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Paper Citation Record · LEDGER

A Survey on LLM-based News Recommender Systems

As of 9 August 2026, this Paper Citation Record lists 100 of 104 outbound references and 2 inbound Pith citation observations for arXiv:2502.09797.

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

pith.paper-citation-record.v1
2502.09797 v2

Coverage vector

measured 100 of 104 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:29:26.764891Z

measured 102 of 102 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T23:04:03.682459Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T16:07:08.455378Z

Reference resolution

100 of 104 outbound references displayed

  • verified exact5
  • verified fuzzy61
  • unresolved34
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5a3963ff-8f09-4ab7-a000-cdb805e70354 · outbound

This paper cites NPA: Neural news recommendation with personalized attention,.

A Survey on LLM-based News Recommender Systems NPA: Neural news recommendation with personalized attention,

Reference 1

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Observation 6beeb580-cb26-4169-9351-da18c053c5b6 · outbound

This paper cites Drn: A deep reinforcement learning framework for news recommendation,.

A Survey on LLM-based News Recommender Systems Drn: A deep reinforcement learning framework for news recommendation,

Reference 2

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Observation 84c20cf4-3733-4d8f-871f-77f7a03dd489 · outbound

This paper cites Personalized news recommendation: Methods and challenges,.

A Survey on LLM-based News Recommender Systems Personalized news recommendation: Methods and challenges,

Reference 3

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Observation 9b115235-f59c-414e-991f-e9ee141c68e0 · outbound

This paper cites DKN: Deep knowledge-aware network for news recommendation,.

A Survey on LLM-based News Recommender Systems DKN: Deep knowledge-aware network for news recommendation,

Reference 4

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Observation 870dd949-1207-420d-81dc-b4aa6bd4e236 · outbound

This paper cites Fine-grained interest matching for neural news recommendation,.

A Survey on LLM-based News Recommender Systems Fine-grained interest matching for neural news recommendation,

Reference 5

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Observation 762cbbb1-2a5c-4dd4-827e-5b00f933ec4b · outbound

This paper cites Neural news recommendation with topic-aware news representation,.

A Survey on LLM-based News Recommender Systems Neural news recommendation with topic-aware news representation,

Reference 6

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Observation c6b9423b-0f81-45bc-b7ac-f42d86dad402 · outbound

This paper cites Neural news recommendation with long-and short-term user represen- tations,.

A Survey on LLM-based News Recommender Systems Neural news recommendation with long-and short-term user represen- tations,

Reference 7

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Observation 88cad664-e6ac-479c-a1e8-c99d4671b68c · outbound

This paper cites News recommendation via multi-interest news sequence modelling,.

A Survey on LLM-based News Recommender Systems News recommendation via multi-interest news sequence modelling,

Reference 8

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Observation bde3d05f-dc41-4582-9b22-cf75a35d069d · outbound

This paper cites Graph neural news recommendation with long-term and short-term interest modeling,.

A Survey on LLM-based News Recommender Systems Graph neural news recommendation with long-term and short-term interest modeling,

Reference 9

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Observation 0212c497-43a8-4d2f-9b6e-d36760529322 · outbound

This paper cites Neural news recommen- dation with collaborative news encoding and structural user encoding,.

A Survey on LLM-based News Recommender Systems Neural news recommen- dation with collaborative news encoding and structural user encoding,

Reference 10

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source=pdf_text observed=2026-08-07T20:29:26.335022Z digest=sha256:bee05f0cf1f354a8d9c987a2ffc84f631085a2f93172443f6f2e1c10bfebea74

Observation 760e1563-cf46-4b44-8b82-e1938a667b04 · outbound

This paper cites Graph neural news recommendation with user existing and potential interest modeling,.

A Survey on LLM-based News Recommender Systems Graph neural news recommendation with user existing and potential interest modeling,

Reference 11

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Observation 6482306e-2ddd-4661-81aa-67ba7036a3da · outbound

This paper cites Intention-aware user modeling for personalized news recommendation,.

A Survey on LLM-based News Recommender Systems Intention-aware user modeling for personalized news recommendation,

Reference 12

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source=pdf_text observed=2026-08-07T20:29:26.344450Z digest=sha256:f0db93b51b944104391456ff88fae3a767c56fb821e2644c8d3e67805d221664

Observation dc999ae2-9869-49ea-9d8a-4dc897e94f14 · outbound

This paper cites Attention is all you need,.

A Survey on LLM-based News Recommender Systems Attention is all you need,

Reference 13

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source=pdf_text observed=2026-08-07T20:29:26.349600Z digest=sha256:ff8750c61449188d3da08b1df045320948ffafbf209e88e1411f7913c9ef08b0

Observation d871f637-0e5f-4b11-9e1f-1a675ce5db87 · outbound

This paper cites Fastformer: Additive Attention Can Be All You Need.

A Survey on LLM-based News Recommender Systems Fastformer: Additive Attention Can Be All You Need

Reference 14

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source=pdf_text observed=2026-08-07T20:29:26.354312Z digest=sha256:93221378d5de327b633500399943ceaa4eaa8c3fe387827b31fd3b057342b583

Observation b8b57fca-f9b4-4ee1-ac98-c5e50c8811c8 · outbound

This paper cites Empowering news recommendation with pre-trained language models,.

