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Paper Citation Record · LEDGER

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms

As of 22 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2507.07251.

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

pith.paper-citation-record.v1
2507.07251 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:52:26.305038Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

  • verified exact0
  • verified fuzzy22
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ce57ab52-536b-4d91-8a98-ea2b16955f77 · outbound

This paper cites https://anonymous.4open.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms https://anonymous.4open

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:28.673518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.225348Z digest=sha256:02c3c46011c3d062083b4d72cd08298039a56dad8899beb3203559d507a8835c

Observation b0423386-0b1d-4ded-8de4-dbd7fabdae23 · outbound

This paper cites https://www.fast.ai/.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms https://www.fast.ai/

Reference 2

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raw_fallback, observed 2026-08-06T18:52:28.516722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.228724Z digest=sha256:404dfd76713d37abdab9666e7c5443f1c4ffb96615b33463ad8921a999e99036

Observation e77787bd-9af3-4a78-89bb-5c2e177aac5e · outbound

This paper cites Phi-4 Technical Report.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Phi-4 Technical Report

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T18:52:26.231579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:52:26.231579Z digest=sha256:a641a1035296af163fee383f7daba8ba9854ab6edc423c546b7688af6e2a1855

Observation b0a3d270-beb8-4d1f-b64c-d6101da68257 · outbound

This paper cites Llm based generation of item-description for recommendation system.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Llm based generation of item-description for recommendation system

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:28.392289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.234493Z digest=sha256:f785ba0755a364e0525a31136ddc7412ab0a88a67f4bd42431b747ced449e66a

Observation 2885bbd3-368d-47e3-be05-463e2a5f1deb · outbound

This paper cites GPT-4 Technical Report.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms GPT-4 Technical Report

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T18:52:26.237601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:52:26.237601Z digest=sha256:0198ff2ac20a9ae1eab29f3a1773741837923cbfb262f46949d18891047adefb

Observation bbcb1e86-d89d-4973-a81e-4694cc58cd9a · outbound

This paper cites C., and Aggarwal, C.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms C., and Aggarwal, C

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:28.257769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.240629Z digest=sha256:6e3d5e22bceb6fea066d0068fc8ec51e2f1f6cbfd27e984099a1c441b29a4506

Observation 49d65f82-eed0-45b7-8602-b914a2ad7c2e · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:28.100779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.243442Z digest=sha256:418f0f12543aa5d362a913c735605baeefa9339391683a7562faab892052d63f

Observation bfcc62b0-2f0e-4975-83c9-2d7ff8595c6b · outbound

This paper cites Recommender system literature review 2019–2023.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Recommender system literature review 2019–2023

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:27.944738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.245845Z digest=sha256:55270a0605e00feb463eb151501f4cd50368d14bbe6d05664a035badd740bd53

Observation 61152c9a-1fd1-474c-9df3-42614d8b9139 · outbound

This paper cites Uncovering chatgpt’s capabilities in recommender systems.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Uncovering chatgpt’s capabilities in recommender systems

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:27.801519Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.248301Z digest=sha256:9f5d3c9051c1a09797262062b9417678015dd25d988a08f2648a63da928d0710

Observation 5de3b5b3-89fe-4e98-b51b-6105febaedeb · outbound

This paper cites M., and Konstan, J.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms M., and Konstan, J

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:27.669393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.250829Z digest=sha256:16e5e79c2c3682d0b711c0d0d88d92442633e8a2e4aa020d77925f700f41ff67

Observation 195c9537-1f26-444e-8c30-e96dc730c6b0 · outbound

This paper cites an unresolved cited work.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:52:27.564463Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.253442Z digest=sha256:ccda492e61abc82c6bfebdc8363b2c9c1b1e2ccfa41f0761c60bcbe7cf55b3ee

Observation 0b8da98e-39df-4132-b88e-07281765e4e9 · outbound

This paper cites Surprise: A python library for recommender systems.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Surprise: A python library for recommender systems

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:27.357282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.255880Z digest=sha256:cb021cf2dcb215efff51204df4c9f8886131a452ae7d3162a14c37945cee6f37

Observation ae95f5ac-3f8a-4cb0-a22c-2485a8ea8135 · outbound

This paper cites M., Bommarito, M.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms M., Bommarito, M

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:27.150536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.258375Z digest=sha256:72f48ba917aee24e46c600d7b91a5c788cd0aadb96758b2a6a7fd86c2cefbb49

Observation fc718ac8-9f76-4e6b-81d0-fc313f66b318 · outbound

This paper cites Factorization meets the neighborhood: a multifaceted collaborative filtering model.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Factorization meets the neighborhood: a multifaceted collaborative filtering model

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.950250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.260880Z digest=sha256:7c89c42b9b70915112d7883b7595fd526bd5e2fcc61c0bd01f908e32e1a8a398

Observation fd722b7a-521f-4ad6-9e54-1732fe14c8ab · outbound

This paper cites Matrix factorization techniques for recom- mender systems.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Matrix factorization techniques for recom- mender systems

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.825368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.263332Z digest=sha256:0c5eaa2a2b8e8e722acfc7f01c556f201106f9cefc4d2289e6035c478215351d

Observation 3c17e716-b4f8-4236-bc11-820d50ec39e4 · outbound

This paper cites M., Buchholz, A., and Schwöbel, P.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms M., Buchholz, A., and Schwöbel, P

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.669671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.265712Z digest=sha256:e84aba5de21d0c1ef498620a09a167c08e7eeb1403d3adf6470babc677c67bfe

