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Paper Citation Record · LEDGER

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization

As of 14 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 0 inbound Pith citation observations for arXiv:2509.09852.

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

pith.paper-citation-record.v1
2509.09852 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T18:37:55.135579Z

measured 70 of 70 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

70 of 70 outbound references displayed

  • verified exact14
  • verified fuzzy0
  • unresolved56
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8e123040-9366-4020-983b-51a442345df4 · outbound

This paper cites online" 'onlinestring :=.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization online" 'onlinestring :=

Reference 1

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no resolver link, observed 2026-08-04T18:37:54.932687Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:54.932687Z digest=sha256:b6eb6030ad2aaa09c9a3f67f50592743146317aef23802771c41608c5c2a64b5

Observation 27993617-efa5-4f0e-b5ac-856b4ce47c5b · outbound

This paper cites write newline.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization write newline

Reference 2

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source=arxiv_source observed=2026-08-04T18:37:54.936434Z digest=sha256:9ca7ef6b10b47a895a91f1c64920dd6f1d21ef6e8762ecef181a681724950810

Observation f128fc74-26d0-4476-9f12-0b228d9821ce · outbound

This paper cites GPT-4 Technical Report.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization GPT-4 Technical Report

Reference 3

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source=arxiv_source observed=2026-08-04T18:37:54.939573Z digest=sha256:3b87a2302dfca647ff830bac023143b914cfbc023e9a0724637ca823a702a92d

Observation b0755606-5acc-4dcc-a2a3-b1a49886d1c2 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 4

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verified exact
doi, observed 2026-08-04T18:38:37.849504Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:54.943368Z digest=sha256:2198d38fadc88a3a461a63f61e390c8f600f6823f313b40bd9f18ab8211d47c6

Observation 84482a07-86cd-402f-b69b-e7bf781c5ddb · outbound

This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 5

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source=arxiv_source observed=2026-08-04T18:37:54.946479Z digest=sha256:6d77fc8866456845e755f97379dca68eea739a00c4b4ed429aa86987480e82ab

Observation 6bac725c-2dfd-4067-a0de-60edad493e92 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 6

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unresolved
no resolver link, observed 2026-08-04T18:37:54.949353Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:54.949353Z digest=sha256:fefca58414259dfff93ef2d9d1cd4474f82faa5221a6196f14793a57a93e4a00

Observation 2f9031bd-2279-46f8-96cb-c5ba6b264c04 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 7

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source=arxiv_source observed=2026-08-04T18:37:54.952230Z digest=sha256:783c4c81f350b5e4bb64c7b8a9f9c5ba0ed930b5df2875b1f588360e97f2d08a

Observation 69b96d60-dddc-436f-b416-65c226628a09 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-04T18:37:54.954972Z digest=sha256:3aba0a21f44a02923bcfab5677a6ec441c04b77138981503cb0a4b8aec35ad96

Observation 9f03312d-a6bb-45db-8d26-3654c45724ed · outbound

This paper cites Multi2: Multi-Agent Test-Time Scalable Framework for Multi-Document Processing.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Multi2: Multi-Agent Test-Time Scalable Framework for Multi-Document Processing

Reference 9

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source=arxiv_source observed=2026-08-04T18:37:54.957762Z digest=sha256:7c528a148f43b0991792ad9128c74e93bfa0808755f17b1ceb4596a2ce49eebb

Observation 3f180606-5c0e-455f-928c-3628b7ad95d1 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 10

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source=arxiv_source observed=2026-08-04T18:37:54.960678Z digest=sha256:16abcece3c0858431cf361e75eb69cc4b94e2b092d053ea4fb8b23ba4dce6c4c

Observation ebef1b7c-0fa4-4f6c-9492-7ee9d67c2a5d · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 11

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source=arxiv_source observed=2026-08-04T18:37:54.963685Z digest=sha256:0edacda08cedec96919bb4cae37b9fcd8b438f27fe998e5b63c2ba9ef842cff0

Observation 5ee19763-2fda-4180-b3eb-ed0b45568f26 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 12

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source=arxiv_source observed=2026-08-04T18:37:54.966778Z digest=sha256:b5f339cdb5095a1146f91f26cffa2d476198cb50f38d7b0039f6a9b1572e6295

Observation 87c8324e-1f07-45f8-89f9-2bab5c376c56 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 13

Resolution
verified exact
doi, observed 2026-08-04T18:38:37.587206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:54.969438Z digest=sha256:eadfe3b008bb26b085c8d0ffd0551e12602f2ab7acceac12510db05c5f01c3f8

Observation b58f3bca-d430-4843-a8f7-903986b2ace2 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 14

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verified exact
doi, observed 2026-08-04T18:38:37.364754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:54.972095Z digest=sha256:6daf7fe87e826d587a426d0563c2a2e151a17ebc673cc70d610779f637119d1d

Observation 696e8f3b-6d18-409d-b7a8-1d164d77626a · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 15

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verified exact
doi, observed 2026-08-04T18:38:37.095082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:54.974580Z digest=sha256:4f330be7bafc94be396c793a863718991929b495f49c5b65ac0399f646b57362

Observation 975b36aa-6521-41e3-a5a5-488fbfca7ef2 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 16

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source=arxiv_source observed=2026-08-04T18:37:54.977345Z digest=sha256:463323874b4ca5b4887c9bcdb43071c5608c9636902071705cf1d5f7db6e84d3

Observation 6d22f3e5-f712-4746-98d8-b8d87e9cd9d9 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 17

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source=arxiv_source observed=2026-08-04T18:37:54.979830Z digest=sha256:89708c65d48ccb295d1664878769d932442f857a192e62c4d4b762d692c9f532

Observation 37e21761-9b5e-47be-9f79-9c5c03828ead · outbound

This paper cites Fabbri, Wojciech Kry \'s ci \'n ski, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Fabbri, Wojciech Kry \'s ci \'n ski, Bryan McCann, Caiming Xiong, Richard Socher, and Dragomir Radev

Reference 18

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source=arxiv_source observed=2026-08-04T18:37:54.982476Z digest=sha256:11b0d0a5aa25287cc5f55b42b6c9bf7d67c4dd52e91175e30e65bd33e1170045

Observation 421dfb8e-d071-4007-a586-65ac5c2668fe · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 19

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source=arxiv_source observed=2026-08-04T18:37:54.984942Z digest=sha256:29ccf14141cf5a8b947a6692bb28481c43b38a9e5fe1accc7a8edbfaf1cdee64

Observation b2c6daf1-39df-4610-a389-969a778a8e28 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 20

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source=arxiv_source observed=2026-08-04T18:37:54.987609Z digest=sha256:f93cda96f75e171cc6b3de214b348d5107a82d9d7965074238ed9de696ea3a45

Observation 446e852a-244a-4e6c-bc67-66de2cc7e1d3 · outbound

This paper cites News Summarization and Evaluation in the Era of GPT-3.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization News Summarization and Evaluation in the Era of GPT-3

Reference 21

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source=arxiv_source observed=2026-08-04T18:37:54.990198Z digest=sha256:8f7c1bdc90fbe9f7cf2c3565e38140bf5c10decbb3645c68c6a614e1f8ae5521

Observation 80bf3e19-b4e1-4a6a-93b8-f3710be16860 · outbound

This paper cites The Llama 3 Herd of Models.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization The Llama 3 Herd of Models

Reference 22

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source=arxiv_source observed=2026-08-04T18:37:54.992933Z digest=sha256:d32f1673657cb1f8579b321e395418f0d04c05ffecbfcf58879180d6342ddf46

Observation 92e92acc-aa21-4e98-8d4c-d0c1ad36ac6a · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 23

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source=arxiv_source observed=2026-08-04T18:37:54.995858Z digest=sha256:0bec2c62bc8f4368c4ec5758eac3641decca5b716214195b2c39d4e749803bf8

Observation 4776e303-3c22-4f8b-91bd-12fea2435057 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 24

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source=arxiv_source observed=2026-08-04T18:37:54.998862Z digest=sha256:f4d283e9126e8c6dacf6bf3cb6020561f64ff743aaf32181339fc6feba1fd15f

Observation af72a5e7-d8ce-4481-bf26-930279b87571 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 25

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source=arxiv_source observed=2026-08-04T18:37:55.001384Z digest=sha256:512a6511132bb2f79d11c83ac145c6fd030306b9649b08b645445c735e433a82

Observation 6790c909-fc2d-49c8-99be-36b19bc76b6b · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 26

Resolution
verified exact
doi, observed 2026-08-04T18:38:36.807053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.004152Z digest=sha256:1fcdbf1cc6fec2ffa8499ba68b5f8d72213a244895bb5d6121a8b2bd62a78595

Observation 2d1f07e2-faa5-46b2-bf86-d53453a363f4 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 27

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source=arxiv_source observed=2026-08-04T18:37:55.006942Z digest=sha256:1c7843166a64c275efa351341eeb5c0aa25ba412acd453deb8aed901837eeb4a

Observation 9f9d56fa-0d3a-4bb5-8269-43081ee147d5 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 28

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source=arxiv_source observed=2026-08-04T18:37:55.009873Z digest=sha256:3667de2957084fbc4cc2ed7cc966aef53fff70e29fbfea7c400f8b5861944b9d

Observation 3f69425a-aca1-4eda-9875-ef5974256a33 · outbound

This paper cites Bennett, and Marti A.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Bennett, and Marti A

Reference 29

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source=arxiv_source observed=2026-08-04T18:37:55.012568Z digest=sha256:37c724aff20aea4ca86549da9eb2ae1fd9d59d9e0db2e9fbb6a5b7bd14109200

Observation 0e7d8c55-932c-4778-ade5-0a0706551ca4 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 30

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source=arxiv_source observed=2026-08-04T18:37:55.015112Z digest=sha256:e73e69220e97d0ff2bc39921f9e18dcca1b08d4488ae0352380057acfece361c

Observation 0206c315-5aaa-4b53-a9d4-9b59e0ade36a · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 31

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source=arxiv_source observed=2026-08-04T18:37:55.017730Z digest=sha256:e707515d138d60817688218647feb7e26d01178f7a7dbc6518c26a2ecdb14bec

Observation 717c806a-2536-4e8b-a504-769dc2b345a1 · outbound

This paper cites SEAM: A Stochastic Benchmark for Multi-Document Tasks.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization SEAM: A Stochastic Benchmark for Multi-Document Tasks

Reference 32

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source=arxiv_source observed=2026-08-04T18:37:55.020402Z digest=sha256:1c627ea48d5342a2560229c021ec6fbd1e7a873c98e365c218522eb695823c60

Observation 72c58c4d-59f0-4fa4-92ec-ea96918066ef · outbound

This paper cites GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document Summarization.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization GLIMMER: Incorporating Graph and Lexical Features in Unsupervised Multi-Document Summarization

Reference 33

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source=arxiv_source observed=2026-08-04T18:37:55.023204Z digest=sha256:7b35f2a3a78495718cccb9fec1812ce32524ca64137498104b9a23373472a034

Observation 6a2ede43-cee0-40c0-ab69-5aaf3d5892ce · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 34

Resolution
verified exact
doi, observed 2026-08-04T18:38:36.595083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.026081Z digest=sha256:69cf31ac8ea78e8981e546e684e96dbb645088c304bc8cacc8d2cf7ff22f5190

Observation 7b848fed-d031-43dc-a2da-63ba045eb01c · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 35

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source=arxiv_source observed=2026-08-04T18:37:55.028884Z digest=sha256:b2ac2b1d84ae9d87b6f6f7138b145440bc8aa384c0df769232ba85931f4b2931

Observation 2dce4749-bc08-4832-8204-142c7b39911a · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 36

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source=arxiv_source observed=2026-08-04T18:37:55.032881Z digest=sha256:a714d461fa4ec7dddfc270dcac4ef7bb058b6dc75dc9747c5e30ff1fabade56d

Observation 11747713-c908-4d51-8da4-cbd69aeccd2c · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 37

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source=arxiv_source observed=2026-08-04T18:37:55.035809Z digest=sha256:20822b896221c8db7697a6191d5eb2e516f08c3ab6162b648622f7522fdc465c

Observation 5ff71bd4-001f-45a6-8541-5f3b0bf2abc3 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 38

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verified exact
doi, observed 2026-08-04T18:38:36.259147Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.038835Z digest=sha256:91ba4193406669da2a406b785bb01ae594bd8b8df90cf12ef902b9dbb7bca12d

Observation 44321e29-c492-4ee9-b791-fa52cc38e411 · outbound

This paper cites Cohen, and Mirella Lapata.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Cohen, and Mirella Lapata

Reference 39

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source=arxiv_source observed=2026-08-04T18:37:55.041811Z digest=sha256:f7b4be0726cd195e1da2a555ba0e0411a70860d1f2ef0ed8816d500e24b06f11

Observation 27b3038b-bae4-4424-b3e9-46688c524050 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 40

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.044736Z digest=sha256:529e00ce72250be57b169c34cff6d438dc4197344b2801b5621c1c36dfd714e1

Observation 7064efb5-4bf1-4e24-a00e-6e72033e47df · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 41

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verified exact
doi, observed 2026-08-04T18:38:35.618144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.047558Z digest=sha256:58e734c964545cd511c3ad14ece95b744eaa73bbee312afdcd7d69b793a0b0a7

Observation 4b3aebdd-b2b9-4dc6-8030-e1e6da2ff6fd · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 42

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source=arxiv_source observed=2026-08-04T18:37:55.050560Z digest=sha256:8057c4397fdd9b94ab9341392153df69fcb6dec87336e9675bb78b8eda4c00aa

Observation c6066735-f05a-4039-bcf1-9aed73fd030c · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 43

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source=arxiv_source observed=2026-08-04T18:37:55.053462Z digest=sha256:91d54d2abbc17a2642676f931ea32123e56b9c1d6423ce8df58f8bbd057078ff

Observation c49137ae-d8a7-41b1-9082-c5d208cea82a · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 44

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no resolver link, observed 2026-08-04T18:37:55.056385Z

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source=arxiv_source observed=2026-08-04T18:37:55.056385Z digest=sha256:89cc66fff75d03d526653cd12481f9ff12c6fde0331629ec6c1b4328dd47cbc9

Observation 54f471c4-7be8-4554-9538-268f18abd4c6 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 45

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verified exact
doi, observed 2026-08-04T18:38:35.341165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.059321Z digest=sha256:19508a4351cebc4f927f94d93408646731ded9022285f7053544f2ad07680508

Observation 0ec0d66b-abd0-4759-979a-6c0e10ddd27c · outbound

This paper cites A Deep Reinforced Model for Abstractive Summarization.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization A Deep Reinforced Model for Abstractive Summarization

Reference 46

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source=arxiv_source observed=2026-08-04T18:37:55.062279Z digest=sha256:6605a4d0850653297fae3875311545b0dd60dab78e9ba0fe054a8849e71759eb

Observation 7784c14a-3e16-4766-94e0-9b7e058ffe37 · outbound

This paper cites Qwen2.5 Technical Report.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Qwen2.5 Technical Report

Reference 47

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source=arxiv_source observed=2026-08-04T18:37:55.065414Z digest=sha256:f19332128c35fd498ac984e377998b423f6c0342bd88ec2614c2a8c20974f8d3

Observation c9dd77dc-ef2a-49eb-8834-b91814cbd7a9 · outbound

This paper cites Sequence Level Training with Recurrent Neural Networks.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Sequence Level Training with Recurrent Neural Networks

Reference 48

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source=arxiv_source observed=2026-08-04T18:37:55.068718Z digest=sha256:52f505674e3cb4da8c5fd557b34bd58059c6c10b1999824194ee4ff760cfe915

Observation 6f250e1b-5068-46a7-b9d3-53da7bdfacf4 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 49

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source=arxiv_source observed=2026-08-04T18:37:55.071711Z digest=sha256:4556e97c012605c038c57f761219315c5586f0a0baad8d4987d76e7ad6415767

Observation 69a57bd8-8660-4b6a-95fa-31b852380ddb · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 50

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no resolver link, observed 2026-08-04T18:37:55.074475Z

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source=arxiv_source observed=2026-08-04T18:37:55.074475Z digest=sha256:1528fae579f8f5fcc6d1555b9e91380e9e869a203c1bde9c6a4e4aa388d2209b

Observation b1ce5533-43a7-40f0-a93c-156ed7d068d5 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 51

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no resolver link, observed 2026-08-04T18:37:55.077493Z

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source=arxiv_source observed=2026-08-04T18:37:55.077493Z digest=sha256:3147a8ad64adb429fe43853db39554e1bdebfa7a115e02800be7b411f1ca85d1

Observation c4d1ed95-af16-43d8-939d-4f0900b872e7 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 52

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no resolver link, observed 2026-08-04T18:37:55.080609Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-04T18:37:55.080609Z digest=sha256:5de2516c72b4176d17ae16b43a0bdda01758ac4e6294476064f660182d7b0f7e

Observation 418c39d3-aab7-4bee-95c8-38b5b7c78b90 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 53

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source=arxiv_source observed=2026-08-04T18:37:55.083675Z digest=sha256:b1173b74e16fa641087d4a8ef1a2fdf7d055c55377fd824585059ee1917b3ee9

Observation 9db541cb-f7f2-4e76-bb7c-85a6cc3f2790 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 54

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source=arxiv_source observed=2026-08-04T18:37:55.087039Z digest=sha256:afa3ec0076ec88ef6db78fd2745313fd05b2fa9c6e8070366e12f807e9f72f0b

Observation d29818ca-1d02-4479-90ab-6750604282ca · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 55

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no resolver link, observed 2026-08-04T18:37:55.089841Z

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source=arxiv_source observed=2026-08-04T18:37:55.089841Z digest=sha256:805b47e1f99ab3095ae6c3762f03e6ba19f18f4b0bce69d556f0760d4fbd9afb

Observation c54f623a-50dc-4002-8d6b-2255c17d4676 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 56

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unresolved
no resolver link, observed 2026-08-04T18:37:55.092759Z

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source=arxiv_source observed=2026-08-04T18:37:55.092759Z digest=sha256:6bae84dc80a9c0d30afaf3a922fcb5a14762f34b712b6a799112a9ca4b61f422

Observation db04bc93-9e02-44c6-8b9e-081f2e92d736 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 57

Resolution
verified exact
doi, observed 2026-08-04T18:38:35.073844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.095671Z digest=sha256:3c723defe9b13796b6c7888b9cbf722cfc14288d57045c561f78c64a7bae1a60

Observation daca5df7-61c3-4c2c-8934-051794284935 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 58

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no resolver link, observed 2026-08-04T18:37:55.098604Z

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source=arxiv_source observed=2026-08-04T18:37:55.098604Z digest=sha256:d17b84832ca216701b2d17be90181d60a3655a4a0b541c40f646ba3f27ec1d4f

Observation 528af9c1-db35-47db-bf29-2ccf5acd719e · outbound

This paper cites Direct Judgement Preference Optimization.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Direct Judgement Preference Optimization

Reference 59

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source=arxiv_source observed=2026-08-04T18:37:55.101448Z digest=sha256:fbe6abab1292ec28b4af20bad9462fe1bdc2b64144c52d6394c5c3470a417c7e

Observation 754482f6-c45f-41e1-88bc-7ce5e905bb45 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 60

Resolution
verified exact
doi, observed 2026-08-04T18:38:34.804247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.104698Z digest=sha256:9fc918415e6e5deb64b368bcbeab308ecfb007d25d1a0599ada7b6292c8f4929

Observation bc0a04bb-806c-4c86-9429-004e5d9072c3 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 61

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unresolved
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:55.107685Z digest=sha256:2a057c03fc4f609e0e61f75e7e371b61784a901c2b008f0162f73d9754d9ac1b

Observation 9e31c8f4-5b7c-409e-abd9-6aa17d7d0e82 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 62

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no resolver link, observed 2026-08-04T18:37:55.110523Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:55.110523Z digest=sha256:aba89cd3bb3de5fde5fa82144714a925aa06ccff76c7d5a47eade82f66cd92fc

Observation ec560527-21b8-4fe2-9980-9ae44ea49c45 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 63

Resolution
verified exact
doi, observed 2026-08-04T18:38:34.590690Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.113515Z digest=sha256:c99689f93f0350592341fe497544d6020fb54532a3f0732a23f38a5632e002dc

Observation 0e799114-89f2-4c3a-8d64-7dd523fc60eb · outbound

This paper cites J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization J4R: Learning to Judge with Equivalent Initial State Group Relative Policy Optimization

Reference 64

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no resolver link, observed 2026-08-04T18:37:55.117220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:55.117220Z digest=sha256:0e5885cb0e0718da8afa27be11e8bc0a84b8822b95f5a78cf4a53877df09f349

Observation b0841bb6-ce8d-4f04-bc9f-f1a733a6e8ed · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 65

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no resolver link, observed 2026-08-04T18:37:55.120683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:55.120683Z digest=sha256:1a0efa6239b602e253fe51b302733eab75d4a64cc754ea6a288ae90f1778b00a

Observation 434f5123-a3cb-4176-b0fc-b3c21c961028 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 66

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unresolved
no resolver link, observed 2026-08-04T18:37:55.123359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:55.123359Z digest=sha256:0801196f410088b9f1aee9a35fd0f7759f1e0956c6baba3836ffef978ee0cf7d

Observation 9b83dc87-1769-473e-9fcc-9c45b4f6513b · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 67

Resolution
verified exact
doi, observed 2026-08-04T18:38:34.373693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

source=arxiv_source observed=2026-08-04T18:37:55.126196Z digest=sha256:216006cc89c4fbade644849b2daef2618a383ea8c22ab4255a12ca765be771f2

Observation 6b02f4cf-8c24-475a-8010-0af7e54faa1b · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 68

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unresolved
no resolver link, observed 2026-08-04T18:37:55.129913Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:55.129913Z digest=sha256:7fed318f3bea1238ae791e5b6747b5603e620c42bac05b2c368e9e4aad7a8d23

Observation 68d76a46-569a-4e2a-9a14-24f3997134d3 · outbound

This paper cites an unresolved cited work.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Unresolved cited work

Reference 69

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unresolved
no resolver link, observed 2026-08-04T18:37:55.132929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:55.132929Z digest=sha256:4d3e8f6badec9ab9f333a923d5a60d33594ad817c218e47e9ce6018ae5e596e8

Observation 46569963-e6be-4e24-934e-02b481e9ec4b · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

Topic-Guided Reinforcement Learning with LLMs for Enhancing Multi-Document Summarization Fine-Tuning Language Models from Human Preferences

Reference 70

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no resolver link, observed 2026-08-04T18:37:55.135579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T18:37:55.135579Z digest=sha256:d0efcc049e6f602c821a24f017b94f391af6dc11e3de663c0fae1cad104732f2

Pith citing papers

No inbound Pith citation observations are available.