A Survey on LLM-based News Recommender Systems Empowering news recommendation with pre-trained language models,

Reference 15

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Observation 3044fe4b-ca59-4fcf-a037-a12bd3d4f0cb · outbound

This paper cites Multimodal recommender systems: A survey,.

A Survey on LLM-based News Recommender Systems Multimodal recommender systems: A survey,

Reference 16

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source=pdf_text observed=2026-08-07T20:29:26.364041Z digest=sha256:533a42cd1014c781d146685e12a141d4910e02cf01d300fe203b9b22147f4e3a

Observation a8c9f692-ac7c-401f-a6b7-b8a3dc140e76 · outbound

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

A Survey on LLM-based News Recommender Systems Bert: Pre-training of deep bidirectional transformers for language understanding,

Reference 17

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Observation c705553f-a9b0-4378-8a38-e22917736081 · outbound

This paper cites Transformers: State-of-the-art natural language processing,.

A Survey on LLM-based News Recommender Systems Transformers: State-of-the-art natural language processing,

Reference 18

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Observation 6cb71c94-8275-4c7c-bb8e-dfb64a6f1a4b · outbound

This paper cites A survey on large language models for recommendation,.

A Survey on LLM-based News Recommender Systems A survey on large language models for recommendation,

Reference 19

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source=pdf_text observed=2026-08-07T20:29:26.378561Z digest=sha256:68bbb9491dcbefd17047dfa96a33a05f49a3d6b01b19f4a2c1b8d09c18745bee

Observation 1d07023c-7eaa-496d-84a9-28e22c8a5a9c · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

A Survey on LLM-based News Recommender Systems RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 20

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source=pdf_text observed=2026-08-07T20:29:26.383764Z digest=sha256:8d05e06168d6bbbc03e355e74d7a1a43052a99764f59b7e9e195bff1056b0de5

Observation c4b7bbdd-2672-4134-9327-932ca4d46809 · outbound

This paper cites BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension.

A Survey on LLM-based News Recommender Systems BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 21

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Observation f3771b40-9e59-414a-8c99-b5e2ea2ad119 · outbound

This paper cites Mtrec: Multi-task learning over bert for news recommendation,.

A Survey on LLM-based News Recommender Systems Mtrec: Multi-task learning over bert for news recommendation,

Reference 22

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Observation c8ba9336-8ea2-40ce-ad08-5cb8116fe0a2 · outbound

This paper cites MINER: Multi-interest matching network for news recommendation,.

A Survey on LLM-based News Recommender Systems MINER: Multi-interest matching network for news recommendation,

Reference 23

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source=pdf_text observed=2026-08-07T20:29:26.398695Z digest=sha256:04a95473460d0ed0840d9c4ea2b0371cdf5ad3b27086553b02ff4ae0afb5b190

Observation 2dee24ea-07d3-4978-93f2-4da49f1da268 · outbound

This paper cites Unitrec: A unified text-to-text transformer and joint contrastive learning framework for text-based recommendation,.

A Survey on LLM-based News Recommender Systems Unitrec: A unified text-to-text transformer and joint contrastive learning framework for text-based recommendation,

Reference 24

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Observation 58633adc-c8fe-4508-8760-607ecdb6bd60 · outbound

This paper cites Amm: Attentive multi-field matching for news recommendation,.

A Survey on LLM-based News Recommender Systems Amm: Attentive multi-field matching for news recommendation,

Reference 25

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source=pdf_text observed=2026-08-07T20:29:26.408415Z digest=sha256:09c10430bb3289f1f10cba7baead31dfabc5dfb8cfbba05c2fe075beda7581c9

Observation ba54273c-4113-41ae-a2e4-33ba02eb8fe0 · outbound

This paper cites NewsBERT: Distilling Pre-trained Language Model for Intelligent News Application.

A Survey on LLM-based News Recommender Systems NewsBERT: Distilling Pre-trained Language Model for Intelligent News Application

Reference 26

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source=pdf_text observed=2026-08-07T20:29:26.412865Z digest=sha256:f282ead7fb5d1655c5c07e666a9317c8cef97306dc9cbec7e080eb1cd2cb7367

Observation 36ada171-93e5-4d41-9faa-ff102915293a · outbound

This paper cites Unbert: User-news matching bert for news recommendation.

A Survey on LLM-based News Recommender Systems Unbert: User-news matching bert for news recommendation

Reference 27

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source=pdf_text observed=2026-08-07T20:29:26.418529Z digest=sha256:02b03f4ac18ade035f5710d6af1fe3fbeb4f727e4498accae3a8a89a40a8ac4f

Observation 39a5b070-654c-485c-99d1-a5c9a9645b8e · outbound

This paper cites Generative news recommendation,.

A Survey on LLM-based News Recommender Systems Generative news recommendation,

Reference 28

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source=pdf_text observed=2026-08-07T20:29:26.423206Z digest=sha256:2f67da0e5bef4297677f324ef324067f0b4fd3b450fb5087f2411baecd9ad16f

Observation 3fee0397-3d70-4897-988e-79fbd3b1ecdf · outbound

This paper cites Rewriting bias: Mitigating media bias in news recommender systems through automated rewriting,.

A Survey on LLM-based News Recommender Systems Rewriting bias: Mitigating media bias in news recommender systems through automated rewriting,

Reference 29

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Observation 429f4b44-fa36-4619-b48f-24b5f4b8a672 · outbound

This paper cites Lkpnr: Large language models and knowledge graph for personalized news recommendation framework.

