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Paper Citation Record · LEDGER

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models

As of 21 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 3 inbound Pith citation observations for arXiv:2505.17051.

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

pith.paper-citation-record.v1
2505.17051 v1

Coverage vector

measured 62 of 62 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:02:03.287322Z

measured 65 of 65 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T00:27:41.609691Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

62 of 62 outbound references displayed

  • verified exact3
  • verified fuzzy25
  • unresolved33
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation d30b283d-b186-4fb3-98b2-dac9dbfcc71d · outbound

This paper cites Pens: A dataset and generic framework for personalized news headline generation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Pens: A dataset and generic framework for personalized news headline generation

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.308514Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.033266Z digest=sha256:f20197495926baa939ee123a394ee0450324f7c0710f47b58e818b238b79e587

Observation f5a0fde8-8d9c-41fd-b6a1-bf9aa0ef35ee · outbound

This paper cites Transparent, scrutable and explainable user models for personalized recommendation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Transparent, scrutable and explainable user models for personalized recommendation

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.292883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.037881Z digest=sha256:523617eb9f7a09ba51d1377fd9b2f9e30d6962266fbbb83bf1a3629ea826f38e

Observation c0502cf9-4f71-4eb9-93ef-29ec90b6542d · outbound

This paper cites Persona: A reproducible testbed for pluralistic alignment.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Persona: A reproducible testbed for pluralistic alignment

Reference 3

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verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.279373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.042784Z digest=sha256:6984127c347721cc7be12876643afaf75bb569232ca6f41aeb9b61d218d72499

Observation bf80ff4c-df58-457f-84d7-c9f88876dc72 · outbound

This paper cites MaxMin-RLHF: Alignment with Diverse Human Preferences.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models MaxMin-RLHF: Alignment with Diverse Human Preferences

Reference 4

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unresolved
no resolver link, observed 2026-08-15T21:02:03.047106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.047106Z digest=sha256:12bedb5fe3eb3736b1d1c0327720ad2d231c671638fed19606a52424406bd830

Observation 79939c40-b339-4f7c-a549-0936bb219024 · outbound

This paper cites Direct preference optimization with unobserved preference heterogeneity.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Direct preference optimization with unobserved preference heterogeneity

Reference 5

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unresolved
no resolver link, observed 2026-08-15T21:02:03.052149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.052149Z digest=sha256:f8fe8a90d4eb4cdbdeff0e7f923e43a79339cfdbe13639d6f7697668fe2a6354

Observation c197f690-c862-491b-8468-bda49aee6845 · outbound

This paper cites Personalized audiobook recommendations at spotify through graph neural networks.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Personalized audiobook recommendations at spotify through graph neural networks

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.266491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.057034Z digest=sha256:ebf91cc6f02e4653cb26ff3837df6ab4d09fb9609d9037b0e2b4b05ae8a1484b

Observation 889c1c5c-cf9e-40f5-a7ad-b188994a5af8 · outbound

This paper cites User Embedding Model for Personalized Language Prompting.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models User Embedding Model for Personalized Language Prompting

Reference 7

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no resolver link, observed 2026-08-15T21:02:03.061415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.061415Z digest=sha256:caae97e7d1bef0d9b08dcc85e3024d0d1e6bd77a9a9c48e3dd0b113b2bd56b7d

Observation b57cabce-07d8-4eee-b8c8-d469259fad96 · outbound

This paper cites KTO: Model Alignment as Prospect Theoretic Optimization.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models KTO: Model Alignment as Prospect Theoretic Optimization

Reference 8

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no resolver link, observed 2026-08-15T21:02:03.065643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.065643Z digest=sha256:b82f5dbc9afc192d7d523aa3f42fefa14f3943a35f02af58d1223e45bd9470e4

Observation 1349b55e-f109-4831-914d-7724764e4968 · outbound

This paper cites Stylept: Personalized neural text style transfer via prompt tuning.proceedings of the 37th aaai conference on artificial intelligence (aaai 2023), pages 9135–9143, 2023.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Stylept: Personalized neural text style transfer via prompt tuning.proceedings of the 37th aaai conference on artificial intelligence (aaai 2023), pages 9135–9143, 2023

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.254170Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.069865Z digest=sha256:51ac8aa49d5f2daa08c8312f20b0fb564d2b848767c4d6cb786acda400006348

