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Paper Citation Record · LEDGER

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India

As of 9 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 1 inbound Pith citation observation for arXiv:2509.08218.

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

pith.paper-citation-record.v1
2509.08218 v1

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T21:03:45.730206Z

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-13T17:11:50.540450Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T17:13:01.153039Z

Reference resolution

34 of 34 outbound references displayed

  • verified exact0
  • verified fuzzy27
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch3

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b7632207-8ba0-4299-b1b3-db9f19d9c366 · outbound

This paper cites International Journal of Indian Psychology12(3) (2024).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India International Journal of Indian Psychology12(3) (2024)

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:51.448827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.341874Z digest=sha256:5226f7e47c59639b5c81d1b18d956d5f34c2a6c07a3728c1910476ce361c2adb

Observation 059fc1f6-dcf8-42e6-a0b0-43ea049929e6 · outbound

This paper cites Harlequin, ??? (2023).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Harlequin, ??? (2023)

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:51.270653Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.414750Z digest=sha256:9ceb4c1bd49a4b5c7df045b4831260906950db5035319e53e5a4dae123be4f0c

Observation 73d66324-a0ec-488c-bb29-d00080ad599f · outbound

This paper cites Review of Agrarian Studies12(1), 161–173 (2022) 14.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Review of Agrarian Studies12(1), 161–173 (2022) 14

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:51.121437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.514774Z digest=sha256:f33ea8f610003c98c0f680a6accad0067eb533a52016d7f89f8ec69329d4ff87

Observation 295de14d-3b37-4b5c-8868-5c3b180a0fca · outbound

This paper cites https://neural-times.vercel.app/.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India https://neural-times.vercel.app/

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:50.728563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.586570Z digest=sha256:639c4ac12e18aef6310b94461b226a1fac05ff190596e52f90c3e971fd15bdfc

Observation 5dd613ba-6176-4b25-892c-b7bd8c3831ef · outbound

This paper cites In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, pp

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:50.533064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.618625Z digest=sha256:8f9d282de4ba745d5092240c872c8e777560bdb5a05c4488df8c4b3e7722ea05

Observation a2d48b5f-6205-4dc7-8095-c53179743406 · outbound

This paper cites In: Proceedings of the International AAAI Conference on Web and Social Media, vol.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Proceedings of the International AAAI Conference on Web and Social Media, vol

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:50.295329Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.641974Z digest=sha256:0b80117b6d6b4eaf3a2036dc8fbc2b8bf1461d8fecb07291c94ed463682d7390

Observation de27cc26-a6a8-412a-bb84-21b25b431f32 · outbound

This paper cites In: Proceedings of the 15th International Conference on Intelligent User Interfaces, pp.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Proceedings of the 15th International Conference on Intelligent User Interfaces, pp

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:50.070453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.719025Z digest=sha256:11b6b0a507e3e10e47443eb5a709d5573c798bb947e58b0c0465f7598a643f03

Observation 54bfebb7-9623-478c-a65f-6006d53715ce · outbound

This paper cites In: Handbook of Digital Journalism: Perspectives from South Asia, pp.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Handbook of Digital Journalism: Perspectives from South Asia, pp

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:49.874197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.797963Z digest=sha256:dca5d6a3656282316837b711b9adb8fb414ca9d5d921a520c8ebaa194fef8f8a

Observation 9ea3cf14-b832-4155-9a98-cfa0814474e7 · outbound

This paper cites Journal of biomedical informatics151, 104606 (2024).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Journal of biomedical informatics151, 104606 (2024)

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:49.668887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.839108Z digest=sha256:aff24f86180e8698d957c2f505f3a89122c11f9c5c1acd436195c0b64153ec8e

Observation cdb6e4cf-5206-4963-a225-ab2497467d39 · outbound

This paper cites Applying Automatic Text Summarization for Fake News Detection.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Applying Automatic Text Summarization for Fake News Detection

Reference 11

Resolution
metadata mismatch
local_arxiv, observed 2026-08-04T21:03:46.034757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:43.930619Z digest=sha256:50111581a991c09ceef0cdf87bdeeb5e1b8b7d9cb428bb406ab08b0afe568f28

Observation 793476ff-c691-4b92-94a8-ceea78865a60 · outbound

This paper cites In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:49.481782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.017003Z digest=sha256:8f8b7da2893a32a795ac9f2b3c5ea4948393fcfa8223a7d20e6eb9099fda9d8c

Observation d05c6225-cdf7-4a66-8c88-24d7e1fce32b · outbound

This paper cites Expert Systems with Applications192, 116292 (2022).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Expert Systems with Applications192, 116292 (2022)