A Survey on LLM-based News Recommender Systems Lkpnr: Large language models and knowledge graph for personalized news recommendation framework

Reference 30

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source=pdf_text observed=2026-08-07T20:29:26.432006Z digest=sha256:03a85af248edef608a569d58da5b6b43f713312fa2e90aba59caae622cb20ab6

Observation 7d7068b5-c8c2-4042-b4ed-43118516b04d · outbound

This paper cites A survey of personalized news recommendation,.

A Survey on LLM-based News Recommender Systems A survey of personalized news recommendation,

Reference 31

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source=pdf_text observed=2026-08-07T20:29:26.436009Z digest=sha256:f57734e49cb5d28b098fa5dbae5acdb1d99ae87bf61df3813746ab81c8b39aed

Observation d4e6947e-77f3-49d9-8656-3443772e8c60 · outbound

This paper cites A survey on knowledge- aware news recommender systems,.

A Survey on LLM-based News Recommender Systems A survey on knowledge- aware news recommender systems,

Reference 32

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source=pdf_text observed=2026-08-07T20:29:26.440359Z digest=sha256:2e055fc418f33c40e9d1cf200fdba8e415b62e6336018a16c07930f0e6eccd65

Observation 66228d0e-6a6e-4281-b0d5-0b0db6dc0fb1 · outbound

This paper cites Dan: Deep atten- tion neural network for news recommendation,.

A Survey on LLM-based News Recommender Systems Dan: Deep atten- tion neural network for news recommendation,

Reference 33

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.445090Z digest=sha256:72ec7deaf01ab30b4d1966cd7cc06843ed37e4d817eca285acff61f3c5394591

Observation 9810819e-d0c0-4783-ae0d-d4726f732d58 · outbound

This paper cites Wg4rec: Modeling textual content with word graph for news recommendation,.

A Survey on LLM-based News Recommender Systems Wg4rec: Modeling textual content with word graph for news recommendation,

Reference 34

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.450354Z digest=sha256:41938f7b842b4e474528c595c07e8e9c6e064121a93f94e2418d5e4a8bbb979d

Observation 60d8bf5a-c1ad-49cf-b1ea-4d994f5af89c · outbound

This paper cites Hram: A hybrid recurrent attention machine for news recommendation,.

A Survey on LLM-based News Recommender Systems Hram: A hybrid recurrent attention machine for news recommendation,

Reference 35

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source=pdf_text observed=2026-08-07T20:29:26.454675Z digest=sha256:270f97d8e9728b3fb7b96c7054384a1ccb7a2ca1e0d0f16d0b3fa2b41c92488e

Observation 62659bef-d0c7-4221-bbe9-1a7370e7f602 · outbound

This paper cites Trnews: Heterogeneous user-interest transfer learning for news recommendation,.

A Survey on LLM-based News Recommender Systems Trnews: Heterogeneous user-interest transfer learning for news recommendation,

Reference 36

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source=pdf_text observed=2026-08-07T20:29:26.458759Z digest=sha256:b9fcdf5c449faca226085c0b0af489cf00c734b29e907879d2abb19cbc821f28

Observation e061e288-235d-495e-bd2c-616032c8d71c · outbound

This paper cites Embedding-based news recommendation for millions of users,.

A Survey on LLM-based News Recommender Systems Embedding-based news recommendation for millions of users,

Reference 37

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.463050Z digest=sha256:9edd90b00d5a1ffe79ccbb5e354df1aa0cfa4f7ac7a332e6d697301dd7d28567

Observation 0a7d98f6-4048-41ad-a437-67569ccebe87 · outbound

This paper cites Time-aware attentive neural network for news recommendation with long-and short- term user representation,.

A Survey on LLM-based News Recommender Systems Time-aware attentive neural network for news recommendation with long-and short- term user representation,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.938732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.468198Z digest=sha256:e65cdbe9daa8fc5c933e3b8152dff1a6af305de987ac19215baecfcefaf55ed1

Observation 412d3bd0-4e85-4e58-936e-1f6494cb3fdf · outbound

This paper cites News recommendation with topic-enriched knowledge graphs,.

A Survey on LLM-based News Recommender Systems News recommendation with topic-enriched knowledge graphs,

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.924738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.472522Z digest=sha256:db214668fae4bdfe8c6363f68381ee08ef2f4c09b3a71b5850e10f329c5d4807

Observation 0ec07ee0-5c0e-4e90-b689-bab0cf8d3435 · outbound

This paper cites Weave&rec: A word embedding based 3-d convolutional network for news recommendation,.

A Survey on LLM-based News Recommender Systems Weave&rec: A word embedding based 3-d convolutional network for news recommendation,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.910976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.477225Z digest=sha256:de6e1f437d85263fe89ce7dca10b8d79ab32753cbbe7e939a5261e2a527f9ce1

Observation f5fac137-8725-441d-87bb-c46795fd5239 · outbound

This paper cites Deep neural networks for news recommendations,.

A Survey on LLM-based News Recommender Systems Deep neural networks for news recommendations,

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.897269Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.482675Z digest=sha256:9ec90d99010035476dea9d79b2def997643860822f77b0c378088daa0ff7de25

Observation 758a9b5c-7d43-452c-ae2d-7cc2a9ce9b79 · outbound

This paper cites Chameleon: a deep learning meta-architecture for news recommender systems,.