Observation f515a9f9-f47c-4712-a496-d4fe33a4239b · outbound

This paper cites Generalized User Representations for Transfer Learning.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Generalized User Representations for Transfer Learning

Reference 10

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verified exact
local_arxiv, observed 2026-08-15T21:02:03.783408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.074272Z digest=sha256:a28f51316fd7dc7ea4ca2641bbb47f353258c242df6039eac5d28d324bbbae97

Observation 0b4cdffa-d9aa-4dbc-85aa-6ecf08918b79 · outbound

This paper cites In-context Autoencoder for Context Compression in a Large Language Model.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models In-context Autoencoder for Context Compression in a Large Language Model

Reference 11

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unresolved
no resolver link, observed 2026-08-15T21:02:03.079849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.079849Z digest=sha256:fa4b20cf2dcb80e5d1052874faa05abcebf5b7af981330c0de223cc8ac2afc91

Observation da52ba7f-3ea0-4e81-a321-82af256bbd3a · outbound

This paper cites The Llama 3 Herd of Models.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models The Llama 3 Herd of Models

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T21:02:03.085271Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.085271Z digest=sha256:f3c2cd357d91cf1f349535a783ceb868b93ca85fe3cd71e2f44dede47633954d

Observation 3b67b106-e4c8-404b-bc62-f37d24fa7c4d · outbound

This paper cites Transformer with memory as personalized gpt for dialogue agents.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Transformer with memory as personalized gpt for dialogue agents

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.242183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.089441Z digest=sha256:3801eeda940cda62f4ffe643006978323a9e5f55d9ce360985c1071019aaa0f7

Observation ac041ce8-9584-48ab-92aa-f3772b2bba17 · outbound

This paper cites Neural collaborative filtering.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Neural collaborative filtering

Reference 14

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unresolved
no resolver link, observed 2026-08-15T21:02:03.092651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.092651Z digest=sha256:7fe252c3d2f54f25089e78c86ea88f5c5707138766acf59ff430b4b34f16a6fc

Observation a178d35d-b820-4cb7-954a-bbd78aef3f43 · outbound

This paper cites PERSOMA: PERsonalized SOft ProMpt Adapter Architecture for Personalized Language Prompting.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models PERSOMA: PERsonalized SOft ProMpt Adapter Architecture for Personalized Language Prompting

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-15T21:02:03.096140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.096140Z digest=sha256:27798643a635b6af167c4b6398c338903b478afa3e92cac6ba21af6bf294cafa

Observation f37cdeeb-de29-4df8-8cc2-e6b0446417d0 · outbound

This paper cites Free energy analyses of cell-penetrating peptides using the weighted ensemble method.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Free energy analyses of cell-penetrating peptides using the weighted ensemble method

Reference 16

Resolution
metadata mismatch
local_arxiv, observed 2026-08-15T21:02:03.732224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.100310Z digest=sha256:aa5a062d2b6485678d98e17e9799440c8562a1084d03b9013444ca7844a1c9d6

Observation 1a11ee79-98c4-43c8-affc-e2ce6cbc1414 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Lora: Low-rank adaptation of large language models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-15T21:02:03.103879Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.103879Z digest=sha256:fed6658435a2025b52a7d3bb6d2a564eb10b39784e41db20f238af7ea6d96e8e

Observation 9eff7bf4-e7fd-454f-ad02-38e978e8f125 · outbound

This paper cites Lapdog: Learning retrieval augmentation for personalized dialogue generation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Lapdog: Learning retrieval augmentation for personalized dialogue generation

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.212337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.107097Z digest=sha256:9e8835f3f3b5ee51622e91f0b696afa25305f102a519fe0f193b509bc16cd454

Observation a57eb3a4-9875-43fc-8baa-aeb7657e2648 · outbound

This paper cites Aligning Language Models to User Opinions.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Aligning Language Models to User Opinions

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T21:02:03.110461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.110461Z digest=sha256:f0324684911af7d643ff19bad2e78292f96b26cd0b578ef1fa2e626a06755fa4

Observation 99647fb3-f4e3-4aa5-9b04-dc02c3addc5f · outbound

This paper cites Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Personalized Soups: Personalized Large Language Model Alignment via Post-hoc Parameter Merging

Reference 20

Resolution
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no resolver link, observed 2026-08-15T21:02:03.114543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.114543Z digest=sha256:69bc3e5c9eeaa86036541a839c64adb4aca1030aa7bb4271593e0470e6a3f5f2

