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Paper Citation Record · LEDGER

Can Large Language Models Understand Preferences in Personalized Recommendation?

As of 23 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 1 inbound Pith citation observation for arXiv:2501.13391.

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

pith.paper-citation-record.v1
2501.13391 v1

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:17:33.819265Z

measured 61 of 61 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:21:07.194530Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

60 of 60 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved59
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 203ff6f2-786e-42f3-8e96-0a110e5c7e14 · outbound

This paper cites Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion.

Can Large Language Models Understand Preferences in Personalized Recommendation? Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion

Reference 1

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no resolver link, observed 2026-08-10T16:17:33.488020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.488020Z digest=sha256:b7bbde334deb9da09fed88d5851738a2fb927300de52922f54876546e0567395

Observation 49c92a7f-98c8-4e00-b24a-2e358d81acec · outbound

This paper cites TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation.

Can Large Language Models Understand Preferences in Personalized Recommendation? TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation

Reference 2

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no resolver link, observed 2026-08-10T16:17:33.494619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.494619Z digest=sha256:2e737af8a74a16737025c5c45930e77f9759f12fa27d822898e78bfc0c979f8f

Observation 1f9c0aa7-3f53-4fae-a907-030ba013570e · outbound

This paper cites PALR: Personalization Aware LLMs for Recommendation.

Can Large Language Models Understand Preferences in Personalized Recommendation? PALR: Personalization Aware LLMs for Recommendation

Reference 3

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no resolver link, observed 2026-08-10T16:17:33.501265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.501265Z digest=sha256:ef463bea8e74c207b5f0435339fe5e5832ffe8331b3e2b6dc73dfd68efb27a7e

Observation 981c745c-208e-408b-aa19-f42b9b654ce0 · outbound

This paper cites Uncovering ChatGPT's Capabilities in Recommender Systems.

Can Large Language Models Understand Preferences in Personalized Recommendation? Uncovering ChatGPT's Capabilities in Recommender Systems

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-10T16:17:34.529562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.506329Z digest=sha256:73b2dd73ef17134af9f2a1377d2174bc718f595b3e41bc1210f700d088f8dbb5

Observation 4aa9d474-21bc-4e97-ac4e-ea51d9df152b · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 5

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raw_fallback, observed 2026-08-10T16:17:35.107909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.511491Z digest=sha256:16360de1baf2c1dc4984a1d631c49a08cc799524eb90afcd963d194e45ae609b

Observation 9a62ba69-46a7-4ffd-af5f-c3496165d93f · outbound

This paper cites Enhancing Job Recommendation through LLM-based Generative Adversarial Networks.

Can Large Language Models Understand Preferences in Personalized Recommendation? Enhancing Job Recommendation through LLM-based Generative Adversarial Networks

Reference 6

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no resolver link, observed 2026-08-10T16:17:33.517008Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.517008Z digest=sha256:16dcc90c698a8ee91860defe4ab8c75bb16223dfd752ff58658a5c8ff005997f

Observation dbe0ef30-d38f-43b3-9c4e-1dcb9001447b · outbound

This paper cites The Llama 3 Herd of Models.

Can Large Language Models Understand Preferences in Personalized Recommendation? The Llama 3 Herd of Models

Reference 7

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no resolver link, observed 2026-08-10T16:17:33.523055Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.523055Z digest=sha256:530ef090774edaa847f182b8ae7ef0213df6d044f88dc37e0a9d7b38a3a8efe4

Observation 22d0c493-3a98-4fac-9a30-e04a5608e95f · outbound

This paper cites Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System.

