ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1911.01352
  4. Cited By
Learning from Explanations with Neural Execution Tree

Learning from Explanations with Neural Execution Tree

4 November 2019
Ziqi Wang
Yujia Qin
Wenxuan Zhou
Jun Yan
Qinyuan Ye
Leonardo Neves
Zhiyuan Liu
Xiang Ren
    LRM
ArXivPDFHTML

Papers citing "Learning from Explanations with Neural Execution Tree"

10 / 10 papers shown
Title
CLUES: A Benchmark for Learning Classifiers using Natural Language
  Explanations
CLUES: A Benchmark for Learning Classifiers using Natural Language Explanations
Rakesh R Menon
Sayan Ghosh
Shashank Srivastava
LRM
ELM
29
9
0
14 Apr 2022
Using Interactive Feedback to Improve the Accuracy and Explainability of
  Question Answering Systems Post-Deployment
Using Interactive Feedback to Improve the Accuracy and Explainability of Question Answering Systems Post-Deployment
Zichao Li
Prakhar Sharma
Xing Han Lù
Jackie C.K. Cheung
Siva Reddy
HAI
25
26
0
06 Apr 2022
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with
  Auxiliary Trigger Extraction
AutoTriggER: Label-Efficient and Robust Named Entity Recognition with Auxiliary Trigger Extraction
Dong-Ho Lee
Ravi Kiran Selvam
Sheikh Muhammad Sarwar
Bill Yuchen Lin
Fred Morstatter
Jay Pujara
Elizabeth Boschee
James Allan
Xiang Ren
39
2
0
10 Sep 2021
On the Diversity and Limits of Human Explanations
On the Diversity and Limits of Human Explanations
Chenhao Tan
19
31
0
22 Jun 2021
Local Interpretations for Explainable Natural Language Processing: A
  Survey
Local Interpretations for Explainable Natural Language Processing: A Survey
Siwen Luo
Hamish Ivison
S. Han
Josiah Poon
MILM
43
48
0
20 Mar 2021
When Can Models Learn From Explanations? A Formal Framework for
  Understanding the Roles of Explanation Data
When Can Models Learn From Explanations? A Formal Framework for Understanding the Roles of Explanation Data
Peter Hase
Joey Tianyi Zhou
XAI
25
87
0
03 Feb 2021
Teaching Machine Comprehension with Compositional Explanations
Teaching Machine Comprehension with Compositional Explanations
Qinyuan Ye
Xiao Huang
Elizabeth Boschee
Xiang Ren
LRM
ReLM
24
34
0
02 May 2020
LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from
  Explanation
LEAN-LIFE: A Label-Efficient Annotation Framework Towards Learning from Explanation
Dong-Ho Lee
Rahul Khanna
Bill Yuchen Lin
Jamin Chen
Seyeon Lee
Qinyuan Ye
Elizabeth Boschee
Leonardo Neves
Xiang Ren
35
22
0
16 Apr 2020
e-SNLI: Natural Language Inference with Natural Language Explanations
e-SNLI: Natural Language Inference with Natural Language Explanations
Oana-Maria Camburu
Tim Rocktaschel
Thomas Lukasiewicz
Phil Blunsom
LRM
287
623
0
04 Dec 2018
Mean teachers are better role models: Weight-averaged consistency
  targets improve semi-supervised deep learning results
Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results
Antti Tarvainen
Harri Valpola
OOD
MoMe
273
1,275
0
06 Mar 2017
1