A Survey on LLM-based News Recommender Systems Chameleon: a deep learning meta-architecture for news recommender systems,

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.882407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.487275Z digest=sha256:5f186313ea4aff19f4c6bf445fd5c39a0f8909f40004cd085ab67c6f30a97d69

Observation 8eadef9d-a616-464f-bd49-b9c959407d07 · outbound

This paper cites Neural news recommendation with multi-head self-attention,.

A Survey on LLM-based News Recommender Systems Neural news recommendation with multi-head self-attention,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.867636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.491877Z digest=sha256:dd0eaeafdbfd679a24a4acacae05f1a9150accc720941aeec549e3d595db6df9

Observation 0dca8d58-ac78-4827-99e2-5c2911140439 · outbound

This paper cites Dynamic attention-integrated neural network for session-based news recommendation,.

A Survey on LLM-based News Recommender Systems Dynamic attention-integrated neural network for session-based news recommendation,

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.853435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.496001Z digest=sha256:055af6bd0e9ce709dc57aea15c42c17459c0db57c96bcc6861c12c2f78660fe7

Observation efcfc597-7315-40ed-be10-a1b2b8054227 · outbound

This paper cites Dynamic news recommenda- tion with hierarchical attention network,.

A Survey on LLM-based News Recommender Systems Dynamic news recommenda- tion with hierarchical attention network,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.839490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.500623Z digest=sha256:bf2cf035b00e86f3cd66691bc4ec4173939121ec905e13f07d3733fcd0aaa1ff

Observation 85440772-a314-49b0-8fce-a7b95977ead2 · outbound

This paper cites Si-news: Integrating social information for news recommendation with attention-based graph convolutional net- work,.

A Survey on LLM-based News Recommender Systems Si-news: Integrating social information for news recommendation with attention-based graph convolutional net- work,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.825419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.505505Z digest=sha256:d23985488af02b40b1709dd30995718b70c9158d548ff42dec399693f80ee4c4

Observation a1c997bc-1b13-4fe8-9e2b-c56703a5b3e9 · outbound

This paper cites Graph enhanced representation learning for news recommendation,.

A Survey on LLM-based News Recommender Systems Graph enhanced representation learning for news recommendation,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.811077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.510133Z digest=sha256:c13e096360152fbbee7ca0a618b79679c5c65bfc90a102910a34d34dd8b33066

Observation 00361495-0bcc-4eea-b2cf-16c1789c40a3 · outbound

This paper cites Joint knowledge pruning and recurrent graph convolution for news recommendation,.

A Survey on LLM-based News Recommender Systems Joint knowledge pruning and recurrent graph convolution for news recommendation,

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.797367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.515242Z digest=sha256:f285bd1cff07b42246b57839b4818734a91d2ceb42f7387ea719a2eeeb1cdd53

Observation 8087ec50-30a4-49b0-97f1-ba5f507bc93a · outbound

This paper cites Rein- forced anchor knowledge graph generation for news recommen- dation reasoning,.

A Survey on LLM-based News Recommender Systems Rein- forced anchor knowledge graph generation for news recommen- dation reasoning,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.782818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.519583Z digest=sha256:15d40d2f2e1ec6e755aaf304533c273ac0cb4c25746e046f04f5b85c10f4a5f6

Observation 50fed401-4c42-42e8-a8d2-420ad0cb22b4 · outbound

This paper cites Kred: Knowledge-aware document representation for news recommendations,.

A Survey on LLM-based News Recommender Systems Kred: Knowledge-aware document representation for news recommendations,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.767420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.524836Z digest=sha256:4e80e220501ad674fd9b3754e98d4cf4a1321bc378789d69053f1281ecb6a78e

Observation 0ab3e044-fd11-4c1e-8a73-52f869fc1f90 · outbound

This paper cites Knowledge-guided article embedding refinement for session-based news recommenda- tion,.

A Survey on LLM-based News Recommender Systems Knowledge-guided article embedding refinement for session-based news recommenda- tion,

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.753048Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.529062Z digest=sha256:2b5004a1631a94f88bf73aa95e91d6d4f88ec6df8259d103f5987774952e13a2

Observation cdda7c7e-86db-4fac-9834-13039e8e63fa · outbound

This paper cites Neural news recommendation with attentive multi-view learning,.

A Survey on LLM-based News Recommender Systems Neural news recommendation with attentive multi-view learning,

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.737985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.533245Z digest=sha256:e5e45e5d5b1a90d2e76f663b939fe21251d21702ecae8a6a440aefe705c39b3f

Observation bb1b3bd5-c520-4527-8336-6c8ce9c1e701 · outbound

This paper cites Aspect-driven user preference and news representation learning for news recommendation,.

A Survey on LLM-based News Recommender Systems Aspect-driven user preference and news representation learning for news recommendation,

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.722183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.538466Z digest=sha256:2a732115f91c9e8144b303f4b5042d7219a5d05a58a7dd3ec82ba3ce6ddbc935

Observation 78d9c381-a532-4a19-9d81-bfb2c5e8d2fc · outbound

This paper cites Hi-fi ark: Deep user representation via high-fidelity archive network.

A Survey on LLM-based News Recommender Systems Hi-fi ark: Deep user representation via high-fidelity archive network

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.708097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.543071Z digest=sha256:09ae05b3013c953aa7b428c36d5327a54a7b89994b7c8bda2e8e85c2ac161a23

Observation 39333e6e-7dc9-41ad-90d8-9609ef1145fe · outbound

This paper cites Neural news recommendation with heterogeneous user behavior,.