Observation a707778c-d31b-4b91-adbc-56a137045812 · outbound

This paper cites Personalized language models via privacy- preserving evolutionary model merging.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Personalized language models via privacy- preserving evolutionary model merging

Reference 21

Resolution
verified exact
raw_fallback, observed 2026-08-15T21:02:03.681963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.118659Z digest=sha256:b4f38982dc0e55df4c88900bd7d04c5574e156852b0602b3b48efb6610e9797f

Observation d3fef1bc-544d-48e4-a445-b8fa79e4294f · outbound

This paper cites Adam: A Method for Stochastic Optimization.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Adam: A Method for Stochastic Optimization

Reference 22

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unresolved
no resolver link, observed 2026-08-15T21:02:03.122154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.122154Z digest=sha256:a8eb696394f82e7f6e076484bf6fe1e197bb05a1eb579b014ed08d426e0c2a19

Observation f9e7eee9-d520-4cef-b15c-ac5bdad06977 · outbound

This paper cites ComPO: Community Preferences for Language Model Personalization.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models ComPO: Community Preferences for Language Model Personalization

Reference 23

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no resolver link, observed 2026-08-15T21:02:03.125926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.125926Z digest=sha256:1946fb3bae7e032d9b75bf45115ffa2689a8bf1b913e585c36470df85a94f991

Observation 6fe9890a-a76e-45df-907b-211070058a32 · outbound

This paper cites P5: Plug-and-play persona prompting for personal- ized response selection.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models P5: Plug-and-play persona prompting for personal- ized response selection

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.198218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.129795Z digest=sha256:fd5373b10f03fac92c1c5fc6ec6af0647643c4b952cf87357dffa64514f58a62

Observation ff457614-973d-443d-9c9b-84560831f2f9 · outbound

This paper cites The power of scale for parameter-efficient prompt tuning.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models The power of scale for parameter-efficient prompt tuning

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.183782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.133612Z digest=sha256:ef15d1033384fe640075c118f29aafd6d65090cccad6600c3860c429005488a1

Observation 2335e8c1-fa4e-4dff-9fdc-dcc5e0d1fb30 · outbound

This paper cites Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Blip-2: Bootstrapping language-image pre-training with frozen image encoders and large language models

Reference 26

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unresolved
no resolver link, observed 2026-08-15T21:02:03.137492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.137492Z digest=sha256:774bd5e3be1ce7a569c8b4200dd31ff7cf8c5b73977c1f2a0b67fd225bd2b478

Observation ad4aaaa5-6a1f-4249-93b2-689bed80cdcf · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 27

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unresolved
no resolver link, observed 2026-08-15T21:02:03.141168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.141168Z digest=sha256:05f3e7820492122454f0e3c2d9a14f9f68200fd1231b44406c17d158932924ec

Observation 47d7bfc9-e4e0-437f-9c02-f7b2eb2937e0 · outbound

This paper cites Personalized item embeddings in federated multimodal recommendation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Personalized item embeddings in federated multimodal recommendation

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.157121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.145345Z digest=sha256:6efc10e9961073a6f186aa369750fe75f5e71b3d8803251197c4a50843efd117

Observation 3b9af0df-5e59-4c45-adc1-47869ef2b785 · outbound

This paper cites 500xCompressor: Generalized Prompt Compression for Large Language Models.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models 500xCompressor: Generalized Prompt Compression for Large Language Models

Reference 29

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unresolved
no resolver link, observed 2026-08-15T21:02:03.149453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.149453Z digest=sha256:8767ac8c137f458ced2e1889874d1c8edeb4d072164b60d7a47d96485120c464

Observation b988c9ea-74ef-4884-88d3-88c79604a219 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Rouge: A package for automatic evaluation of summaries

Reference 30

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unresolved
no resolver link, observed 2026-08-15T21:02:03.153088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.153088Z digest=sha256:d69ecabe2fd80f111abdf0e5c585d4f3e6b4de676d9e3ddd2cf4026a6fa9730e

Observation b16d1249-156e-4dd5-924a-a3076b1a3c1c · outbound

This paper cites Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Visual instruction tuning.Advances in neural information processing systems, 36:34892–34916, 2023

