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Paper Citation Record · LEDGER

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

As of 7 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 2026-08-07T06:34:17.273281+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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.225348Z digest=sha256:301134fa5ebdb77e496a6ba948054eba5bbdf529710b563c98d53e327bf7150e

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

Resolution
verified fuzzy
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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.228724Z digest=sha256:9924633a60ebfdb50993ddbc9e2edc2867f6ee6746ca123b18fa9e82d7810925

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=sha256:34933cf78abb665d1d2203600347f2bdda038aa071380f17f29665a3bc531b19

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.234493Z digest=sha256:fabe18df2142b836d45408ca5a63dae5997675dafbe1db10b714b6a95803f7ee

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=sha256:93503ff3c10c7135de986331c40f41ce53b1e6ce4d2e725ff5623975dac2227b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.240629Z digest=sha256:cc6730681c46c33b02445c6e488e3ca42669d35d6d4401ee620c866665c7ccb3

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.243442Z digest=sha256:19acff83cc0187e7beff781b49ada4023c64f16b6358dc318cd49256a84cf309

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.245845Z digest=sha256:0ecbaf37ccc0c4490ee1ab1bc0f7cee0e963f651e320d3ff2bbe5ac1657fbdc5

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.248301Z digest=sha256:9c88b0d2fd11cdc7f9d78632d89148227ca07a4dc6548347af1282b60cdc273e

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.250829Z digest=sha256:75d3b57f9a69c49a7c528e366b77d17f14b473993051a0e9b98dc7ccc900108b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.253442Z digest=sha256:b750b7284e4366f4d88e3ef91caaf48b35d0fe2f501b5553454b202132c42cc2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.255880Z digest=sha256:45dd6fb219dd06447f55a14aecc6b6208025cad07a78cbb3c85c73b8a9c3fee4

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.258375Z digest=sha256:cdf57f2d7e9c02899e735688afe0dd5f4278cbe70daf8cd4ffea80f364487436

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.260880Z digest=sha256:e712fa421e2791c702b2bf4d96df3c035c4aadc96e40953ddb21a5bbedfef186

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.263332Z digest=sha256:b23ec829b1f5bf67e66c1362f5eb28b61e7cf0a0dd427bc3ee8614ac0097f2a4

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.265712Z digest=sha256:0e49ca1c2ce8b1fcda544cf9d7a33abfd336cdee39a4fa4b4a92e934a0df3325

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:bd74b9a53ebd3ee754564a9ae26d1b308c05853a24ada84d46aec199e0cdf99c

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.271025Z digest=sha256:81465ed19d5434e0a0269011be7ed8c44999a90a6a72b8a21f3c52f43378bed6

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.273653Z digest=sha256:e462f4693fa6166dbaf98ea480df4383089fd4a73d003a370cabfcfa735dc782

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=sha256:5292dfafa68908360ead112931fe416d983a6f476091749bf7d79418ee576f6b

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.279597Z digest=sha256:41f38bfa36c56d5e33024d210f46ad4d9d58b37a16258a90fdfcf8512de17955

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.282063Z digest=sha256:9076a5c7f3d9f9245997517b2fc35e3b31be41ea5be5f6fb3d0d2974b50c89d9

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.284595Z digest=sha256:cacb116c24b24e7615d37547d303371cb70ad7415701fef94989a0559927c615

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.287111Z digest=sha256:409d3fe720823d6a4e085a1087cddc386e250982318a5d79039d0c36826417d2

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:f314ef2d37c04d2b9c6e0028215f8d9bf59fc20cba1edc8c7035ffab24fb606e

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=sha256:9cf09b8e36e76355e417769b11566d4725c2586030c3788cf59360224585e4ab

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.294871Z digest=sha256:be44038293d6361234d5aa092e0aaacb395085423e87d10c42c40f6f3f72d2f2

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.297394Z digest=sha256:fe1ebfe2c6e3a345482fbe3593f0feb891c00a13cba0518905517e78d1893d08

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.299976Z digest=sha256:75a962c19956c40cb4827831977470f399f0944f845c0ac0f8607bcd21159cbc

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 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-06T18:52:26.302395Z digest=sha256:c02fe457c2542e59f8647806b930c958ca7a7a21dfbcac28f6f9e7e327e51d97

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:e6cb9d46d963fa9dbf39a6a4d917e9ebfe1d3dab96937883958f8fc0907fa3f8

Pith citing papers

No inbound Pith citation observations are available.