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---
date: '2022-11-28T11:31:57'
hypothesis-meta:
created: '2022-11-28T11:31:57.626263+00:00'
document:
title:
- Countering the Effects of Lead Bias in News Summarization via Multi-Stage Training
and Auxiliary Losses
flagged: false
group: __world__
hidden: false
id: RG4WUG8QEe2-tZ8v6nNOJA
links:
html: https://hypothes.is/a/RG4WUG8QEe2-tZ8v6nNOJA
incontext: https://hyp.is/RG4WUG8QEe2-tZ8v6nNOJA/aclanthology.org/D19-1620.pdf
json: https://hypothes.is/api/annotations/RG4WUG8QEe2-tZ8v6nNOJA
permissions:
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delete:
- acct:ravenscroftj@hypothes.is
read:
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update:
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tags:
- NLProc
- summarization
- bandit
- rl
target:
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start: 7890
type: TextPositionSelector
- exact: BanditSum a hierarchical bi-LSTM
prefix: S uses a CNN+bi-GRU encoder, and
suffix: ". RNES\u2019s de-coder is auto-regres"
type: TextQuoteSelector
source: https://aclanthology.org/D19-1620.pdf
text: Banditsum uses bi-directional LSTM encoding. It generates sentence-level representations
updated: '2022-11-28T11:34:57.447988+00:00'
uri: https://aclanthology.org/D19-1620.pdf
user: acct:ravenscroftj@hypothes.is
user_info:
display_name: James Ravenscroft
in-reply-to: https://aclanthology.org/D19-1620.pdf
tags:
- NLProc
- summarization
- bandit
- rl
- hypothesis
type: annotation
url: /annotations/2022/11/28/1669635117
---
<blockquote>BanditSum a hierarchical bi-LSTM</blockquote>Banditsum uses bi-directional LSTM encoding. It generates sentence-level representations