Reference 31

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no resolver link, observed 2026-08-15T21:02:03.156725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.156725Z digest=sha256:b486a831ef53268c14f4689625160d4b9173005c96071d40125feb2aff83b407

Observation 5eb5a081-3769-4c29-969c-149cb8697929 · outbound

This paper cites A survey of personalized large language models.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models A survey of personalized large language models

Reference 32

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no resolver link, observed 2026-08-15T21:02:03.160124Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:02:03.160124Z digest=sha256:51f279aa286050d2c4cfad01f00f45b07eef2b313cb67147b191c36a220401fd

Observation 3d54abe7-9366-43f8-a156-e078b7d1d785 · outbound

This paper cites Llms + persona-plug = personalized llms.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Llms + persona-plug = personalized llms

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.117387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.163981Z digest=sha256:e9c0f07f6f9d9d26169a0ec17ffac0ae301f4fcfdf2635f8fb7ea289afbaa88b

Observation 77c10429-9d24-4bce-bfa8-b9403f5c3a23 · outbound

This paper cites Xrec: Large language models for explainable recommendation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Xrec: Large language models for explainable recommendation

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.101781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.167987Z digest=sha256:436afaa4ce9ef998bdd9609d154719ffbffffc19a8535315ee00b593543ff256

Observation 67d545ab-bbbd-4ffb-9e08-34ed495e256e · outbound

This paper cites Personalizing dialogue agents via meta-learning.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Personalizing dialogue agents via meta-learning

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.086766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.172440Z digest=sha256:55529e507797c9fb027d93c03b179948954ab10eadcf9af86d5f3f19fe781fd7

Observation a6309277-3922-4564-a86f-cd9058059c7a · outbound

This paper cites Personalized paraphrasing: Controlling the formality and style of text.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Personalized paraphrasing: Controlling the formality and style of text

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.177473Z digest=sha256:885677651ace8276eca2cea4bac67bfc2a5ca72eab50363b7f13883990494ea1

Observation 099005e2-2fab-4a20-8684-eae094dd79f1 · outbound

This paper cites User-LLM: Efficient LLM Contextualization with User Embeddings.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models User-LLM: Efficient LLM Contextualization with User Embeddings

Reference 37

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source=pdf_text observed=2026-08-15T21:02:03.181524Z digest=sha256:a90b4bb60ac078b8502da551aec0687c11e82af24c7ff8f0c9e850e8bf3540f1

Observation ed391dc7-1436-476f-9902-3e31828b5d32 · outbound

This paper cites Recommender systems with generative retrieval.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Recommender systems with generative retrieval

Reference 38

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source=pdf_text observed=2026-08-15T21:02:03.186130Z digest=sha256:325836611d9356ae0964f821b9fe71bfa6d04d6f8578f8e73dd57d86ed237b1a

Observation 87027175-a6f3-4afb-bc11-295b2520c839 · outbound

This paper cites LaMP: When Large Language Models Meet Personalization.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models LaMP: When Large Language Models Meet Personalization

Reference 39

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source=pdf_text observed=2026-08-15T21:02:03.192832Z digest=sha256:8dcad458634957b684a86f24ac4875fd0a1dd83ae9ffbbeda99577c3f6e14efb

Observation 0248f60f-90f5-4721-aa67-0b51db24519b · outbound

This paper cites Whose opinions do language models reflect? In International Conference on Machine Learning, pages 29971–30004.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Whose opinions do language models reflect? In International Conference on Machine Learning, pages 29971–30004

Reference 40

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source=pdf_text observed=2026-08-15T21:02:03.197165Z digest=sha256:8f13a4744068f32d2efbe133888ddc68fe77c623891ec7133a29019a58a347d1

Observation 49da6413-21c2-4efa-906c-0995830cdede · outbound

This paper cites LMFusion: Adapting Pretrained Language Models for Multimodal Generation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models LMFusion: Adapting Pretrained Language Models for Multimodal Generation

Reference 41

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source=pdf_text observed=2026-08-15T21:02:03.202470Z digest=sha256:794e16915308cd0723aeb6d3fe8890c6a9f3aa46535246d738b95595d7f47db5

Observation 7c0acf2c-dcbd-460a-91eb-0e9a563efdf6 · outbound

This paper cites Better generalization with semantic ids: A case study in ranking for recommendations.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Better generalization with semantic ids: A case study in ranking for recommendations