Can Large Language Models Understand Preferences in Personalized Recommendation? Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System

Reference 8

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no resolver link, observed 2026-08-10T16:17:33.528758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.528758Z digest=sha256:2b14bb2f38b1f36859b26eb51353d3268b2b8c741f7ecf6514f1d1f75002301f

Observation bb4de2b9-b66e-4254-abad-5cceb67f9090 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 9

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raw_fallback, observed 2026-08-10T16:17:35.086580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.533849Z digest=sha256:4dfb4eccf7ba795b84cde78a9895238d5cca4f04af8dd817e50445d5f8ce71f8

Observation f824d2b7-e9fb-4f89-9db8-4b920c19390b · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 10

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unresolved
raw_fallback, observed 2026-08-10T16:17:35.058440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.539118Z digest=sha256:9260932ca42002994853aba6a934ad2b4458f15e472d012b822cd3e91aab8223

Observation 1fb0af47-707c-4b5b-9e87-645e2407770b · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 11

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raw_fallback, observed 2026-08-10T16:17:35.032075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.544047Z digest=sha256:a32c557975a0cf76886f885f99d122a4f97ff52b6a07aa6eda5789d4ea94158a

Observation bcc607dc-46a4-441c-86ab-d2bf69e60320 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 12

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unresolved
no resolver link, observed 2026-08-10T16:17:33.549208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.549208Z digest=sha256:0ff65b69498264472373c6e2a0a8ae8cef49ce5733e5acf8027edf003ddbdddd

Observation 8a90ad78-8828-4a24-a3d4-1acf419017b8 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 13

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no resolver link, observed 2026-08-10T16:17:33.554442Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.554442Z digest=sha256:ba37e102e058ead6973bfe3d3668879788360dda5df5b85e3c8411846bdade43

Observation 7761c466-389f-4d0a-b6d2-b2995f6eafc5 · outbound

This paper cites Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders.

Can Large Language Models Understand Preferences in Personalized Recommendation? Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders

Reference 14

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no resolver link, observed 2026-08-10T16:17:33.561537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.561537Z digest=sha256:eac0974fdd62c2258e097f897ee91557a99b81d612681a1eef170b4c205b4ef1

Observation 60622c94-8c75-4290-a824-1c2a60ea3193 · outbound

This paper cites Large Language Models are Zero-Shot Rankers for Recommender Systems.

Can Large Language Models Understand Preferences in Personalized Recommendation? Large Language Models are Zero-Shot Rankers for Recommender Systems

Reference 15

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unresolved
no resolver link, observed 2026-08-10T16:17:33.566575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.566575Z digest=sha256:914cc8bab6beac09e8ee0983e7f2fccfd7c34656d981c33a41d4f1c3bf5ef500

Observation 9a130a72-5611-4821-9d70-e412d8935e91 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 16

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no resolver link, observed 2026-08-10T16:17:33.572087Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.572087Z digest=sha256:5dcb936d3cd4154b5c89f6162df347a7e10bfe9f3029a9e32cba71c9056a854d

Observation b3402431-a2cf-4820-b850-7c72ec862a2e · outbound

This paper cites GPT-4o System Card.

Can Large Language Models Understand Preferences in Personalized Recommendation? GPT-4o System Card

Reference 17

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unresolved
no resolver link, observed 2026-08-10T16:17:33.577905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.577905Z digest=sha256:2e8e5302399f3875b37d9bc1e674f1aa755bf08bd02b4ce2e0dafee15730aeab

Observation ad18e068-641f-4953-a886-6ad3b64944d5 · outbound

This paper cites a rvelin and Jaana Kek \.

Can Large Language Models Understand Preferences in Personalized Recommendation? a rvelin and Jaana Kek \

Reference 18

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no resolver link, observed 2026-08-10T16:17:33.583652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.583652Z digest=sha256:fff7ed7b4039d39c9ba1b22741e4354f4a5c2cdd89465f77402760ba691f810c

Observation de61f101-f2fe-4323-bc1a-5d8d6a7e5465 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 19

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unresolved
raw_fallback, observed 2026-08-10T16:17:34.908742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.588623Z digest=sha256:13bb360fcd5971ddb56c45bba030874bdc7269e6010f7492ef1e2e60d5061228

Observation 26479f65-c4a5-4e45-8b47-c66460fa694a · outbound

This paper cites Mixtral of Experts.