A Survey on LLM-based News Recommender Systems Neural news recommendation with heterogeneous user behavior,

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.692610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.548260Z digest=sha256:83be1d23790d7b4b741f32289664acbd9ad52a256c5a591c40b300442e7fc155

Observation 1aa91d93-1927-4b90-98f2-be1fca474dc6 · outbound

This paper cites Towards better rep- resentation learning for personalized news recommendation: A multi-channel deep fusion approach,.

A Survey on LLM-based News Recommender Systems Towards better rep- resentation learning for personalized news recommendation: A multi-channel deep fusion approach,

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.678560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.552474Z digest=sha256:3d289f36bf0964229a6817cffbe8a319f40897ba6fe3e0bb00173f2a4b1642b4

Observation 7e3f855b-748b-4945-b397-0b8f662d5a93 · outbound

This paper cites HieRec: Hierarchical user interest modeling for personalized news recommendation,.

A Survey on LLM-based News Recommender Systems HieRec: Hierarchical user interest modeling for personalized news recommendation,

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.665058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.556513Z digest=sha256:c150a8ecaa08625c4dfb40934031cef433cdbb85bd4b6ca9da2ec481491c8c46

Observation b7e73925-fd0e-4671-96e6-3f5e533afa46 · outbound

This paper cites Pp-rec: News rec- ommendation with personalized user interest and time-aware news popularity,.

A Survey on LLM-based News Recommender Systems Pp-rec: News rec- ommendation with personalized user interest and time-aware news popularity,

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.650648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.561046Z digest=sha256:5e6ced3bd889fab1ba85c9918287f379ebb63064bca69000e80de63e03523270

Observation 444221a9-9811-4fa5-9a0f-06a6b0649322 · outbound

This paper cites News recommendation with candidate-aware user mod- eling,.

A Survey on LLM-based News Recommender Systems News recommendation with candidate-aware user mod- eling,

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.636562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.565660Z digest=sha256:247d028920e2a71f0295142de4d8b03c7743932217ab7f093f9e76f246cfd0e8

Observation ebafb6fb-e629-4fd1-b5be-b0183f54da1a · outbound

This paper cites Popularity-enhanced news recommendation with multi-view interest representation,.

A Survey on LLM-based News Recommender Systems Popularity-enhanced news recommendation with multi-view interest representation,

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.623157Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.570965Z digest=sha256:af4ca6794d55debd77c251a19c7c23eee98d09cc2a716a98568f43bcf096bcfe

Observation d93393d7-c865-476c-a5d8-6c56ad3b05d6 · outbound

This paper cites Intention nets: Psychology-inspired user choice behavior mod- eling for next-basket prediction,.

A Survey on LLM-based News Recommender Systems Intention nets: Psychology-inspired user choice behavior mod- eling for next-basket prediction,

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.608485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.575441Z digest=sha256:5640a6c592b32148853d87cc27e4386d1dec6b0856e42c03c912de0f5edc565f

Observation fac5e695-0bc2-49d9-800b-ab02bedff6a2 · outbound

This paper cites Sentirec: Sentiment diversity-aware neural news recommendation,.

A Survey on LLM-based News Recommender Systems Sentirec: Sentiment diversity-aware neural news recommendation,

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.593340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.580660Z digest=sha256:a26b195f7c2dae1fefa98283bf30345b940ce31a15a3eadcd8b65641b73cffd2

Observation 9b97c333-4962-4e71-a6ae-739e2ea0fa30 · outbound

This paper cites Removing ais sentiment manipulation of personalized news delivery,.

A Survey on LLM-based News Recommender Systems Removing ais sentiment manipulation of personalized news delivery,

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.578622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.585160Z digest=sha256:3956aa2728d66078fd167940f4d69f358d65f8c1a9ee5e7fb2b4b5b0f6059794

Observation 00adc51f-0546-4151-912d-ca46be960650 · outbound

This paper cites Fairness-aware news recommendation with decomposed adversarial learning,.

A Survey on LLM-based News Recommender Systems Fairness-aware news recommendation with decomposed adversarial learning,

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.563277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.590825Z digest=sha256:812ed322c914f5f7022ddecc28a27cc9d44f7a59ef6edca28c4fdd05534f34ed

Observation 748f5f43-8cf6-4af4-903c-b15aa917d480 · outbound

This paper cites A hierarchical and disentangling interest learning framework for unbiased and true news recommendation,.

A Survey on LLM-based News Recommender Systems A hierarchical and disentangling interest learning framework for unbiased and true news recommendation,

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.549187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.595239Z digest=sha256:50bdbc4504e65ef08e816f8a0d652a835855938be17a350b7a2860af718a9737

Observation 7c47ff0e-468a-4700-8129-c15eb1af2755 · outbound

This paper cites Privacy-Preserving News Recommendation Model Learning.

A Survey on LLM-based News Recommender Systems Privacy-Preserving News Recommendation Model Learning

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T20:29:26.599864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:29:26.599864Z digest=sha256:ddab6b73cbf2d28e420edcdee30fce72ec9b598c5d18383eda6aec4fc4fe9e00

Observation cd4e5c7a-3b39-4558-b255-bd192993f7a3 · outbound

This paper cites Efficient- fedrec: Efficient federated learning framework for privacy- preserving news recommendation,.