Reference 42

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source=pdf_text observed=2026-08-15T21:02:03.206801Z digest=sha256:eeea8923ec114d6bd4f2ae537dbab3e25bc5da5106ee510903fc9e46fed46106

Observation f680662e-dadc-447d-8c38-57df903d95a7 · outbound

This paper cites A multi-stage approach for persona-aware response generation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models A multi-stage approach for persona-aware response generation

Reference 43

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verified fuzzy
raw_fallback, observed 2026-08-15T21:02:04.031195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.210862Z digest=sha256:a10807c2345da8e505f17dc6f53cc8a985ecbb67452d220a81d52b3394bac1cb

Observation a1148751-83f8-4b19-9426-180228dbf14c · outbound

This paper cites Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement

Reference 44

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source=pdf_text observed=2026-08-15T21:02:03.215244Z digest=sha256:6171c88844058c84a002b14c026de199f0992b3fe12279b27c78775a69487c56

Observation ded11a61-f327-4a83-adfa-169ac0a560ad · outbound

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

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Democratizing Large Language Models via Personalized Parameter-Efficient Fine-tuning

Reference 45

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source=pdf_text observed=2026-08-15T21:02:03.220418Z digest=sha256:60da23c725a44a0a982753dd5ec61c6db555eb3a7e95beaa68d3cd2972a838f9

Observation 38c2f07d-5654-4ca4-b2b2-6794336f2176 · outbound

This paper cites Step-Back Profiling: Distilling User History for Personalized Scientific Writing.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Step-Back Profiling: Distilling User History for Personalized Scientific Writing

Reference 46

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source=pdf_text observed=2026-08-15T21:02:03.224700Z digest=sha256:ec8b882833412e5098791d71f55bc5cc358fb3fd0942c2e054c0a094f8f089c6

Observation 26667197-5793-4dfb-ab56-2724f60e4960 · outbound

This paper cites Demystifying Embedding Spaces using Large Language Models.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Demystifying Embedding Spaces using Large Language Models

Reference 47

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verified exact
local_arxiv, observed 2026-08-15T21:02:03.384384Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.228702Z digest=sha256:f7e43835418000f27ad308f05c330cd7f16abf43412e33b629bcab0b1097c873

Observation 2a4619c6-7ea4-408c-860c-f42bbb66f783 · outbound

This paper cites Modeling users’ personality for response generation in conversational agent.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Modeling users’ personality for response generation in conversational agent

Reference 48

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raw_fallback, observed 2026-08-15T21:02:04.019910Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.233183Z digest=sha256:8e81bd247e6a9cab08f74f72f9552dfa8f7fd40f0d9b2a6faeb0f44e05bf9e00

Observation ee5d7b11-8327-440b-b0b9-86903de610b1 · outbound

This paper cites Large Language Model as a Universal Clinical Multi-task Decoder.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Large Language Model as a Universal Clinical Multi-task Decoder

Reference 49

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source=pdf_text observed=2026-08-15T21:02:03.237117Z digest=sha256:1e456a30718655568d08d42d8de2fbf4f8e26de91bb4a42e83a1406e5ada1036

Observation 600be5a3-76c4-468a-b722-5628f6600c28 · outbound

This paper cites Building your own chatbot with customized persona.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Building your own chatbot with customized persona

Reference 50

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raw_fallback, observed 2026-08-15T21:02:04.008842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.241044Z digest=sha256:95d2d26685ea90629a34ec5a805a212c2d3a338b8833df02aa9b40de5a4e4737

Observation dc3fca91-03e0-4053-a022-d942f6633f09 · outbound

This paper cites Personalized LLM Response Generation with Parameterized Memory Injection.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Personalized LLM Response Generation with Parameterized Memory Injection

Reference 51

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source=pdf_text observed=2026-08-15T21:02:03.245063Z digest=sha256:b65eae037de404e044ff50e7d912c03e7d99766fe4c4155640fa3684de0f51fe

Observation c87d9e9e-ef99-4ff3-be46-ccc7970b6102 · outbound

This paper cites Llama-adapter: Efficient fine-tuning of large language models with zero-initialized attention.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Llama-adapter: Efficient fine-tuning of large language models with zero-initialized attention

Reference 52

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raw_fallback, observed 2026-08-15T21:02:03.997774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.250225Z digest=sha256:bb16bc59f24514db3ba318413cb8085a4222b45f4a21afa60f04f0f019cf268c