Can Large Language Models Understand Preferences in Personalized Recommendation? Mixtral of Experts

Reference 20

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no resolver link, observed 2026-08-10T16:17:33.593616Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.593616Z digest=sha256:1e407e07ac14b25fb9cb937896e76b950551dfba58603bbdc9e55f51c10d562f

Observation 2f5ece3a-5588-4c0e-b851-3c04180af632 · outbound

This paper cites Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction.

Can Large Language Models Understand Preferences in Personalized Recommendation? Do LLMs Understand User Preferences? Evaluating LLMs On User Rating Prediction

Reference 21

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no resolver link, observed 2026-08-10T16:17:33.598681Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.598681Z digest=sha256:ad7ef9b7311cf162089ee71f9c256a9108a6b2655ee5bcf334d58d958b7e5b47

Observation 2006dce1-195d-45f9-93ec-eff5c06972fe · outbound

This paper cites Scaling Laws for Neural Language Models.

Can Large Language Models Understand Preferences in Personalized Recommendation? Scaling Laws for Neural Language Models

Reference 22

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no resolver link, observed 2026-08-10T16:17:33.605022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.605022Z digest=sha256:fb8b1a057c8c8ed8d006f3e319a00a34d6e9449c8deff8ae122b8da20ce9e458

Observation 335943b7-9f6e-46ea-a39a-faec28fb0583 · outbound

This paper cites Gonzalez, Hao Zhang, and Ion Stoica.

Can Large Language Models Understand Preferences in Personalized Recommendation? Gonzalez, Hao Zhang, and Ion Stoica

Reference 23

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no resolver link, observed 2026-08-10T16:17:33.611538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.611538Z digest=sha256:f789c23e3176bb43709127dd983155e006a77f0e4fe21bc6ead34447c2329210

Observation 62bf22f2-1fbb-4347-848e-e855fc8ca928 · outbound

This paper cites Personalized Language Modeling from Personalized Human Feedback.

Can Large Language Models Understand Preferences in Personalized Recommendation? Personalized Language Modeling from Personalized Human Feedback

Reference 24

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no resolver link, observed 2026-08-10T16:17:33.617159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.617159Z digest=sha256:7ccf66dc075e2963f96a62f1d7127e323cf0d6a0367b2b878f080e23c3fb3fcc

Observation 2c7e6ccd-4b61-40ba-a0dc-12f0e0b1ae21 · outbound

This paper cites DeepSeek-V3 Technical Report.

Can Large Language Models Understand Preferences in Personalized Recommendation? DeepSeek-V3 Technical Report

Reference 25

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no resolver link, observed 2026-08-10T16:17:33.624581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.624581Z digest=sha256:bb14b4160c3af34a3289ed1a8d9697be35fb3a93a33584d240a6ccd6ae00a25f

Observation 9c9120e5-9cf8-442f-b561-0e83a97bb372 · outbound

This paper cites Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens.

Can Large Language Models Understand Preferences in Personalized Recommendation? Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 26

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no resolver link, observed 2026-08-10T16:17:33.631642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.631642Z digest=sha256:6fc613021c0605b2d344b991ca69d3d768bab8fa44a1b67876884ba852cf7d35

Observation 24af0f59-ac29-4eac-8bde-17fb264cdc46 · outbound

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

Can Large Language Models Understand Preferences in Personalized Recommendation? Is ChatGPT a Good Recommender? A Preliminary Study

Reference 27

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no resolver link, observed 2026-08-10T16:17:33.637007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.637007Z digest=sha256:80f94d9d784bb7edc055d90e49c374a99bd8f333bb6cf5326357634354b1ff60

Observation 749a5ec1-a755-4d5b-a401-a5d24a219cfc · outbound

This paper cites ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models.