Observation 3b75e176-16c6-4713-96f2-cb2e78c38d94 · outbound

This paper cites Is ChatGPT a Good Recommender? A Preliminary Study.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Is ChatGPT a Good Recommender? A Preliminary Study

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T18:52:26.268131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:52:26.268131Z digest=sha256:a9aaed463f94c2daac0ae5eef0bacb0a92d28ebacd6e3e9b7421b3db5d6a2b7c

Observation 25c44bee-6ed8-44d8-a755-15942e1d3b4d · outbound

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

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Once: Boosting content-based recommendation with both open-and closed-source large language models

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.628197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.271025Z digest=sha256:3a118fd7c6155ff977ed2cd9a2bed2e3f24ccbc1d572d3768b50ebfeae2de5e1

Observation c336f6ba-84fa-4752-9395-2e220b9ddcd6 · outbound

This paper cites Y., Morishetti, L., Giahi, R., Nag, K., Xu, J., Cho, J., Korpeoglu, E., Kumar, S., and Achan, K.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Y., Morishetti, L., Giahi, R., Nag, K., Xu, J., Cho, J., Korpeoglu, E., Kumar, S., and Achan, K

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.597094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.273653Z digest=sha256:be0f474442e1f5995c7e28f1d296921c6b0678ab34c24ba583ad5dbd8b76cfc1

Observation 66c79a88-f12b-47b8-bf6a-194981a100bb · outbound

This paper cites Capabilities of GPT-4 on Medical Challenge Problems.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Capabilities of GPT-4 on Medical Challenge Problems

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T18:52:26.276510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:52:26.276510Z digest=sha256:fd1c17b4061434117ab042b734e50a6f0e070b131ea5ab769261a84c30efd148

Observation a2db1c33-9a6c-4d75-9325-927405753308 · outbound

This paper cites Representation learning with large language models for recommendation.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Representation learning with large language models for recommendation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.566798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.279597Z digest=sha256:187c30f7cc1c908c3c00022bdbea75a4d1bf38d8323cde4a0750299862c7317e

Observation f9719393-67c7-4232-93f4-0640a16739aa · outbound

This paper cites an unresolved cited work.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-08-06T18:52:26.533447Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.282063Z digest=sha256:72b6ac3c9a829833d3f1c6bc41e786d4fd091c2608a8fd41ea1abb1b0eddfde7

Observation d9652373-7905-435f-af9e-9454b603b16d · outbound

This paper cites A systematic review and research perspective on recommender systems.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms A systematic review and research perspective on recommender systems

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.502046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.284595Z digest=sha256:7235e8370e5275220cc5e96aa458deba38569ec3bcae1e1404a728d43a69c591

Observation ce5f80c2-315a-4218-88c6-e1af673789e1 · outbound

This paper cites Large language models are competitive near cold-start recommenders for language-and item- based preferences.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Large language models are competitive near cold-start recommenders for language-and item- based preferences

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.471013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.287111Z digest=sha256:dd2929e52b4634531438581c3576672f11f856385a27cc74971d6b12693ed6bb

Observation 40ad0be8-bf17-4909-a923-7443566a9c9b · outbound

This paper cites Zero-Shot Next-Item Recommendation using Large Pretrained Language Models.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Zero-Shot Next-Item Recommendation using Large Pretrained Language Models

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-06T18:52:26.289460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:52:26.289460Z digest=sha256:662332db32cea23641f4d213970cb487c8e7c7fd3f3002579c58311a0399a2a7

Observation c384cd05-199e-45ed-b7f8-830af9528212 · outbound

This paper cites Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Rethinking the Evaluation for Conversational Recommendation in the Era of Large Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T18:52:26.292247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:52:26.292247Z digest=sha256:55a56b562d37945b7060301fbd3d1e35eb44f0af4bed1ebec7c3e4e5fcab3b8e

Observation a757e4b6-ff84-4e66-ad42-10b8793df3e6 · outbound

This paper cites Llmrec: Large language models with graph augmentation for rec- ommendation.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Llmrec: Large language models with graph augmentation for rec- ommendation

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.439645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.294871Z digest=sha256:9726c6cacf8d01e547965560b8c2e41139c92d7cba0fd2176044cb02c4f10de7

Observation 4c3248d5-d160-434f-88fb-74200aec70b1 · outbound

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

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Empowering news recommendation with pre-trained language models

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.406810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.297394Z digest=sha256:33bf97190ba79f143f0af59021f722d54fdbec2110cab41a791d5fe727f5b467

Observation 10e1e6e2-3a49-4f74-877a-16b6bbcdaffe · outbound

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

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms A survey on large language models for recommendation

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.385153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.299976Z digest=sha256:0358dd16d126072db2efa5f18ef504058dd06430408503e7578387d88a8d0bdc

Observation 9259499c-5aab-445c-bc45-4ca9c46bf735 · outbound

This paper cites Evaluating recommender systems: survey and framework.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms Evaluating recommender systems: survey and framework

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:52:26.371980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-06T18:52:26.302395Z digest=sha256:3dbc210aabbed457fc790cd25d1f5195824e73717e11f5e668e25643862c12f1

Observation f67fb30c-41b4-4192-a00c-f87b8b1da423 · outbound

This paper cites LLMTreeRec: Unleashing the Power of Large Language Models for Cold-Start Recommendations.

A Language-Driven Framework for Improving Personalized Recommendations: Merging LLMs with Traditional Algorithms LLMTreeRec: Unleashing the Power of Large Language Models for Cold-Start Recommendations

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T18:52:26.305038Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:52:26.305038Z digest=sha256:8245dc58c73af07f7a1da288eab97f6999a392ac577d675624319d10a3b1b51d

Pith citing papers

No inbound Pith citation observations are available.