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:49.259348Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.065140Z digest=sha256:7e3a4eb29145d52e057f3c13b1d293f49abbe95870df43cebdc7f97a28ba38ac

Observation 409dee3a-b88e-43f3-adf2-00b8900b7f22 · outbound

This paper cites In: 2024 IEEE International Conference on Artificial Intelligence Testing (AITest), pp.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: 2024 IEEE International Conference on Artificial Intelligence Testing (AITest), pp

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-04T21:03:44.163916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:03:44.163916Z digest=sha256:af06460adc623e95d61901cafdf8722bdd8d7348584487d102ba2ee7943c9fdb

Observation 0ebb9f26-90bd-4cc6-ae47-525b2291110d · outbound

This paper cites Multi-LLM Text Summarization.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Multi-LLM Text Summarization

Reference 15

Resolution
metadata mismatch
local_arxiv, observed 2026-08-04T21:03:45.949188Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.243276Z digest=sha256:f00d322864e9b69d7b8dd2d7dc7f4b4595a6b7217d95688d219eddf742fccacf

Observation 62f0c9cd-ddcc-4cac-89cc-f3ca13b63975 · outbound

This paper cites Authorea Preprints (2025).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Authorea Preprints (2025)

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:49.045341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.325973Z digest=sha256:7b8f6623b09c84a8a9256e72a70c972bce4956259b67280102d13e66b72c4a02

Observation bcd21346-6abb-43ea-8e07-cb3e617c06e9 · outbound

This paper cites A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India A Guide To Effectively Leveraging LLMs for Low-Resource Text Summarization: Data Augmentation and Semi-supervised Approaches

Reference 17

Resolution
metadata mismatch
local_arxiv, observed 2026-08-04T21:03:45.859517Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.401860Z digest=sha256:36ac29f371c8125f1eb21299e21c7ce243d8c9ed39c1065b1b97ff6f7e68152b

Observation d1f78af5-6755-40f3-ae45-1315acdc0765 · outbound

This paper cites FineSurE: Fine-grained Summarization Evaluation using LLMs.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India FineSurE: Fine-grained Summarization Evaluation using LLMs

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-04T21:03:44.490351Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:03:44.490351Z digest=sha256:992b093620b5f539b6e8636faf28a7dc22bb4bb25ca6b162c8e6ddbbf298cc27

Observation af3a1426-b13c-4a9f-b2ae-da7841e30806 · outbound

This paper cites In: Pacific Rim International Conference on Artificial Intelligence, pp.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Pacific Rim International Conference on Artificial Intelligence, pp

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:48.720294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.575221Z digest=sha256:d5ef4a91e9e5d9467501415f82c7074021d2d57d8203643d90d67b396bb28365

Observation 5dcd0944-1eda-42b5-8f20-9833945f4150 · outbound

This paper cites Journalism Practice3(1), 1–12 (2009).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Journalism Practice3(1), 1–12 (2009)

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:48.438961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.653338Z digest=sha256:18c0cf7d28a3d94c769156e816ae5c931712107e6b24931994fc046d2df5555f

Observation e7fdcbf8-6497-4682-8fc8-bede0590e24d · outbound

This paper cites European journal of communication6(4), 499–522 (1991).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India European journal of communication6(4), 499–522 (1991)

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:48.221619Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.703133Z digest=sha256:6fda9134b8d071d5c6c797892c235d491a135afb0d799ab17b2ff73f43148758

Observation 4fddfb57-985e-47a1-bb10-a99d4bda13fd · outbound

This paper cites Journalism Quarterly69(2), 436–446 (1992).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Journalism Quarterly69(2), 436–446 (1992)

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:47.917275Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.779755Z digest=sha256:a5694f0e4326aade9da6396bdd5e1cfe3ba423b26ffe144c53be123597230786

Observation 251343fb-cd28-4876-91a0-2856080d593c · outbound

This paper cites American Journal of Industrial and Business Management04, 567–572 (2014).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India American Journal of Industrial and Business Management04, 567–572 (2014)

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:47.733065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:44.922420Z digest=sha256:00b539c70eecbb902f94fc4d34b44eee450b642b752277e8599f470faade1ec9

Observation 526548bb-b113-4d5f-9320-0772683b181a · outbound

This paper cites International Journal of Human-Computer Interaction30, 343–368 (2014).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India International Journal of Human-Computer Interaction30, 343–368 (2014)

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:47.425671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.086887Z digest=sha256:0c2ec88713545ddd9dd4ea83ac717495cbfbe833fbacf6008f6b1f4c579e2753