Can Large Language Models Understand Preferences in Personalized Recommendation? ONCE: Boosting Content-based Recommendation with Both Open- and Closed-source Large Language Models

Reference 28

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no resolver link, observed 2026-08-10T16:17:33.641770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.641770Z digest=sha256:b67ea8e813a4c8ddc8b3d462ee079978b6cce10c7cfd9ddb3d172c3fa074aae5

Observation 5a732318-813a-4544-8ff5-a52a526637e2 · outbound

This paper cites Are Emergent Abilities in Large Language Models just In-Context Learning?.

Can Large Language Models Understand Preferences in Personalized Recommendation? Are Emergent Abilities in Large Language Models just In-Context Learning?

Reference 29

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no resolver link, observed 2026-08-10T16:17:33.646835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.646835Z digest=sha256:d0ddb90f587106bc795066d51ce73764a886a16cbd1033e728ec2e8ace766c12

Observation 7e700c7e-7563-4856-a3eb-308512de2516 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 30

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no resolver link, observed 2026-08-10T16:17:33.652006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.652006Z digest=sha256:db6f3673c1efe65d27eb4afaf0e30093dee17ad07671e8147679096ca93df3ac

Observation 3aa7f51e-a82c-42c4-bc3e-a6a2c17f49ca · outbound

This paper cites Zero-Shot Listwise Document Reranking with a Large Language Model.

Can Large Language Models Understand Preferences in Personalized Recommendation? Zero-Shot Listwise Document Reranking with a Large Language Model

Reference 31

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no resolver link, observed 2026-08-10T16:17:33.658138Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.658138Z digest=sha256:aba863369ae4a4bcdd78317c0e9c8f55dc0dc0bab68e0b302e47ebaaadbac90f

Observation a57b3f00-5f53-4c8a-b4e1-1abc5acd9dd3 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 32

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unresolved
raw_fallback, observed 2026-08-10T16:17:34.845053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.664138Z digest=sha256:d740eb80531f1117e4eb026d7ad85863ceadc1f79dd050e3e08c949a41712b35

Observation 2a335503-65dd-4908-9c41-e29a7dd7ca61 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 33

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no resolver link, observed 2026-08-10T16:17:33.669629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.669629Z digest=sha256:4adf52c01ff4ae439dccd5a97930e6cdf3f4854d789fdb5c0b20d79c897a30de

Observation bed712e6-88d0-44e3-acb4-935f06b8a01b · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 34

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unresolved
raw_fallback, observed 2026-08-10T16:17:34.801231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.675400Z digest=sha256:811c28e50f059a0c3086fa8f3edda49727db61b05ed974848377987165aa1812

Observation 44999cb9-7758-489e-8c31-d4cd24637d5c · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 35

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raw_fallback, observed 2026-08-10T16:17:34.781759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.681088Z digest=sha256:986eea0cbc60e76f4d6db846e47b51433cf36fe34292e0f188dfcd1df28c862c

Observation 34f9518c-5312-4419-991a-34af5fb01b2c · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 36

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no resolver link, observed 2026-08-10T16:17:33.686144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.686144Z digest=sha256:94c5d88d35d44262d19937c66474cd32c2413cd8bf7dd29cff699456e0fb8dc5

Observation 1df70064-5697-4481-a4a7-3baca4dea71f · outbound

This paper cites Qwen2.5 Technical Report.

Can Large Language Models Understand Preferences in Personalized Recommendation? Qwen2.5 Technical Report

Reference 37

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unresolved
no resolver link, observed 2026-08-10T16:17:33.692478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.692478Z digest=sha256:6a9e42f6c2bbe3f73b43641fda293cd27e591e14e2d400b16b7c105c0e5a4926

Observation 6092f3fb-0b4e-46bc-9464-d74a4c770bdb · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 38

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unresolved
raw_fallback, observed 2026-08-10T16:17:34.762556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.697560Z digest=sha256:224e4ba83da447ce1706b87a10763584118f6cec4da9b77781f95605efd9803c

Observation eaaa5d0d-50c8-477e-aad2-e522abec2381 · outbound

This paper cites Integrating Summarization and Retrieval for Enhanced Personalization via Large Language Models.

