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A Survey on Multi-hop Question Answering and Generation
[article]
2022
arXiv
pre-print
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The ability to answer multi-hop questions and perform multi step reasoning can significantly improve the utility of NLP systems. ...
The notion of 'multiple hops' is somewhat abstract which results in a large variety of tasks that require multi-hop reasoning. ...
[79] tackle the problem of difficulty controllable question generation (DQG) [44] by generating questions which require a particular number of reasoning hops. ...
arXiv:2204.09140v1
fatcat:tqr6472sjrfpvollvapwo3z3x4
Question-Aware Memory Network for Multi-hop Question Answering in Human-Robot Interaction
[article]
2021
arXiv
pre-print
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We evaluate QA2MN on PathQuestion and WorldCup2014, two representative datasets for complex multi-hop question answering. ...
Knowledge graph question answering is an important technology in intelligent human-robot interaction, which aims at automatically giving answer to human natural language question with the given knowledge ...
For multi-hop question, Xu et al. ...
arXiv:2104.13173v1
fatcat:3v43jnf74rfyzi2x54df7vpk5i
Multi-hop Inference for Sentence-level TextGraphs: How Challenging is Meaningfully Combining Information for Science Question Answering?
2018
Proceedings of the Twelfth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-12)
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judgements across knowledge graphs built from three freetext corpora (including study guides and Simple Wikipedia). ...
Question Answering for complex questions is often modelled as a graph construction or traversal task, where a solver must build or traverse a graph of facts that answer and explain a given question. ...
Information aggregation or "multi-hop" graph traversal has been shown to be extremely challenging, with QA solvers generally showing only modest performance benefits when aggregating information, and diminishing ...
doi:10.18653/v1/w18-1703
dblp:conf/textgraphs/Jansen18
fatcat:affa552ayfauvhkjxl3mhaxvt4
Few-shot Multi-hop Question Answering over Knowledge Base
[article]
2022
arXiv
pre-print
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Besides, we propose a data generation strategy, which enables our model to generalize well from few training samples. ...
KBQA is a task that requires to answer questions by using semantic structured information in knowledge base. ...
Beam Search It is worth to notice that when extending multi-hop relations of the two type questions above, Query Path Generation module often suffers from the vast searching space. ...
arXiv:2112.11909v2
fatcat:6thbal5nureldcishdwrovoyae
Answering Any-hop Open-domain Questions with Iterative Document Reranking
[article]
2021
arXiv
pre-print
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2021 pre-print arXiv:2009.07465v4 fatcat:xoaaxvnjnbcpjlzma7kz2ou3liOther Versions
Existing approaches for open-domain question answering (QA) are typically designed for questions that require either single-hop or multi-hop reasoning, which make strong assumptions of the complexity of ...
Our method consistently achieves performance comparable to or better than the state-of-the-art on both single-hop and multi-hop open-domain QA datasets, including Natural Questions Open, SQuAD Open, and ...
To the
best of our knowledge, we are the first to propose graph-based
document reranking method for open-domain multi-hop QA.
2 OVERVIEW
2.1 Problem Definition
Given a factoid question, the task ...
arXiv:2009.07465v5
fatcat:m3hosnzbwvdx3k3g7x7tlm5zhi
UHop: An Unrestricted-Hop Relation Extraction Framework for Knowledge-Based Question Answering
[article]
2019
arXiv
pre-print
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In related work, an exhaustive search from all one-hop relations, two-hop relations, and so on to the max-hop relations in the knowledge graph is necessary but expensive. ...
In relation extraction for knowledge-based question answering, searching from one entity to another entity via a single relation is called "one hop". ...
Figure 1 shows the difference between previous work and our model in the scenario of multi-hop KBQA task with an simplified knowledge graph and the question "Who published the novel adapted into A Study ...
arXiv:1904.01246v1
fatcat:ham6ahicdzc33cgx6ib442rp6u
KQA Pro: A Dataset with Explicit Compositional Programs for Complex Question Answering over Knowledge Base
[article]
2022
arXiv
pre-print
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Complex question answering over knowledge base (Complex KBQA) is challenging because it requires various compositional reasoning capabilities, such as multi-hop inference, attribute comparison, set operation ...
Our codes and datasets can be obtained from https://github.com/shijx12/KQAPro_Baselines. ...
EmbedKGQA utilizes knowledge graph embedding to improve multi-hop reasoning. ...
arXiv:2007.03875v3
fatcat:otqbqpbsore7xjmz6rj6i5ncdq
Multi-hop Inference for Sentence-level TextGraphs: How Challenging is Meaningfully Combining Information for Science Question Answering?
[article]
2018
arXiv
pre-print
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judgments across knowledge graphs built from three free-text corpora (including study guides and Simple Wikipedia). ...
