

Mokanarangan Thayaparan, Marco Valentino, André Freitas
2020 arXiv   pre-print
MultiRC (Khashabi et al., 2018a) combines multi-hop inference with various forms of abstract reasoning such as commonsense, Domain The knowledge domain of the MRC task -i.e. open domain (OD) , science  ...  In parallel with extractive MRC tasks, Graph Networks are applied for answer selection on commonsense reasoning, where a subset of approaches have started exploring the use of explanation graphs extracted  ... 
arXiv:2010.00389v1 fatcat:jzxjysnma5ee5auvplfxxfar2u

CoCoLM: COmplex COmmonsense Enhanced Language Model with Discourse Relations [article]

Changlong Yu, Hongming Zhang, Yangqiu Song, Wilfred Ng
2022 arXiv   pre-print
Different from existing fine-tuning approaches, we do not focus on a specific task and propose a general language model named CoCoLM.  ...  Through the careful training over a large-scale eventuality knowledge graphs ASER, we successfully teach pre-trained language models (i.e., BERT and RoBERTa) rich complex commonsense knowledge among eventualities  ...  Yangqiu Song was supported by the NSFC Fund (U20B2053) from the NSFC of China, the RIF (R6020-19 and R6021-20) and the GRF (16211520) from RGC of Hong Kong, the MHKJFS (MHP/001/19) from ITC of Hong Kong with  ... 
arXiv:2012.15643v2 fatcat:6uvc5kepdvd6tmpx4vrnvf7q3a

MKGN: A Multi-Dimensional Knowledge Enhanced Graph Network for Multi-Hop Question and Answering

Ying ZHANG, Fandong MENG, Jinchao ZHANG, Yufeng CHEN, Jinan XU, Jie ZHOU
2022 IEICE transactions on information and systems  
Machine reading comprehension with multi-hop reasoning always suffers from reasoning path breaking due to the lack of world knowledge, which always results in wrong answer detection.  ...  Based on our analysis, we propose a Multidimensional Knowledge enhanced Graph Network, named MKGN, which exploits specific knowledge to repair the knowledge gap in reasoning process.  ...  which focus on enhancing the representations of questions and contexts and performing implicit multi-hop reasoning with external knowledge and graph neural networks (GNNs) [9] .  ... 
doi:10.1587/transinf.2021edp7154 fatcat:t7zhidxuyjdqpargsqtmdohe6q

Relevant CommonSense Subgraphs for "What if..." Procedural Reasoning [article]

Chen Zheng, Parisa Kordjamshidi
2022 arXiv   pre-print
We propose a novel multi-hop graph reasoning model to 1) efficiently extract a commonsense subgraph with the most relevant information from a large knowledge graph; 2) predict the causal answer by reasoning  ...  We study the challenge of learning causal reasoning over procedural text to answer "What if..." questions when external commonsense knowledge is required.  ...  (I) Multi-Hop Graph Reasoning: this is the Graph Reasoning part of Figure 2-B .  ... 
arXiv:2203.11187v2 fatcat:ol4kqpzjhzetxi2f3npgbfirt4

Open-domain Dialogue Generation Grounded with Dynamic Multi-form Knowledge Fusion [article]

Feifei Xu, Shanlin Zhou, Xinpeng Wang, Yunpu Ma, Wenkai Zhang, Zhisong Li
2022 arXiv   pre-print
then expands the content of the dialogue and its 1st hop using a commonsense knowledge graph to get apposite triples as 2nd hop.  ...  Recently, many approaches based on external knowledge are proposed to generate rich semantic and information conversation.  ...  These commonsense facts can enhance language representation in the commonsense aspect and even expand topics with reasoning by traversing entities and relations.  ... 
arXiv:2204.11239v1 fatcat:7gt6a6yzdnfs3o6vrvo6y4vnnq