Can Large Language Models Understand Preferences in Personalized Recommendation? Integrating Summarization and Retrieval for Enhanced Personalization via Large Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.703117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.703117Z digest=sha256:33f679a436ccda7eb2473fe390273c526f8321a570c70900203a9ce774885956

Observation 2b8f3de5-3665-49db-ad50-5c745c9a0690 · outbound

This paper cites Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.

Can Large Language Models Understand Preferences in Personalized Recommendation? Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.709325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.709325Z digest=sha256:ac7af28747066be7a39388e1c3d4e575093423ab8685818e2ab26a8cc9aa783c

Observation fc62c4f9-df41-4192-812e-3a769c1cfb28 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-10T16:17:34.742983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.714647Z digest=sha256:98432a0230ee8bbc733ee824ec4a9c20a613588f8ebec1e3195e4189f7acdead

Observation 170315a5-ea72-45d4-8142-1974b8d6a898 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-10T16:17:34.717731Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.723775Z digest=sha256:c5ef887c9e8d8ef2f7d407aac4dac0f742ce3eba71505c0b993aa0058d1af6b6

Observation 9439b5a8-b2f1-429b-bc45-c2f4a50feed9 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-10T16:17:34.699633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.729613Z digest=sha256:3541547f336c82dbf64f7d701e609170af728b8b6a3503608ef3310f7dee0cfd

Observation 662a1520-a88b-4d53-963f-539b4b2c3119 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.734724Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.734724Z digest=sha256:f0d64907141d6453ebbcd639c7961b4c746642ade370ac07c16ef7d3a7759c62

Observation 643dd8b2-3030-44fb-9fd9-35ec4bb1ca70 · outbound

This paper cites User Modeling in the Era of Large Language Models: Current Research and Future Directions.

Can Large Language Models Understand Preferences in Personalized Recommendation? User Modeling in the Era of Large Language Models: Current Research and Future Directions

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.739881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.739881Z digest=sha256:006d0649db9e0f8a768587bc984415d3d016fd178cf9bc7da685da489dbbf8f4

Observation b0ebb297-64ca-4951-bc58-c3e43ad88cb7 · outbound

This paper cites Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts.

Can Large Language Models Understand Preferences in Personalized Recommendation? Personalized Pieces: Efficient Personalized Large Language Models through Collaborative Efforts

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.745502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.745502Z digest=sha256:469ceeb84a305909192c4603b83719920061b45e95909efd4a01103701368e62

Observation 8c7c15b7-8f98-4c13-a872-0054fc998516 · outbound

This paper cites Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning.

Can Large Language Models Understand Preferences in Personalized Recommendation? Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.751561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.751561Z digest=sha256:255362b5d4d6d061691338f41934291e1c1463fdfc6b3d7e3dfa42276e2dc875

Observation ee24a763-d025-4a60-a6f1-8ca22424aa3c · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Can Large Language Models Understand Preferences in Personalized Recommendation? Gemma 2: Improving Open Language Models at a Practical Size

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.756494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.756494Z digest=sha256:85d95fb758854818fc985266f28828f42d15ed26795ac157e8de20a0b7eabe96

Observation 03fa2995-a2db-423b-a812-bd50693627c5 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.761135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.761135Z digest=sha256:db3e333d150a2e51e0470e942f598884ab60b96d04ba958a81d669c32b5bd01b

Observation 41d10818-db76-4d05-aee5-c1ae25336c84 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-10T16:17:34.665476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.765919Z digest=sha256:fc86cf52c92cb77a3b6a60dbc8805ce37e4553a965144a80b03017b5c9a1fcf2

Observation 3acf6c5f-5cb3-4972-a079-cbc146f36f8c · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-10T16:17:34.646548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-08-10T16:17:33.770481Z digest=sha256:9b0bf819c6d4a5938f081b4a33fd7cd06ec043f42a641f2950140c419b617940

Observation 9ab6e3b9-7e73-4ef0-a879-9ac827ed481e · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.775341Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.775341Z digest=sha256:29da95ed5149a713802bba2bbded7329f4d722bcfe6fc421358efe2cee1e1a16

Observation b965417b-af56-435a-920d-2d6977376525 · outbound

This paper cites Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models.