Question Answering for complex questions is often modeled as a graph construction or traversal task, where a solver must build or traverse a graph of facts that answer and explain a given question. ...
Information aggregation or "multi-hop" graph traversal has been shown to be extremely challenging, with QA solvers generally showing only modest performance benefits when aggregating information, and diminishing ...
arXiv:1805.11267v1
fatcat:mujrhpg6drdpbngz3e6cuuliiy
An Intelligent Question Answering System based on Power Knowledge Graph
[article]
2021
arXiv
pre-print
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This method thoroughly combined knowledge graph and graph computing characteristics, realized high-speed multi-hop knowledge correlation reasoning analysis in tremendous knowledge. ...
This article introduced a domain knowledge graph using the graph database and graph computing technologies from massive heterogeneous data in electric power. ...
In terms of graph traversal, the tested queries cover 10 single-hop and 190 multi-hop queries; in terms of restriction conditions, the tested queries cover 20 single-condition and 180 multi-condition queries ...
arXiv:2106.09013v1
fatcat:xw4hnpu4dzh3bbrd4s76kphcxy
GMH: A General Multi-hop Reasoning Model for KG Completion
[article]
2021
arXiv
pre-print
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To the best of our knowledge, there lacks a general framework that approaches multi-hop reasoning in mixed long-short distance reasoning scenarios. ...
We argue that there are two key issues for a general multi-hop reasoning model: i) where to go, and ii) when to stop. ...
Second, the global knowledge learnt from graph structure, which has been overlooked by the existing multi-hop reasoning models, is incorporated in GMH. ...
arXiv:2010.07620v3
fatcat:d56bqdmtcfeppdfoevlwjmruei
Cooperative Reasoning on Knowledge Graph and Corpus: A Multi-agentReinforcement Learning Approach
[article]
2019
arXiv
pre-print
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Each agent learns its skill to complete its own task, hopping on KG or select knowledge from the corpus, via maximizing the reward for correctly answering the question. ...
However, previous methods suffer from the incompleteness of the knowledge graph, namely the interested link or entity that can be missing in the knowledge graph(explicit missing). ...
Related Work We now review related work in the directions of knowledge graph reasoning, multi-agent reinforcement learning, and fusion of KB and texts for question answering. ...
arXiv:1912.02206v1
fatcat:l6oks5pidzfnxiavb3m37py5cm
GraphDialog: Integrating Graph Knowledge into End-to-End Task-Oriented Dialogue Systems
[article]
2020
arXiv
pre-print
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To exploit the relations between entities in KBs, the model combines multi-hop reasoning ability based on the graph structure. ...
End-to-end task-oriented dialogue systems aim to generate system responses directly from plain text inputs. ...
Acknowledgements We would like to thank Bayu Distiawan Trisedya for his insightful discussions and the valuable feedbacks from all anonymous reviewers. ...
arXiv:2010.01447v1
fatcat:ubmh2rloqfdo7h3gpi4oueyvn4
Neural, Symbolic and Neural-Symbolic Reasoning on Knowledge Graphs
[article]
2021
arXiv
pre-print
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We survey two specific reasoning tasks, knowledge graph completion and question answering on knowledge graphs, and explain them in a unified reasoning framework. ...
Since knowledge graphs can be viewed as the discrete symbolic representations of knowledge, reasoning on knowledge graphs can naturally leverage the symbolic techniques. ...
Symbolic Reasoning Symbolic reasoning aims at deducing general logic rules from the knowledge graphs. ...
arXiv:2010.05446v5
fatcat:tc6fowebkzbv7df3cjyhkcu6uq
Stabilizing Adversarial Invariance Induction from Divergence Minimization Perspective
2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
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This paper presents an analysis of the reasons for the optimization difficulties and provides a better optimization procedure by rethinking AII from a divergence minimization perspective. ...
Adversarial invariance induction (AII) is a generic and powerful framework for enforcing an invariance to nuisance attributes into neural network representations. ...
Our contributions are summarized as flows: • We address the multiple semantic issue where a relation in knowledge graph has different meanings on multi-hop knowledge graph reasoning, which is an essential ...
doi:10.24963/ijcai.2020/267
dblp:conf/ijcai/WanP00H20
fatcat:zfhotcefyfgqljabsvtu6iwj3y
HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification
[article]
2020
arXiv
pre-print
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In HoVer, the claims require evidence to be extracted from as many as four English Wikipedia articles and embody reasoning graphs of diverse shapes. ...
many-hop reasoning to achieve strong results. ...
WorldTree:
A corpus of explanation graphs for elementary sci-
ence questions supporting multi-hop inference. ...
arXiv:2011.03088v2
fatcat:wtwwko4bxbfuta3cnk3usxcdy4
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