Commonsense for Generative Multi-Hop Question Answering Tasks

Lisa Bauer, Yicheng Wang, Mohit Bansal
2018 Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing  
We also show that our background knowledge enhancements are generalizable and improve performance on QAngaroo-WikiHop, another multi-hop reasoning dataset.  ...  This type of multi-step reasoning also often requires understanding implicit relations, which humans resolve via external, background commonsense knowledge.  ...  Figure 1 : 1 Architecture for our Multi-Hop Pointer-Generator Model, and the NOIC commonsense reasoning cell.  ... 
doi:10.18653/v1/d18-1454 dblp:conf/emnlp/BauerWB18 fatcat:w6jkczewqbeq7pxldd6bb4z3t4

Connecting the Dots: A Knowledgeable Path Generator for Commonsense Question Answering [article]

Peifeng Wang, Nanyun Peng, Filip Ilievski, Pedro Szekely, Xiang Ren
2020 arXiv   pre-print
Prior works use commonsense knowledge graphs (KGs) to obtain this knowledge for reasoning.  ...  By extrapolating over existing paths in a KG with a state-of-the-art language model, our generator learns to connect a pair of entities in text with a dynamic, and potentially novel, multi-hop relational  ...  N660011924033 with the United States Office Of Naval Research.  ... 
arXiv:2005.00691v2 fatcat:qshaqmvcy5aitknv62wtqcsfve

Fusing Context Into Knowledge Graph for Commonsense Question Answering [article]

Yichong Xu, Chenguang Zhu, Ruochen Xu, Yang Liu, Michael Zeng, Xuedong Huang
2021 arXiv   pre-print
Many prior methods couple language modeling with knowledge graphs (KG).  ...  This creates a gap when fusing knowledge graphs into language modeling, especially when there is insufficient labeled data.  ...  employs GPT-2 to generate paths between concepts in a knowledge graph, which can dynamically provide multi-hop relations between any pair of concepts.  ... 
arXiv:2012.04808v3 fatcat:3pczpxjzjbashgkuwkphutt37e

Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering [article]

Yanlin Feng, Xinyue Chen, Bill Yuchen Lin, Peifeng Wang, Jun Yan, Xiang Ren
2020 arXiv   pre-print
In this paper, we propose a novel knowledge-aware approach that equips pre-trained language models (PTLMs) with a multi-hop relational reasoning module, named multi-hop graph relation network (MHGRN).  ...  It performs multi-hop, multi-relational reasoning over subgraphs extracted from external knowledge graphs.  ...  Table 2 : 2 Computation complexity of different K-hop reasoning models on a dense/sparse multi-relational graph with n nodes and m relation types.  ... 
arXiv:2005.00646v2 fatcat:7mvyv7233fegpo2ils2wjfmeve

RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge [article]

Bill Yuchen Lin, Ziyi Wu, Yichi Yang, Dong-Ho Lee, Xiang Ren
2021 arXiv   pre-print
Answering such a riddle-style question is a challenging cognitive process, in that it requires complex commonsense reasoning abilities, an understanding of figurative language, and counterfactual reasoning  ...  Herein, we present RiddleSense, a new multiple-choice question answering task, which comes with the first large dataset (5.7k examples) for answering riddle-style commonsense questions.  ...  N660011924033 with the United States Office Of Naval Research, the Defense Advanced Research Projects Agency with award W911NF-19-20271, and NSF SMA 18-29268.  ... 
arXiv:2101.00376v2 fatcat:tn4jpoopvzalfkjkpw2y75js5y

Empathetic response generation through Graph-based Multi-hop Reasoning on Emotional Causality

Jiashuo Wang, Wenjie Li, Peiqin Lin, Feiteng Mu
2021 Knowledge-Based Systems  
Then, we propose a novel graph-based model with multi-hop reasoning to model the emotional causality of the empathetic conversation.  ...  Finally, we demonstrate the effectiveness of our model on EMPATHETICDIALOGUES in comparison with several competitive models.  ...  Dialogue Systems with Multi-hop Reasoning over Commonsense Knowledge Graphs Multi-hop reasoning over external knowledge graphs has been proved an effective approach to involve rich semantic information  ... 
doi:10.1016/j.knosys.2021.107547 fatcat:lrwfsmfajjdydgdz4kbqfjyrsy
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