A Survey on LLM-based News Recommender Systems Efficient- fedrec: Efficient federated learning framework for privacy- preserving news recommendation,

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.534016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.604718Z digest=sha256:b1a82ab17a32c51b7d4e13daf6dfa22aff5f4ecd368d021913a4c1a46be4503c

Observation 5aac8fb3-4fe7-466e-a4ce-71f02f8fd0e0 · outbound

This paper cites User modeling with click preference and reading satisfaction for news recommendation.

A Survey on LLM-based News Recommender Systems User modeling with click preference and reading satisfaction for news recommendation

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.519807Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.610124Z digest=sha256:ae3a188bb189a5e86512ac8271cc04ae504babd445745dcb44fb0c7e77c67606

Observation d9fae255-8586-4883-b55a-7d521204ccc0 · outbound

This paper cites Personal or general? a hybrid strategy with multi-factors for news recommendation,.

A Survey on LLM-based News Recommender Systems Personal or general? a hybrid strategy with multi-factors for news recommendation,

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.504864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.615286Z digest=sha256:70f161fb9de811efd1f7ba9127c3342491507129cab1c07c6c1c7479ecae91bd

Observation 26aa8076-2210-4730-b773-0013cbf8e340 · outbound

This paper cites Train Once, Use Flexibly: A Modular Framework for Multi-Aspect Neural News Recommendation.

A Survey on LLM-based News Recommender Systems Train Once, Use Flexibly: A Modular Framework for Multi-Aspect Neural News Recommendation

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-07T20:29:26.619368Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:29:26.619368Z digest=sha256:553c835fc3738fdde243b7898a0228db265f8ec22e61ccfece1e4366be01d49d

Observation ab828e86-8e5f-455e-91e5-9598329b901d · outbound

This paper cites NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation.

A Survey on LLM-based News Recommender Systems NewsRecLib: A PyTorch-Lightning Library for Neural News Recommendation

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-07T20:29:26.624942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:29:26.624942Z digest=sha256:5de26ce44c088993240c32b522b84c0fd1312263b77dcc8f4ff1d71514c73095

Observation 86b5c0f1-1fcf-4344-84bd-02859674d992 · outbound

This paper cites News Recommendation with Category Description by a Large Language Model.

A Survey on LLM-based News Recommender Systems News Recommendation with Category Description by a Large Language Model

Reference 72

Resolution
verified exact
local_arxiv, observed 2026-08-07T20:29:26.993646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.629279Z digest=sha256:bb100a5ede5350dd29fbc723ebf4c3306852f98707786320f32dbaa2f37d0662

Observation 291f4de6-55e6-4c43-a7b0-7eeb0ad3d3fe · outbound

This paper cites Once: Boost- ing content-based recommendation with both open-and closed- source large language models,.

A Survey on LLM-based News Recommender Systems Once: Boost- ing content-based recommendation with both open-and closed- source large language models,

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.489340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.635080Z digest=sha256:390e8e9737384ca032e2ee0694252f610022ae62865a9a9be65694b1710070af

Observation 55a09e83-61cf-493f-8a60-b941025fe8ed · outbound

This paper cites Modeling user viewing flow using large language models for article recommendation,.

A Survey on LLM-based News Recommender Systems Modeling user viewing flow using large language models for article recommendation,

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.474053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.639517Z digest=sha256:29dc605ec4b3783f7adbaac5b4dd10fc1ea903b26c5c5f69467889cc1a9dea76

Observation c22babab-6427-446c-83ba-e270d7a440ea · outbound

This paper cites Tiny-newsrec: Effective and efficient plm-based news recommendation,.

A Survey on LLM-based News Recommender Systems Tiny-newsrec: Effective and efficient plm-based news recommendation,

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.458784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.643980Z digest=sha256:d99791f7b6f57a1cd1ba581d402ca19bce6db68a1f91eeb6fbde883fab000050

Observation ce67bb9c-f6c6-4a47-bc70-618f7c7f7a54 · outbound

This paper cites Training large-scale news recommenders with pre- trained language models in the loop,.

A Survey on LLM-based News Recommender Systems Training large-scale news recommenders with pre- trained language models in the loop,

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.442876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.648203Z digest=sha256:f390d1c7943c0ed706b6894bffd5c5240b6404179949ae5cab58188ffee98911

Observation 8459209e-fefd-4d72-ab62-e4ba16d527ac · outbound

This paper cites RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models.

A Survey on LLM-based News Recommender Systems RecPrompt: A Self-tuning Prompting Framework for News Recommendation Using Large Language Models

Reference 77

Resolution
verified exact
local_arxiv, observed 2026-08-07T20:29:26.969989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.652333Z digest=sha256:78808513532567e62fbd41bc73e1d53a0625b6973a59def243cf0c7e060cb9a5

Observation 03da08e3-07b8-426a-85f1-1e01a4d7aee7 · outbound

This paper cites CherryRec: Enhancing News Recommendation Quality via LLM-driven Framework.

A Survey on LLM-based News Recommender Systems CherryRec: Enhancing News Recommendation Quality via LLM-driven Framework

Reference 78

Resolution
verified exact
local_arxiv, observed 2026-08-07T20:29:26.947946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.656653Z digest=sha256:df5958f6f688f1eff2b9eb93a07907eba425363e7b5c29da0b0e0f59892e2ba4

Observation 37bc6531-e9ff-4f41-a6ca-8a477937b4a3 · outbound

This paper cites Streamingrec: a framework for benchmarking stream-based news recom- menders,.

