Pith. sign in

Paper Citation Record · LEDGER

Repurposing Decoder-Transformer Language Models for Abstractive Summarization

As of 18 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:1909.00325.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1909.00325 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T05:59:39.677951Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

33 of 33 outbound references displayed

  • verified exact2
  • verified fuzzy1
  • unresolved30
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a3fa0ea9-aca1-43d6-b545-e6db3e0e8300 · outbound

This paper cites URL: " 'urlintro :=.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization URL: " 'urlintro :=

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.554935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.554935Z digest=sha256:4bdcc7cbcedf627211e3d0e2efa6aa0721da09445fbcfdf899b334bf23d6c9f8

Observation eea6d6f5-75ab-4672-9e00-faf689d5db08 · outbound

This paper cites write newline.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization write newline

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.560273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.560273Z digest=sha256:20f679740124f8a1368d169949d3c105464096826087c69e9e239cc8847581d5

Observation 118cee23-5e0d-4fe1-99fe-468c6e8f3a89 · outbound

This paper cites Deep Communicating Agents for Abstractive Summarization.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Deep Communicating Agents for Abstractive Summarization

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.564270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.564270Z digest=sha256:abb81fe9ca12b18b226679742412a9e6068d5792eded7a1df51fd942616e16e6

Observation 5f928dc8-e101-44e8-a12f-4221e0231a33 · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-08-14T05:59:39.952054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-14T05:59:39.568644Z digest=sha256:27dfcafd8df9a96e780458fc5e8a2136841fb7efd7142e7ce0a323145a3e47bd

Observation 03114911-13f7-424a-bf3d-1d90e01e71d2 · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.572494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.572494Z digest=sha256:2a4a2a76ea3dbaec7fcfe4b6336e4b7865a48964ac66bc58e287094f88b68aed

Observation c5f8db10-c982-4da8-ae7e-e1621255623a · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.576246Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.576246Z digest=sha256:f4c0325b5ecb41c661a045cd1592de027d6973ff39c12aba99b59050af901c00

Observation b5ab106c-35d4-4682-bb31-a3102f85ad2a · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.580046Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.580046Z digest=sha256:b0af4bf322e70bc5036abe6e5ca8f71a9f2618f845ee59318bb714854c142033

Observation c5b3c5fd-e1e4-4f2c-ad16-db48d3a3ec07 · outbound

This paper cites Incorporating Copying Mechanism in Sequence-to-Sequence Learning.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Incorporating Copying Mechanism in Sequence-to-Sequence Learning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.583537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.583537Z digest=sha256:00338df6509060bced7d844716495df58a779550dc388499ef91495fe90c507a

Observation ee7d3775-6788-489a-82a1-15bd2e505e03 · outbound

This paper cites The Curious Case of Neural Text Degeneration.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization The Curious Case of Neural Text Degeneration

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.587768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.587768Z digest=sha256:59a7222d415938ded122d36c72ec00c9c22b4188dcd271937f0fcdb1228d2f9a

Observation e4a86387-42b1-42b6-9d44-ceb5df58f635 · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.591532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.591532Z digest=sha256:105577a1403105b1dc60276a6bda48bdb966c8ee76c12059d7c7ee118fa4d638

Observation 6b16ed9e-1594-43d2-a528-8ef61f33cb81 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Adam: A Method for Stochastic Optimization

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.594984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.594984Z digest=sha256:c0f3b6a75d5a1fff3fd6d8fac79d7c8b98cea7ef2b44a1839d38e8809a7882df

Observation 93914926-9609-4d0a-9eb3-242293e6df2f · outbound

This paper cites SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.599082Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.599082Z digest=sha256:8ed0f20deb0b29146ce6e11bdda0d7a50d44a114dfe7a69b8e1dc86cb0aa5244

Observation e9e63412-78f1-4ca8-8f13-5beaa88213ad · outbound

This paper cites Layer Normalization.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Layer Normalization

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.602861Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.602861Z digest=sha256:8b61513fce6ee819b0c837becaaf1a95e844a94f48b5fc3e30ad95d9a5f1da60

Observation d8142070-7843-4e71-8a57-b0b5a048d637 · outbound

This paper cites Actor-Critic based Training Framework for Abstractive Summarization.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Actor-Critic based Training Framework for Abstractive Summarization

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.606319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.606319Z digest=sha256:04fd22b34030e19491c0fd496e92e0c264e97f973bc54d36d904d9ece3030220

Observation 8c6e6563-9989-4f31-92ff-4bd8ae1cec4d · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-08-14T05:59:39.923925Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-14T05:59:39.610073Z digest=sha256:f84461a9cff1bfad2f126488cb5e70f9dd64e4f02be27a45a572d2b11c97d96e

Observation 2b3bf7d9-dfd7-404f-85f4-9cd95c1b2966 · outbound

This paper cites Liu, Mohammad Ahmad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Liu, Mohammad Ahmad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam Shazeer

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T05:59:39.913260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-14T05:59:39.613846Z digest=sha256:f1bf7b5b7dfdc0262a25ec8c657f2ee1cdda69f95867bf61016abf4e79e6aab9

Observation 2dce94d5-fb15-4324-bb05-e34a077af28d · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 17