Can Large Language Models Understand Preferences in Personalized Recommendation? Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.780673Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.780673Z digest=sha256:37222d0f39b315e8317e78b7cd8d2f66a2a41ec59085e6e633e8bff65688bda9

Observation af6ebec0-142b-4cd8-a1e6-da66d7b9d55b · outbound

This paper cites Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge.

Can Large Language Models Understand Preferences in Personalized Recommendation? Justice or Prejudice? Quantifying Biases in LLM-as-a-Judge

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.786507Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.786507Z digest=sha256:87b9a71f38f51bb306168569f1c8c1ae5d4f5e67806c2e1cf1a8d562511de9c4

Observation a3c19e98-84da-40e5-9e8d-07fe8881d9f9 · outbound

This paper cites an unresolved cited work.

Can Large Language Models Understand Preferences in Personalized Recommendation? Unresolved cited work

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.792120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.792120Z digest=sha256:23cecc6ea4ac669ae39aa3713afa66e89687d47a4caaeb4079b25fc69c290da3

Observation 30e92eae-0f76-40fe-850f-000e7185666e · outbound

This paper cites Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach.

Can Large Language Models Understand Preferences in Personalized Recommendation? Recommendation as Instruction Following: A Large Language Model Empowered Recommendation Approach

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.797295Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.797295Z digest=sha256:79a7c990a1f2cef9fe2950927ed2e38d02773d4e91508f7a7469f23ce07c84cf

Observation 7d3d8cc7-58a3-4486-9c1a-73a2887349ba · outbound

This paper cites Personalization of Large Language Models: A Survey.

Can Large Language Models Understand Preferences in Personalized Recommendation? Personalization of Large Language Models: A Survey

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.803788Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.803788Z digest=sha256:3fabb829cff82a85cea88c7a006807c48f9bba4e6c869a16be437604578ca672

Observation 11686a0e-dc99-4748-9989-ec786c892b80 · outbound

This paper cites BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model.

Can Large Language Models Understand Preferences in Personalized Recommendation? BookGPT: A General Framework for Book Recommendation Empowered by Large Language Model

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.809022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.809022Z digest=sha256:291ec024a9e7cf7a73f40bb351f94af73f4f9fd6209066771d5c8d05e0992430

Observation d8db9a83-bda9-46f5-a427-d68fa6e5187d · outbound

This paper cites online" 'onlinestring :=.

Can Large Language Models Understand Preferences in Personalized Recommendation? online" 'onlinestring :=

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.814110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.814110Z digest=sha256:3459f7bf04e5f94c8225a3e87cbe01471150c1597998175f7b3c5d3d78f4e1f7

Observation 6334ab4b-aab7-41de-a467-c4ce116d9680 · outbound

This paper cites write newline.

Can Large Language Models Understand Preferences in Personalized Recommendation? write newline

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T16:17:33.819265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:17:33.819265Z digest=sha256:26766401193226b1ceebb92bb0bd29e1c2ba978cffd6567ccf47f911e2458f67

Pith citing papers

Observation 1b3bb75f-b5be-4b95-b87f-454ee71a668f · inbound

Instant Personalized Large Language Model Adaptation via Hypernetwork cites this paper.

Instant Personalized Large Language Model Adaptation via Hypernetwork Can Large Language Models Understand Preferences in Personalized Recommendation?

Reference 6475

Resolution
unresolved
no resolver link, observed 2026-08-04T09:21:07.194530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:21:07.194530Z digest=sha256:853611daa748543a7df9fb77340a459d0b84fec41c33f3d919018719a9152677