Survey on Abstractive Text Summarization: Dataset, Models, and Metrics | Paper Citation Record

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This paper cites Text summarization sota experiment.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Text summarization sota experiment

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This paper cites World report: Citable documents, 2022.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics World report: Citable documents, 2022

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This paper cites Report of all scientific articles on covid published from 2015 to 2024.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Report of all scientific articles on covid published from 2015 to 2024

Reference 3

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This paper cites Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension

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This paper cites Peters, and Arman Cohan.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Peters, and Arman Cohan

Reference 8

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This paper cites Big bird: Transformers for longer sequences.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Big bird: Transformers for longer sequences

Reference 9

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This paper cites Longt5: Efficient text-to-text transformer for long sequences.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Longt5: Efficient text-to-text transformer for long sequences

Reference 10

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This paper cites Gomez, Łukasz Kaiser, and Illia Polosukhin.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Gomez, Łukasz Kaiser, and Illia Polosukhin

Reference 11

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This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 12

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This paper cites Primera: Pyramid-based masked sentence pre-training for multi-document summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Primera: Pyramid-based masked sentence pre-training for multi-document summarization

Reference 13

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This paper cites Antognini and B.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Antognini and B

Reference 14

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

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This paper cites Yasunaga, R.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Yasunaga, R

Reference 16

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This paper cites Song, Y .-S.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Song, Y .-S

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This paper cites Efficiently summarizing text and graph encodings of multi-document clusters.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Efficiently summarizing text and graph encodings of multi-document clusters

Reference 18

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This paper cites Learning to extract coherent summary via deep reinforcement learning.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Learning to extract coherent summary via deep reinforcement learning

Reference 19

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This paper cites Banditsum: Extractive summarization as a contextual bandit.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Banditsum: Extractive summarization as a contextual bandit

Reference 20

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This paper cites Neural document summa- rization by jointly learning to score and select sentences.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Neural document summa- rization by jointly learning to score and select sentences

Reference 21

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This paper cites Neural latent extractive document summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Neural latent extractive document summarization

Reference 22

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This paper cites Cohen, and Mirella Lapata.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Cohen, and Mirella Lapata

Reference 23

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Williams

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This paper cites Neural extractive text summarization with syntactic compression.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Neural extractive text summarization with syntactic compression

Reference 25

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This paper cites Strass: A light and effective method for extractive summarization based on sentence embeddings.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Strass: A light and effective method for extractive summarization based on sentence embeddings

Reference 26

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This paper cites A novel extractive multi-document text summarization system using quantum-inspired genetic algorithm: Mtsqiga.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics A novel extractive multi-document text summarization system using quantum-inspired genetic algorithm: Mtsqiga

Reference 27

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Observation 68c58e78-13d9-4bff-9bae-4919a5b73869 · outbound

This paper cites Alguliev, R.M.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Alguliev, R.M

Reference 28

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Alguliyev, R

Reference 29

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This paper cites Alguliyev, R.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Alguliyev, R

Reference 30

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Reference 31

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This paper cites Alguliyev, R.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Alguliyev, R

Reference 32

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer

Reference 33

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Abstractive text summarization using sequence-to-sequence rnns and beyond

Reference 34

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Narayan, S

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This paper cites An entity-driven framework for abstractive summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics An entity-driven framework for abstractive summarization

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Hierarchical transformers for multi-document summarization

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Text summarization with pretrained encoders

Reference 39

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Liu, and Christopher D

Reference 40

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Cohan, F

Reference 41

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This paper cites Soft layer-specific multi-task summarization with entailment and question generation.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Soft layer-specific multi-task summarization with entailment and question generation

Reference 42

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This paper cites Improving abstraction in text summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Improving abstraction in text summarization

Reference 43

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Observation fed40d47-fbd9-40e3-b07d-1c9c9add38cf · outbound

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Raffel, N

Reference 44

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Observation 5ec93ba8-311e-44bc-a484-d392cdac4c4f · outbound

This paper cites Distillation knowledge applied on pegasus for summarization, 2019–2020.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Distillation knowledge applied on pegasus for summarization, 2019–2020

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Observation 315d0e98-09b8-4bd1-b49c-57e95b47eb6a · outbound

This paper cites Faithful to the original: Fact aware neural abstractive summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Faithful to the original: Fact aware neural abstractive summarization

Reference 46

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This paper cites Liu, and Mohammad Saleh.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Liu, and Mohammad Saleh

Reference 47

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Observation 794e48dd-26b9-46dd-852f-54ad1f373e46 · outbound

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 48

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Observation a7cd131b-9b07-4a85-8cc5-1b50ee5f21b3 · outbound

This paper cites Neural text summarization: A critical evaluation.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Neural text summarization: A critical evaluation

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Observation f954d62f-2f72-4465-87dc-6a867c818ce6 · outbound

This paper cites Long short-term memory.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Long short-term memory

Reference 50

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This paper cites Review summarization with pointer gen and bert, 2020.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Review summarization with pointer gen and bert, 2020

