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# Simple Unsupervised Summarization by Contextual Matching
言語モデルのみを利用したシンプルな教師なしの生成型要約手法を提案。ここでは、Contextual Matching ModelとDomain Fluency Modelの2つの言語モデルを利用して要約文を生成している。生成型要約および抽出型要約の2つのタスクで、提案手法の有用性を…
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ACM Multimedia, (2019).
Attention付きConditional GAN(ACGAN)を提案し,Video Summarizationにおいて,SumMeとTVSumでSOTAを達成.
![image](https://user-images.githubusercontent.com/18545255/70013490-2e6a2f80-15bb-11ea-8…
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https://aclanthology.org/D19-1320/
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https://aclanthology.org/2020.acl-main.124/
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SImilar to skip-gram in your typical word2vec. However in this case the sentence is passed through a RNN encoder, whose output is fed simultaneously into:
- a forward thought RNN decoder : predict …
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Hi,
Is there any official result(included in summarization topic papers) on TextRank?
Thanks.
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Treat it as unsupervised problem.
Approach ( idea inspired from topic modelling on user prompts from [Chatbot Arena paper](https://arxiv.org/html/2403.04132v1)
> To study the prompt diversity, we bu…
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hello, how does the evaluation metrics of Summe and TVSum datasets τ and ρ calculate? I only see the calculation method of fscore in the code.
Looking forward to getting your reply, thank you very…
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### Metadata
Authors: Prajit Ramachandran, Peter J. Liu and Quoc V. Le
Organization: Google Brain
Conference: EMNLP 2017
Link: https://goo.gl/n2cKG9
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# URL
- https://arxiv.org/abs/2305.18290
# Affiliations
- Rafael Rafailov, N/A
- Archit Sharma, N/A
- Eric Mitchell, N/A
- Stefano Ermon, N/A
- Christopher D. Manning, N/A
- Chelsea Finn, …