Observation 6966fb1f-fe16-40f5-aeb5-57edae6b4a51 · outbound

This paper cites Social Science Quarterly101(2), 811–824 (2020).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Social Science Quarterly101(2), 811–824 (2020)

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:47.190330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.220871Z digest=sha256:61ba2a53def3b0c16c6cd0c42574cd3ac87f582aa057f49598adc2089eb84e60

Observation 2ea1b96b-e0b7-49b2-82a2-bb3e4d24c2cb · outbound

This paper cites In: Proceedings of the International AAAI Conference on Web and Social Media, vol.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Proceedings of the International AAAI Conference on Web and Social Media, vol

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:50.965965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.310587Z digest=sha256:83a3846fc0629a6c7c3b439a5c56de43751ad02f6b5f46f46ef252ce7d1c661e

Observation 2315e2fb-1b4a-43bd-b96e-4cd233bdf87e · outbound

This paper cites Reuters (2024).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Reuters (2024)

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:47.062297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.349800Z digest=sha256:181c0978fcf4691e6415f7139ecb68e10c2deaf9192fd3419d5515d8ee3a9d14

Observation 3cfe37de-696b-4d95-9bf9-1eb2f027e509 · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-04T21:03:45.434388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:03:45.434388Z digest=sha256:cd8cf73e1fc645af6e5bc731c59678430284b0c1ba55a3c8eb82535a71aa182e

Observation dcc49ce1-4ba1-4771-be05-a176831c03a8 · outbound

This paper cites The Llama 3 Herd of Models.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India The Llama 3 Herd of Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-04T21:03:45.510601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T21:03:45.510601Z digest=sha256:5d66f600e551f9954cd51e7a3984e6eeae997b84c732c9ca145ec75012aedf69

Observation fd289363-8c67-443a-9490-fd8d62bc9f5b · outbound

This paper cites https://drive.google.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India https://drive.google

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:46.884795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.557356Z digest=sha256:375ab7cb3ea927f7cf2e6b30a56f61a8fd611f3e7dc2edbbb9c1b3a7c2181815

Observation eba1c8ef-e933-4449-bbe5-71a4520861e5 · outbound

This paper cites Newspaper Research Journal42(2), 162–181 (2021).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Newspaper Research Journal42(2), 162–181 (2021)

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:46.640184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.600671Z digest=sha256:573e20ca8c701098f13ae599fc087a7544217805c9165f6acf388b5f77749d79

Observation b3615eb0-5bc7-4ca3-bb99-d82f948d41a6 · outbound

This paper cites Humanities and Social Sciences Communications11(1), 1–12 (2024).

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Humanities and Social Sciences Communications11(1), 1–12 (2024)

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:46.501033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.641669Z digest=sha256:ca4b9a2b271c5fd93afa9e09512bc3ceb4e6013f713a152384b9d145eb15ebd2

Observation c6f08245-c4ac-4c71-b411-c4ed5f54836e · outbound

This paper cites In: Proceedings of the 2024 8th International Conference on Natural Language Processing and Information Retrieval, pp.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Proceedings of the 2024 8th International Conference on Natural Language Processing and Information Retrieval, pp

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:46.318985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.661073Z digest=sha256:194e011349e3b473ef07ad0a69efb789bb046cabc13d698f0163db3022297a20

Observation 422ce5b4-8f8b-45bd-ab8a-8d4970bea74c · outbound

This paper cites In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India In: Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, pp

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:46.250636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.708214Z digest=sha256:c74c98af774c9e29e3e882fe69f2ed03b5264a84ad4385ba30a56af2e2f0c6ee

Observation effad047-627a-467d-b2e0-39a79aab3a55 · outbound

This paper cites Reading in a foreign language 23(1), 84–101 (2011) 17.

PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India Reading in a foreign language 23(1), 84–101 (2011) 17

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-04T21:03:46.123978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-04T21:03:45.730206Z digest=sha256:cc8a1e0c65466127ae97f6e596887d946ba4eb8c1ba0390b1489ce206d989879

Pith citing papers

Observation 2ec7234e-c444-4c17-b75a-da3e46e4772f · inbound

Method for Aggregating Unstructured Data Using Large Language Models cites this paper.

Method for Aggregating Unstructured Data Using Large Language Models PolicyStory: Leveraging Large Language Models to Generate Comprehensible Summaries of Policy-News in India

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-13T17:13:01.154435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-13T17:11:50.540450Z digest=sha256:bb46572d2659f510246368fbe5efa31e3be6b48f7eb5fdc25bee9217c3745afa