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.978753Z

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Observation a8f46f5e-ceba-4781-ba92-007f4ac36cb0 · outbound

This paper cites A Deep Reinforced Model for Abstractive Summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics A Deep Reinforced Model for Abstractive Summarization

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This paper cites Multi-reward reinforced summarization with saliency and entailment.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Multi-reward reinforced summarization with saliency and entailment

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.966906Z

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Observation badc18f7-fb6f-4580-a0a7-22a66d5ec0cb · outbound

This paper cites Closed-book training to improve summarization encoder memory.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Closed-book training to improve summarization encoder memory

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.955000Z

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Observation 79b06991-64bd-4b2c-8ba5-951aab5e35c4 · outbound

This paper cites Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.943316Z

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Observation f946c8cd-3fb3-4cfe-a2e2-080deb282c38 · outbound

This paper cites Unified language model pre-training for natural language understanding and generation.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unified language model pre-training for natural language understanding and generation

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.930802Z

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Observation c1521ceb-1803-4344-9bce-007a53ca07f7 · outbound

This paper cites Deep communicating agents for abstractive summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Deep communicating agents for abstractive summarization

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.918901Z

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Observation beabc8a4-6d47-49fb-8e82-d6c16a4d5c8a · outbound

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Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 58

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Observation a9af3755-6123-488d-8ce5-b2084edb7727 · outbound

This paper cites Fast abstractive summarization with reinforce-selected sentence rewriting.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Fast abstractive summarization with reinforce-selected sentence rewriting

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.895146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6c9cfd59-bf29-4ed3-97db-cb680dfa3ae6 · outbound

This paper cites an unresolved cited work.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 60

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:46:59.884210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9bad44f4-faaf-4c85-90dc-e6273e13b67c · outbound

This paper cites A unified model for extractive and abstractive summarization using inconsistency loss.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics A unified model for extractive and abstractive summarization using inconsistency loss

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.872702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 20cfca97-fd87-467a-804f-3bf04c4fb08b · outbound

This paper cites Improving multi-document summarization through referenced flexible extraction with credit-awareness.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Improving multi-document summarization through referenced flexible extraction with credit-awareness

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.859897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 51823c6a-dec6-48ad-84c0-9a92b5fa28a9 · outbound

This paper cites an unresolved cited work.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 63

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:46:59.848024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0e330c01-e826-47f7-b68f-ff78e5e16235 · outbound

This paper cites Efficient estimation of word representations in vector space.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Efficient estimation of word representations in vector space

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.836135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2d95a7a4-6c93-41d0-a24e-7562bde86a43 · outbound

This paper cites an unresolved cited work.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 65

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:46:59.823890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 34bb39cd-0bdd-42d5-a92a-3fdabbc11277 · outbound

This paper cites An introduction to convolutional neural networks.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics An introduction to convolutional neural networks

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.811981Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d43505cf-6357-40f4-ba16-6b2c37db1820 · outbound

This paper cites an unresolved cited work.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T05:46:58.938434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14607ad7-ea88-4787-a7ad-c1aceacffd35 · outbound

This paper cites Huggingface.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Huggingface

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.793686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ecd6bc2f-5b25-4cef-b4ac-6d771b91c21d · outbound

This paper cites Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T05:46:58.946747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a2be189f-1b86-49bb-b862-c85e63d98910 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries, 2004.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Rouge: A package for automatic evaluation of summaries, 2004

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T05:46:58.951006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e79026e-9ce9-427a-aeb8-291b34dfba46 · outbound

This paper cites Learning to score system summaries for better content selection evaluation.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Learning to score system summaries for better content selection evaluation

Reference 71

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.775540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3b2f3b31-8855-4220-b130-7572027e40e9 · outbound

This paper cites BERTScore: Evaluating Text Generation with BERT.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics BERTScore: Evaluating Text Generation with BERT

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T05:46:58.958699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c99c3467-77d6-408c-b947-4c3360fa89e5 · outbound

This paper cites Meyer, and Steffen Eger.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Meyer, and Steffen Eger

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.764420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 10758d3e-05b0-4205-a2d6-43a09cdf36c7 · outbound

This paper cites Speeding up word mover’s distance and its variants via properties of distances between embeddings, 12 2019.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Speeding up word mover’s distance and its variants via properties of distances between embeddings, 12 2019

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.753511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ab309c0d-ffb3-4cd0-be90-13190ce929c9 · outbound

This paper cites an unresolved cited work.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 75

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:46:59.742129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation fa25e71b-f424-44eb-a8df-7331c3b2ea1a · outbound

This paper cites Answers unite! unsupervised metrics for reinforced summarization models.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Answers unite! unsupervised metrics for reinforced summarization models

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.731562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c5550f85-0f36-45e4-8260-f013da18b150 · outbound

This paper cites Fill in the BLANC: Human-free quality estimation of document summaries.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Fill in the BLANC: Human-free quality estimation of document summaries

Reference 77

Resolution: unresolved; no resolver link, observed 2026-08-11T05:46:58.978075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01c8e5ae-4ebf-4a50-9511-d7f825c7799c · outbound