Resolution
verified exact
doi, observed 2026-08-14T05:59:39.708932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-14T05:59:39.617785Z digest=sha256:0ce786223efe991a52566dfdde8c9317749a65992d49d24197b6b3dc3dc6bc7f

Observation 35e06056-7c0b-4ff2-bf1b-2d01cf20d88c · outbound

This paper cites Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Abstractive Text Summarization Using Sequence-to-Sequence RNNs and Beyond

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.622038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.622038Z digest=sha256:4befe91652ab1a9397fa2b7855d0956642b16504d3d2cd5d86167d1b5adfda28

Observation 512f626f-c8fc-458b-a021-3a178fadfe1d · outbound

This paper cites Cohen, and Mirella Lapata.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Cohen, and Mirella Lapata

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.626476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.626476Z digest=sha256:b249a09bf6ea63a139a2d2e9d535adb73fa32f305f4f5019e7ae05acf4882805

Observation 7985c6c1-79ad-4cb5-ac66-52a927bfffad · outbound

This paper cites A Deep Reinforced Model for Abstractive Summarization.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization A Deep Reinforced Model for Abstractive Summarization

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.630755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.630755Z digest=sha256:0a81be481a670db646f7d8b004dc092ca44b3c07cdca495cfba5ab237bb7c9c4

Observation e976b93c-3201-411f-8ca2-d5896e86c67b · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.634628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.634628Z digest=sha256:97ef48127fffd5700cb8da150a4fa32c4b0e58fc8ec7cf9799864f3a920c7563

Observation bfd5d0b9-06cc-4db1-a49b-90d5521c4b92 · outbound

This paper cites Improving language understanding by generative pre-training.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Improving language understanding by generative pre-training

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.638711Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.638711Z digest=sha256:3e8d60512b4a78b65400357a880dfcf848e6953a84116a62b275528faae60e22

Observation 95b86dea-bd6a-416d-b99f-b815d9f7e87d · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.642668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.642668Z digest=sha256:e56ec1f7d9172ebe67276dff7405585d1c46ddd4163f85832184fe8945646ed4

Observation 9dbdec1b-e931-4fef-9034-9e58b9fc1f30 · outbound

This paper cites A Neural Attention Model for Abstractive Sentence Summarization.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization A Neural Attention Model for Abstractive Sentence Summarization

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.645820Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.645820Z digest=sha256:5529ec70e7eff17da17eef944b9b5ef1e6c327e61c53c259fc3f440ce0855343

Observation 53035531-eca7-4982-ac35-4430a1370341 · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-14T05:59:39.879886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-14T05:59:39.649315Z digest=sha256:fdf4c65dce01c73e128e8cdf63523de297c06c5b09ab9c11549561829abacd1a

Observation 5d6ed72b-ccd7-4834-9fab-cfb0078b55ba · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.653191Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.653191Z digest=sha256:da1758b122d9f63ff13805c779e3f0fcefa9b73b8b83d8a9bcb4da9f7a92c80a

Observation aff0ecfc-46ba-44e4-8cb9-1d03a5ffb015 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Neural Machine Translation of Rare Words with Subword Units

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.656661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.656661Z digest=sha256:6d346706e56fe471b370940eeef7eb77890fb816063c0ccdd927102b9ec912d1

Observation 3ceadbe9-6f0a-42f9-9222-f990f7d78223 · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.660573Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.660573Z digest=sha256:b8dd9327caf2c21528d15ae7280d9e2e43f31afe08f93d405b7309b5bfbdb98c

Observation 99421633-5061-4821-9442-9f7a34f7584a · outbound

This paper cites Modeling Coverage for Neural Machine Translation.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Modeling Coverage for Neural Machine Translation

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.663778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.663778Z digest=sha256:98aafcd57f8be8074956fd75747cd41a9f80ce7f969623b835933fd1be040286

Observation 74317759-001f-4c56-80c7-31a6e65ba0cc · outbound

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

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.667610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.667610Z digest=sha256:70ad20c34141ac6dd9e9ebbd21b8d9a59392cad56307b5bbc8d4a24529d584c8

Observation 34fc66e7-82a5-4581-8600-d37b5e18b7fa · outbound

This paper cites an unresolved cited work.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Unresolved cited work

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.671378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.671378Z digest=sha256:eba969564f5910ce9ceea1cf1d0727e3f8870bb786a12afb9829d28be99a71a2

Observation 556b5903-a98b-4967-ad31-a33bab998cfa · outbound

This paper cites Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-14T05:59:39.674676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T05:59:39.674676Z digest=sha256:e958014b5b93f28d473f64bf43b8d5889d6685b907eb796b991d715656440912

Observation 5089fa09-b005-4bdc-9518-906389c4e046 · outbound

This paper cites Efficient Summarization with Read-Again and Copy Mechanism.

Repurposing Decoder-Transformer Language Models for Abstractive Summarization Efficient Summarization with Read-Again and Copy Mechanism

Reference 33

Resolution
verified exact
local_arxiv, observed 2026-08-14T05:59:39.724024Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-14T05:59:39.677951Z digest=sha256:4b933dbf45190550393be802d3703335e3d029087bfbf70ab1baf6c814316c81

Pith citing papers

No inbound Pith citation observations are available.