A Survey on LLM-based News Recommender Systems Streamingrec: a framework for benchmarking stream-based news recom- menders,

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.429075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.660938Z digest=sha256:d2b63f9cbd78b0971b6e54198a9b505fe8515c05d3005cc58b31a08e0ba1e417

Observation 9dde4158-8218-449a-b976-014cd85f1b2f · outbound

This paper cites Accurate news recommen- dation coalescing personal and global temporal preferences,.

A Survey on LLM-based News Recommender Systems Accurate news recommen- dation coalescing personal and global temporal preferences,

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.414186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.665186Z digest=sha256:d644eb0aac09dcc7ef6a740229c3494f14163ac389333eff5bf231f1490f5b8d

Observation dc9687d2-5a9e-4da1-8f17-b9519b79f671 · outbound

This paper cites Dynamic hierarchical attention network for news recommendation,.

A Survey on LLM-based News Recommender Systems Dynamic hierarchical attention network for news recommendation,

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.400007Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.669568Z digest=sha256:a62779864438dc917e3fce5974c0fe521afb7cfbfed91f48318214abf712d29a

Observation 9f1d4520-921b-4dae-abda-089e4ccbcf83 · outbound

This paper cites Fair multi- stakeholder news recommender system with hypergraph rank- ing,.

A Survey on LLM-based News Recommender Systems Fair multi- stakeholder news recommender system with hypergraph rank- ing,

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.385058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.674701Z digest=sha256:047f519a297c8e34126affbce29c7fae6367a8b2676ce5ec4effcf36cb52dc4d

Observation a3698280-deae-43e7-b481-77a5b41e2147 · outbound

This paper cites Lancer: A lifetime- aware news recommender system,.

A Survey on LLM-based News Recommender Systems Lancer: A lifetime- aware news recommender system,

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.369328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.679790Z digest=sha256:1ec53fdcacf4a46dd43e652e80272bd05a8bebfa7061ca2bfd52e1cf6559c72b

Observation 67a2ff38-ac22-4f40-87bb-35eeab0a879d · outbound

This paper cites News session-based recommendations using deep neural net- works,.

A Survey on LLM-based News Recommender Systems News session-based recommendations using deep neural net- works,

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.353451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.684374Z digest=sha256:65d630e511f5a5dec1dd508c51b62d2e70ddbacca97e11698181c55960dd56f6

Observation 13ebaef0-5f0c-4833-9929-f0a184d5c365 · outbound

This paper cites The plista dataset,.

A Survey on LLM-based News Recommender Systems The plista dataset,

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.337494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.688823Z digest=sha256:9a8633b0ca687f50a11a32bb9cbc08af046506cb831f7f6b136ed6ec0ad0a2a7

Observation 9e79dfac-e64d-4adb-9d60-29f09c682be5 · outbound

This paper cites The adressa dataset for news recommendation,.

A Survey on LLM-based News Recommender Systems The adressa dataset for news recommendation,

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.321629Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.693879Z digest=sha256:0cc95c8462eb61bac71c9690050cdb71455c8d2f2faa082faeb672342a38461f

Observation 8d8fbb25-c484-461c-82e7-329a40f628bd · outbound

This paper cites MIND: A large-scale dataset for news recommendation,.

A Survey on LLM-based News Recommender Systems MIND: A large-scale dataset for news recommendation,

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.305966Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.698441Z digest=sha256:276e078f9d93745bfe01d41433e262f513c7145f9a4d9b3407382d2979416288

Observation d5be0551-0199-4ced-8f3b-3055495feb9c · outbound

This paper cites Npr: a news portal recommendations dataset.

A Survey on LLM-based News Recommender Systems Npr: a news portal recommendations dataset

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.290897Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.703556Z digest=sha256:66a0d64dc9e50fe18566ba5f668fe0c183cdea1e41efb3521308ae29db5e6fa2

Observation 45ce6a58-93f6-4640-8f79-ad58ddced14f · outbound

This paper cites Mind your language: A multilingual dataset for cross-lingual news recommendation,.

A Survey on LLM-based News Recommender Systems Mind your language: A multilingual dataset for cross-lingual news recommendation,

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.274947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.708149Z digest=sha256:cf9a6b70ab3981ed877d372fa0bbafb2b76dd7cbf59ee308538823c132620da5

Observation a78a11ed-58ca-468b-bd8e-302a2f10aa62 · outbound

This paper cites Eb-nerd a large-scale dataset for news recommendation,.

A Survey on LLM-based News Recommender Systems Eb-nerd a large-scale dataset for news recommendation,

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.259830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.713761Z digest=sha256:4e10531c9f9eab27539b73de273938a977f09a5fcb433e14cf78d6fd5530a001

Observation 36588b22-e1fd-4da5-8e82-deac95ec104e · outbound

This paper cites Mm-rec: Visiolinguistic model empowered multimodal news recommendation,.

A Survey on LLM-based News Recommender Systems Mm-rec: Visiolinguistic model empowered multimodal news recommendation,

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.242344Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.718359Z digest=sha256:95cff0570b8c5c9e351e4d48b87254adf70ca3fd786c743c059fb86cb6abb764

Observation d10ca3e0-3602-403e-9338-9e32d2cd6b62 · outbound

This paper cites Legommenders: A Comprehensive Content-Based Recommendation Library with LLM Support.

