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Unsupervised Expressive Rules Provide Explainability and Assist Human
  Experts Grasping New Domains

Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains

19 October 2020
Eyal Shnarch
Leshem Choshen
Guy Moshkowich
Noam Slonim
R. Aharonov
ArXivPDFHTML

Papers citing "Unsupervised Expressive Rules Provide Explainability and Assist Human Experts Grasping New Domains"

4 / 4 papers shown
Title
RuleRAG: Rule-Guided Retrieval-Augmented Generation with Language Models for Question Answering
RuleRAG: Rule-Guided Retrieval-Augmented Generation with Language Models for Question Answering
Zhongwu Chen
Chengjin Xu
Dingmin Wang
Zhen Huang
Yong Dou
Xuhui Jiang
Jian Guo
RALM
68
1
0
15 Oct 2024
Which Side Are You On? A Multi-task Dataset for End-to-End Argument
  Summarisation and Evaluation
Which Side Are You On? A Multi-task Dataset for End-to-End Argument Summarisation and Evaluation
Hao Li
Yuping Wu
Viktor Schlegel
R. Batista-Navarro
Tharindu Madusanka
...
Jiayan Zeng
Xiaochi Wang
Xinran He
Yizhi Li
Goran Nenadic
20
6
0
05 Jun 2024
Topic Ontologies for Arguments
Topic Ontologies for Arguments
Yamen Ajjour
Johannes Kiesel
Benno Stein
Martin Potthast
20
5
0
23 Jan 2023
Progressive Analytics: A Computation Paradigm for Exploratory Data
  Analysis
Progressive Analytics: A Computation Paradigm for Exploratory Data Analysis
Jean-Daniel Fekete
Romain Primet
43
84
0
18 Jul 2016
1