This paper cites Supert: towards new frontiers in unsupervised evaluation metrics for multi document summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Supert: towards new frontiers in unsupervised evaluation metrics for multi document summarization

Reference 78

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.720655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 753e29ba-24e1-49e9-a5df-1a50271d0049 · outbound

This paper cites Bleu: a method for automatic evaluation of machine translation.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Bleu: a method for automatic evaluation of machine translation

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.709378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a1808f9b-794a-4a4d-b193-9dbd8b4c2aa4 · outbound

This paper cites Chrf: Character n-gram f-score for automatic mt evaluation.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Chrf: Character n-gram f-score for automatic mt evaluation

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.697920Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation a89eadb1-52b8-44ea-ba81-421b63855013 · outbound

This paper cites Meteor: An automatic metric for mt evaluation with high levels of correlation with human judgments.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Meteor: An automatic metric for mt evaluation with high levels of correlation with human judgments

Reference 81

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.686705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 51ebb77b-33f0-4b7d-a475-34c6d06e90b1 · outbound

This paper cites Lawrence Zitnick, and Devi Parikh.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Lawrence Zitnick, and Devi Parikh

Reference 82

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.675154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eba0a1df-22b2-44eb-a86f-59918b470948 · outbound

This paper cites Evaluating the factual consistency of abstractive text summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Evaluating the factual consistency of abstractive text summarization

Reference 83

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.664006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e4f3e728-7efd-430f-a5b4-5e48f3ca4493 · outbound

This paper cites Entity-level factual consistency of abstractive text summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Entity-level factual consistency of abstractive text summarization

Reference 84

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.652994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 34ee355a-ddf5-4d5e-9db9-05ebeb95c43b · outbound

This paper cites Fact-checking.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Fact-checking

Reference 85

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.640968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation eb253ff8-8fda-4d98-812c-8efb9820e87b · outbound

This paper cites Fabbri, Wojciech Kry´sci´nski, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Fabbri, Wojciech Kry´sci´nski, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev

Reference 86

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.628845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0f4c6382-a8ca-498f-9d56-960939735722 · outbound

This paper cites Generating Representative Headlines for News Stories.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Generating Representative Headlines for News Stories

Reference 87

Resolution: verified exact; local_arxiv, observed 2026-08-11T05:46:59.271592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 62785ebf-8006-4648-937b-dd71027d8c1e · outbound

This paper cites an unresolved cited work.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 88

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:46:59.616723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 3367d8c9-55d6-48b1-b110-ec5d0c7d6746 · outbound

This paper cites Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Newsroom: A dataset of 1.3 million summaries with diverse extractive strategies

Reference 89

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.605675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation cd59e727-86ae-47ef-bcc5-0e0926a51eab · outbound

This paper cites an unresolved cited work.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 90

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:46:59.595186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 2a820a03-ed89-4523-b9b8-89b94b14cae7 · outbound

This paper cites Graff, J.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Graff, J

Reference 91

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.584493Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d6fc6dda-c77d-4403-835f-574161680697 · outbound

This paper cites Sharma, C.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Sharma, C

Reference 92

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.573101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 9e1a8548-6f0c-4e9a-b41d-d7550234f816 · outbound

This paper cites WikiHow: A Large Scale Text Summarization Dataset.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics WikiHow: A Large Scale Text Summarization Dataset

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-11T05:46:59.038766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95f43f94-87c7-4dc4-9f81-9c2918bec38e · outbound

This paper cites an unresolved cited work.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Unresolved cited work

Reference 94

Resolution: unresolved; raw_fallback, observed 2026-08-11T05:46:59.561199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation e076b283-07d8-4bb4-9841-cba582478775 · outbound

This paper cites Zhang and J.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Zhang and J

Reference 95

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.544068Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d27ed675-d7ba-4264-9307-3774d3f22944 · outbound

This paper cites The enron corpus: A new dataset for email classification research.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics The enron corpus: A new dataset for email classification research

Reference 96

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.531171Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d11ce5a1-07d9-44cb-b8ac-4e5cd298d8e3 · outbound

This paper cites Kornilova and V.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Kornilova and V

Reference 97

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.519378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ad65ca52-ea6e-40c1-84d8-ead6ce34d98b · outbound

This paper cites BookSum: A Collection of Datasets for Long-form Narrative Summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics BookSum: A Collection of Datasets for Long-form Narrative Summarization

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-11T05:46:59.058964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b7d7ce2-dc84-46ac-b407-cc74648724f6 · outbound

This paper cites Efficient attentions for long document summarization.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Efficient attentions for long document summarization

Reference 99

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.507650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation b681b70d-7443-483a-b87a-b7b028ddd8fb · outbound

This paper cites Multi-lexsum: Real-world summaries of civil rights lawsuits at multiple granularities, 06 2022.

Survey on Abstractive Text Summarization: Dataset, Models, and Metrics Multi-lexsum: Real-world summaries of civil rights lawsuits at multiple granularities, 06 2022

Reference 100

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T05:46:59.495342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers