Paper Citation Record · LEDGER

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques

As of 8 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 2 inbound Pith citation observations for arXiv:2507.05123.

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

pith.paper-citation-record.v1
2507.05123 v1

Coverage vector

measured 78 of 78 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:37:22.081341Z

measured 80 of 80 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T22:45:31.935618Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T22:46:53.220410Z

Reference resolution

78 of 78 outbound references displayed

verified exact9
verified fuzzy19
unresolved40
parse uncertain0
malformed identifier5
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7f58d3c4-ac95-4c81-b650-c4601e143ffa · outbound

This paper cites Expert Systems with Applications 165, 113679 (2021) https://doi.org/10.1016/j.eswa.2020.113679.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Expert Systems with Applications 165, 113679 (2021) https://doi.org/10.1016/j.eswa.2020.113679

Reference 1

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T19:37:25.034468Z

Source-reported events for the cited work

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Observation 7a7eb954-676b-4013-bc85-2d60d4fc5bdd · outbound

This paper cites In: Riezler, S., Goldberg, Y.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Riezler, S., Goldberg, Y

Reference 2

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Source-reported events for the cited work

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Observation 506de1bf-fe3e-48c6-a145-4597f3e10ff3 · outbound

This paper cites Journal of King Saud University - Computer and Information Sciences 34(4), 1029–1046 (2022) https://doi.org/10.1016/j.jksuci.2020.05.006 32.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Journal of King Saud University - Computer and Information Sciences 34(4), 1029–1046 (2022) https://doi.org/10.1016/j.jksuci.2020.05.006 32

Reference 3

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Source-reported events for the cited work

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correction dated 2020-11-24. Source: crossref record 10.1016/j.jksuci.2020.11.017->10.1016/j.jksuci.2020.05.006:correction, observed 2026-07-11T03:15:16.524084+00:00. This notice travels one citation hop only.

correction dated 2020-11-25. Source: crossref record 10.1016/j.jksuci.2020.11.008->10.1016/j.jksuci.2020.05.006:correction, observed 2026-07-11T03:10:43.036446+00:00. This notice travels one citation hop only.

Observation 93c242f5-3cb2-4051-b1de-fc11190b76a6 · outbound

This paper cites IOP Conference Series: Materials Science and Engineering 1099(1), 012042 (2021) https://doi.org/10.1088/1757-899X/1099/ 1/012042.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques IOP Conference Series: Materials Science and Engineering 1099(1), 012042 (2021) https://doi.org/10.1088/1757-899X/1099/ 1/012042

Reference 4

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Source-reported events for the cited work

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Observation 639c6d81-d70c-4358-b25a-1d55c4f9abce · outbound

This paper cites Information Processing & Management 45(1), 20–34 (2009) https://doi.org/10.1016/j.ipm.2008.06.002.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Information Processing & Management 45(1), 20–34 (2009) https://doi.org/10.1016/j.ipm.2008.06.002

Reference 5

Resolution: verified exact; doi, observed 2026-08-06T19:37:23.288176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0cc17143-a059-40bb-8368-86c697ed9fb3 · outbound

This paper cites In: 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: 2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp

Reference 6

Resolution: metadata mismatch; raw_fallback, observed 2026-08-06T19:37:24.863753Z

Source-reported events for the cited work

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Observation 1f56ab0a-b7b2-4f88-bbe4-34425d92e880 · outbound

This paper cites Neural Computing and Applications 35, 18553–18570 (2023) https://doi.org/10.1007/s00521-023-08680-0.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Neural Computing and Applications 35, 18553–18570 (2023) https://doi.org/10.1007/s00521-023-08680-0

Reference 7

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Source-reported events for the cited work

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Observation 4937e121-ba88-4be0-a899-0ebc545c8cb6 · outbound

This paper cites In: Muresan, S., Nakov, P., Villavicencio, A.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Muresan, S., Nakov, P., Villavicencio, A

Reference 8

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Observation 96de1c8a-783c-45e2-afcb-50aae86b2e11 · outbound

This paper cites Neural Computing and Applications (2023) https://doi.org/10.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Neural Computing and Applications (2023) https://doi.org/10

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:28.409944Z

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Observation b32db519-5e85-4f2e-8728-f14f1e1701e2 · outbound

This paper cites In: 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP), pp.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: 2017 International Conference on Computer, Communication and Signal Processing (ICCCSP), pp

Reference 10

Resolution: verified exact; doi, observed 2026-08-06T19:37:23.046899Z

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Observation 7074de72-0359-4971-b05a-afb76bd46dd8 · outbound

This paper cites Neural Computing and Applications 32, 11491–11503 (2020) https://doi.org/10.1007/s00521-019-04638-3.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Neural Computing and Applications 32, 11491–11503 (2020) https://doi.org/10.1007/s00521-019-04638-3

Reference 11

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Observation 44f808b4-838d-4956-89c1-65da5ba3b090 · outbound

This paper cites In: 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), pp.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), pp

Reference 12

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Observation 9d460364-8fc5-4124-b5b9-cf16d1c60ebe · outbound

This paper cites an unresolved cited work.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:37:28.394721Z

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Observation 735156e4-1bdf-4f5e-9729-389c3fa33847 · outbound

This paper cites In: Latifi, S.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Latifi, S

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:28.377491Z

Source-reported events for the cited work

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Observation ccddb2bf-53be-4ae7-9b18-aba94e08c581 · outbound

This paper cites Applied Sciences 13(7) (2023) https://doi.org/10.3390/app13074610.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Applied Sciences 13(7) (2023) https://doi.org/10.3390/app13074610

Reference 16

Resolution: verified exact; doi, observed 2026-08-06T19:37:22.738774Z

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Observation 435bd82f-b1f3-4cd1-b213-2b8b04ea7f8d · outbound

This paper cites In: Webber, B., Cohn, T., He, Y., Liu, Y.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Webber, B., Cohn, T., He, Y., Liu, Y

Reference 17

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Observation 333b6ea5-b2c3-4016-b127-599899a3cfb6 · outbound

This paper cites In: 2019 International Joint Conference on Neural Networks (IJCNN), pp.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: 2019 International Joint Conference on Neural Networks (IJCNN), pp

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:17.773839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66415ca2-b6fb-4c29-b99d-355e0bf971ec · outbound

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Reference 19

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Observation 328fb085-2c86-474e-9fb0-68a33538eedd · outbound

This paper cites an unresolved cited work.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 20

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:37:28.332127Z

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Observation ae464cc9-2aca-4a94-91f1-9c6b4d432936 · outbound

This paper cites Z Sun: Evaluating large language models on medical evi- dence summarization.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Z Sun: Evaluating large language models on medical evi- dence summarization

Reference 21

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Observation 56d484e6-4723-4307-9232-08197849306d · outbound

This paper cites Generator-Retriever-Generator Approach for Open-Domain Question Answering.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Generator-Retriever-Generator Approach for Open-Domain Question Answering

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:18.009132Z

Source-reported events for the cited work

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Observation 60b24e12-645f-4087-a189-49a594aa1d8d · outbound

This paper cites an unresolved cited work.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 23

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Observation 4264c7bf-f3f7-4f37-a3d5-189ae9e72c9d · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques ACM Comput

Reference 24

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Source-reported events for the cited work

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Observation fb319519-47b3-41bf-bf55-c113173c43b7 · outbound

This paper cites Unleashing the potential of prompt engineering for large language models.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unleashing the potential of prompt engineering for large language models

Reference 25

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Observation 233358cc-e0e9-41dc-a00a-2fff4fdc16c4 · outbound

This paper cites A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques A Systematic Survey of Prompt Engineering in Large Language Models: Techniques and Applications

Reference 26

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Observation 3a763cb5-698f-4e07-9ca1-c583bf15f0d4 · outbound

This paper cites Prompt Design and Engineering: Introduction and Advanced Methods.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Prompt Design and Engineering: Introduction and Advanced Methods

Reference 27

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Accessed: 2024-01-22

Reference 28

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Observation 1905f742-926e-4340-b615-74b3f3e23de6 · outbound

This paper cites an unresolved cited work.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 29

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Observation 5ad74407-3a33-45e6-8f25-9fbcf53e3ce1 · outbound

This paper cites an unresolved cited work.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 30

Resolution: unresolved; raw_fallback, observed 2026-08-06T19:37:28.233530Z

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Observation 39c7d87e-637b-43de-8dfb-82643adac500 · outbound

This paper cites an unresolved cited work.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 31

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Observation aa18735e-9210-4256-a87b-06b9cc326c21 · outbound

This paper cites In: Inui, K., Jiang, J., Ng, V., Wan, X.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Inui, K., Jiang, J., Ng, V., Wan, X

Reference 32

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Observation f93d7435-e5fc-478e-9fa6-121e74dd587d · outbound

This paper cites In: Burstein, J., Doran, C., Solorio, T.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Burstein, J., Doran, C., Solorio, T

Reference 33

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Observation 3962b2e5-b213-4f93-afdd-75d1101d3bed · outbound

This paper cites Gambhir, V.G.: Deep learning-based extractive text summarization with word- level attention mechanism.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Gambhir, V.G.: Deep learning-based extractive text summarization with word- level attention mechanism

Reference 34

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Observation 16bd085c-aeec-4e2f-a25f-28de496abbde · outbound

This paper cites Neural Computing and Applications 35(25), 18603–18622 (2023).

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Neural Computing and Applications 35(25), 18603–18622 (2023)

Reference 35

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Observation 0ddb8930-1f35-4853-87cf-28ee6ee001b7 · outbound

This paper cites In: Korhonen, A., Traum, D., M` arquez, L.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Korhonen, A., Traum, D., M` arquez, L

Reference 36

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This paper cites In: Annual Meeting of the Association for Computational Linguistics (2019).

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Annual Meeting of the Association for Computational Linguistics (2019)

Reference 37

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Observation a3d4f6aa-9552-4ff8-acc0-523591c2ddd1 · outbound

This paper cites In: Durmus, E., Gupta, V., Liu, N., Peng, N., Su, Y.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Durmus, E., Gupta, V., Liu, N., Peng, N., Su, Y

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:27.738072Z

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Observation 51e00205-4fdb-4433-81d8-5cfb573f05dd · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 39

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Observation e30afa2b-20d8-4181-bf29-091aed100c2a · outbound

This paper cites an unresolved cited work.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 40

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Observation c0ba4e67-db20-4330-a613-38dbc732fcd8 · outbound

This paper cites an unresolved cited work.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 41

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Observation ca9b410b-2f60-4bed-b415-373a43872a2b · outbound

This paper cites In: Riloff, E., Chiang, D., Hockenmaier, J., Tsujii, J.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Riloff, E., Chiang, D., Hockenmaier, J., Tsujii, J

Reference 42

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Observation c3e3fabe-17ff-439e-96eb-2902da64bc16 · outbound

This paper cites In: Isabelle, P., Charniak, E., Lin, D.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Isabelle, P., Charniak, E., Lin, D

Reference 43

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This paper cites In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:27.005599Z

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Observation 753f893d-a1a6-49d7-bb47-18ac06c8232e · outbound

This paper cites Introducing ChatGPT.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Introducing ChatGPT

Reference 45

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Observation 2b236559-b088-42a1-9688-62b1f520ce7f · outbound

This paper cites In: Text Summarization Branches Out, pp.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Text Summarization Branches Out, pp

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:26.588139Z

Source-reported events for the cited work

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Observation 52d4ec70-f7ba-4aac-97d7-3605654dafb9 · outbound

This paper cites In: Goldstein, J., Lavie, A., Lin, C.-Y., Voss, C.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Goldstein, J., Lavie, A., Lin, C.-Y., Voss, C

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:26.412313Z

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Reference 48

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Rogers, A., Boyd-Graber, J., Okazaki, N

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This paper cites (eds.) Proceedings of the 2022 Conference on Empirical Methods in Natural Language Process- ing, pp.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Larochelle, H., Ranzato, M., Hadsell, R., Bal- can, M.F., Lin, H

Reference 51

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 52

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Unavailable: canonical work link unavailable.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:25.881717Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0aa2c055-b20d-4541-b5c5-707c563e743d · outbound

This paper cites In: Proceedings of the 2nd Workshop on New Frontiers in Summarization.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Proceedings of the 2nd Workshop on New Frontiers in Summarization

Reference 54

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Unavailable: canonical work link unavailable.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Walker, M., Ji, H., Stent, A

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:25.796978Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 148d48a7-e729-4bb2-9f78-8a8e1aa82d79 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques ACM Trans

Reference 56

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Unavailable: canonical work link unavailable.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques What learning algorithm is in-context learning? Investigations with linear models

Reference 57

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Unavailable: canonical work link unavailable.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Krause, A., Brunskill, E., Cho, K., Engelhardt, B., Sabato, S., Scarlett, J

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:25.682367Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2fbe0b92-6868-4c97-bd86-61e9604a8acf · outbound

This paper cites OpenAI blog 1(8), 9 (2019).

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques OpenAI blog 1(8), 9 (2019)

Reference 59

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8e8f39c3-9ca0-451f-a92e-861abf5e104f · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Korhonen, A., Titov, I

Reference 60

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Observation 8628535e-f9be-4ca4-a697-ecd4bee1e85a · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 61

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ccd5defc-02c2-4b1e-aa38-f548cbe9361b · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Autoregressive Models: What Are They Good For?

Reference 62

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Unavailable: canonical work link unavailable.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Unresolved cited work

Reference 63

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f886bbfb-3c4b-4bb9-90a9-7fd45ca480d7 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Barolli, L

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:25.266491Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fbbe1b97-fe18-462d-8cf6-e6e14c93ab29 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Mistral 7B

Reference 65

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Unavailable: canonical work link unavailable.

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This paper cites https://storage.googleapis.com/deepmind-media/gemma/ gemma-report.pdf.

An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques https://storage.googleapis.com/deepmind-media/gemma/ gemma-report.pdf

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:37:25.139053Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 46d8fbb2-f8ff-4d57-8da0-46b0be5583f1 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Mixtral of Experts

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:21.416231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques A Survey on Mixture of Experts in Large Language Models

Reference 68

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b4eab4f-2560-48d7-8d92-321c7b7779ae · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension

Reference 69

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Observation ef12264c-a430-44bb-bad4-ed7a95217e52 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques IEEE Transactions on Visualization & Computer Graphics 29(01), 1146–1156 (2023) https://doi.org/10.1109/TVCG.2022.3209479

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Unavailable: canonical work link unavailable.

Observation 2c781ccf-4d98-4d06-9347-fc68f8ad6215 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Prompt Engineering for Healthcare: Methodologies and Applications

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:21.734141Z

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Unavailable: canonical work link unavailable.

Observation b9850b7d-0f23-446c-afb5-60dd8eec0368 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Is Temperature the Creativity Parameter of Large Language Models?

Reference 72

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Unavailable: canonical work link unavailable.

Observation e2dd1364-8431-4600-ae62-06857cb785fc · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques A Survey on In-context Learning

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-06T19:37:21.869358Z

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Observation 2f088098-6b48-42c2-a1fc-0ce95e94a7a9 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques IEEE Access 9, 156043–156070 (2021) https://doi.org/10.1109/ACCESS.2021.3129786

Reference 74

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2dc1f1f5-e416-4e24-829f-4c94fac9a615 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques Neural Text Summarization: A Critical Evaluation

Reference 75

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Unavailable: canonical work link unavailable.

Observation 86ed0189-4293-494d-bf93-cd9b655e98a0 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques In: Webber, B., Cohn, T., He, Y., Liu, Y

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Unavailable: canonical work link unavailable.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques https://doi.org/ 10.18653/v1/2021.naacl-srw.20

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Resolution: verified exact; doi, observed 2026-08-06T19:37:22.424002Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 762fd8ea-bad0-42ed-803b-14043da0ee71 · outbound

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques https://doi.org/10.18653/v1/N18-2097

Reference 621

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Unavailable: canonical work link unavailable.

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An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques https://doi.org/10.18653/v1/D19-1387

Reference 3740

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Unavailable: canonical work link unavailable.

Pith citing papers

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Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends cites this paper.

Copyright Protection for Large Language Models: A Survey of Methods, Challenges, and Trends An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques

Reference 5

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7524fdb2-de73-4eb3-a746-f6a539e73ecd · inbound

Making AI Evaluation Deployment Relevant Through Context Specification cites this paper.

Making AI Evaluation Deployment Relevant Through Context Specification An Evaluation of Large Language Models on Text Summarization Tasks Using Prompt Engineering Techniques

Reference 32

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.