A Survey on LLM-based News Recommender Systems Legommenders: A Comprehensive Content-Based Recommendation Library with LLM Support

Reference 92

Resolution
verified exact
local_arxiv, observed 2026-08-07T20:29:26.921358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.722850Z digest=sha256:e4b9d58729fec841504343aff31ccb71417022f3dbef3cdaefbdb1acafd7e469

Observation 84c98521-bb70-4f37-91e5-7d92f1cbe4e0 · outbound

This paper cites Microsoft recommenders: tools to accelerate developing recommender systems,.

A Survey on LLM-based News Recommender Systems Microsoft recommenders: tools to accelerate developing recommender systems,

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.226089Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.728467Z digest=sha256:4db7d9dd262cbb9daf6f2864a0750dad21f0f11832e3aef39cfdf492c37dd694

Observation 2a545e7b-355e-487d-a881-948acf6d5eab · outbound

This paper cites Recbole: Towards a unified, comprehensive and efficient framework for recommendation algorithms,.

A Survey on LLM-based News Recommender Systems Recbole: Towards a unified, comprehensive and efficient framework for recommendation algorithms,

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.210405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.732941Z digest=sha256:73fc80d59b85409cd81cc49fe18d90731dae405a7f5ccb37965b60f4e0787262

Observation e6f4b479-8fbd-497d-879d-03c70d04fc49 · outbound

This paper cites SPAR: Personalized Content-Based Recommendation via Long Engagement Attention.

A Survey on LLM-based News Recommender Systems SPAR: Personalized Content-Based Recommendation via Long Engagement Attention

Reference 95

Resolution
unresolved
no resolver link, observed 2026-08-07T20:29:26.739672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:29:26.739672Z digest=sha256:2f17554f862087f3aa3c5bc3f7e1298c0681c22c4f28a1bc4c211b91f7b27654

Observation d80e5c52-bff2-4571-93dd-00b47c6d84b2 · outbound

This paper cites Benchmarking news recommendation in the era of green ai,.

A Survey on LLM-based News Recommender Systems Benchmarking news recommendation in the era of green ai,

Reference 96

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.192251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.745206Z digest=sha256:08869a92db4ff6761fb968945bb173d573e08f59cb46c348a685a07c980b5e68

Observation 230ed797-253a-403a-8146-ad19ceffa7bb · outbound

This paper cites Discrete semantic tokenization for deep ctr prediction,.

A Survey on LLM-based News Recommender Systems Discrete semantic tokenization for deep ctr prediction,

Reference 97

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.176502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.750319Z digest=sha256:06941993cdd6728f75877c41a9f2dfad3d78c41007329aef0c5c1743a1b3509b

Observation d8d253a0-ffd2-4fe0-9c92-4ee2eb470fd1 · outbound

This paper cites HALoGEN: Fantastic LLM Hallucinations and Where to Find Them.

A Survey on LLM-based News Recommender Systems HALoGEN: Fantastic LLM Hallucinations and Where to Find Them

Reference 98

Resolution
unresolved
no resolver link, observed 2026-08-07T20:29:26.755143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:29:26.755143Z digest=sha256:420e5bdb2febc47416fc1353f77efcdaa71fbb1105211150a7353a14308ebadf

Observation f7a04871-65e2-453c-9f9d-ebabc865160d · outbound

This paper cites Enhancing LLM's Ability to Generate More Repository-Aware Unit Tests Through Precise Contextual Information Injection.

A Survey on LLM-based News Recommender Systems Enhancing LLM's Ability to Generate More Repository-Aware Unit Tests Through Precise Contextual Information Injection

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-07T20:29:26.759864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T20:29:26.759864Z digest=sha256:444ab7c9cade6e2095612dd480a5bf03fc33ab162ea9e811e9ab7729a3b4cc92

Observation 57efa484-77a5-43f3-8cd6-f5b2648a53d2 · outbound

This paper cites Prompt learning for news recom- mendation,.

A Survey on LLM-based News Recommender Systems Prompt learning for news recom- mendation,

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T20:29:27.160549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T20:29:26.764891Z digest=sha256:eb133922c5bfb717b9214151f048889f9c8d0c4a701c1506c6394bca9c5e6374

Pith citing papers

Observation 9379b521-e9fb-4782-8340-abf72b0a88b2 · inbound

Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation cites this paper.

Controlled Personalization in Legacy Media Online Services: A Case Study in News Recommendation A Survey on LLM-based News Recommender Systems

Reference 48

Resolution
verified exact
arxiv_id, observed 2026-05-25T08:10:31.414240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T08:08:23.728074Z digest=sha256:f40aa7cc7937b7f4ecf7100e612dabd5ac3c4f7cb2b2cf4ddba4b68081d7bba9

Observation c8ccf1ca-9df0-4ef9-9049-82322c2b1638 · inbound

Mind the Gap: Bridging Behavioral Silos with LLMs in Multi-Vertical Recommendations cites this paper.

Mind the Gap: Bridging Behavioral Silos with LLMs in Multi-Vertical Recommendations A Survey on LLM-based News Recommender Systems

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-07-02T16:07:08.456878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-27T23:04:03.682459Z digest=sha256:5b12450bef80faaadf88db455347e99a9858fcb51ec00eddb1a934002147e630