Observation e78bbb66-aeda-46d2-943f-695fa26f4027 · outbound

This paper cites an unresolved cited work.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Unresolved cited work

Reference 53

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.253952Z digest=sha256:d8d1534a30fa0f5f90133f421320954870d2079dfce7493459b86719e920108f

Observation 4cf98ec0-d32e-4d2d-85d9-cc52bba4de39 · outbound

This paper cites Personalize your llm: Fake it then align it.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Personalize your llm: Fake it then align it

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:02:03.974385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.257060Z digest=sha256:8e75816646e969608cc4380a1e0367d3b676099ca63b327736cc8c781ac683a4

Observation 9408749f-0049-476b-89f0-5919b8559098 · outbound

This paper cites Less is more: Learning to refine dialogue history for personalized dialogue generation.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Less is more: Learning to refine dialogue history for personalized dialogue generation

Reference 55

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verified fuzzy
raw_fallback, observed 2026-08-15T21:02:03.961912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.260118Z digest=sha256:5656f6fa89c5eddd98736527a584c7662d3ca8beb7f1ee9e537f553501702065

Observation 9e586c4c-69f5-4b48-afea-739f3fc6105c · outbound

This paper cites Useradapter: Few-shot user learning in sentiment analysis.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models Useradapter: Few-shot user learning in sentiment analysis

Reference 56

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raw_fallback, observed 2026-08-15T21:02:03.949057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.263007Z digest=sha256:e84a1ef14f69895cc5f8700f0e7210f765a4352e57054a76bd5a31b6826af3dd

Observation 45ea48c1-f977-4c1e-85e1-7099554962e9 · outbound

This paper cites DiffLM: Controllable Synthetic Data Generation via Diffusion Language Models.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models DiffLM: Controllable Synthetic Data Generation via Diffusion Language Models

Reference 57

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source=pdf_text observed=2026-08-15T21:02:03.265878Z digest=sha256:778e5093d117dc7e0b4e25692f4b84369068afb51d4b6967564d3db647e5a79c

Observation be414146-c8b6-40d3-8d37-2f54d6e33d1c · outbound

This paper cites HYDRA: Model Factorization Framework for Black-Box LLM Personalization.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models HYDRA: Model Factorization Framework for Black-Box LLM Personalization

Reference 58

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source=pdf_text observed=2026-08-15T21:02:03.269290Z digest=sha256:52c77030441dc270f28ac4d3f1201395931bf6c9347d23ae35eb6943112e5716

Observation f48898b3-da56-4a8c-8914-15e225b2d8c2 · outbound

This paper cites We start from the “cleaned” HuggingFace edition (version dated 2024-03-01, 122,499 dialogues).

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models We start from the “cleaned” HuggingFace edition (version dated 2024-03-01, 122,499 dialogues)

Reference 59

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raw_fallback, observed 2026-08-15T21:02:03.936013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.273478Z digest=sha256:bc4ce10fcea7664c01095f45f06932d420c4814f8dc051da79b02c4ebd1abf5e

Observation 01ef7b10-fd2e-4b85-9112-b97e0359afdb · outbound

This paper cites We use the official v7 TSV dump distributed on Kaggle and respect its train/valid/personalized_test partition.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models We use the official v7 TSV dump distributed on Kaggle and respect its train/valid/personalized_test partition

Reference 60

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raw_fallback, observed 2026-08-15T21:02:03.923820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.277643Z digest=sha256:97596e76a52e95ae45ebcde080bd64bc573131d7de5cf5d2da704a633c58052d

Observation 706608ab-65a1-4cec-8674-f9f40175b558 · outbound

This paper cites This internal dataset consists of 300,000 user queries and generated playlists.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models This internal dataset consists of 300,000 user queries and generated playlists

Reference 61

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raw_fallback, observed 2026-08-15T21:02:03.910471Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.282079Z digest=sha256:b341749d9a70ab05c2e507ed73a46c20be6560d1c717caaa5305d8410828bfb2

Observation ed9314f4-4ab8-46af-bed0-f3a6ec34cf98 · outbound

This paper cites AlekseyKorshuk/persona-chat.

Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models AlekseyKorshuk/persona-chat

Reference 62

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raw_fallback, observed 2026-08-15T21:02:03.897334Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-08-15T21:02:03.287322Z digest=sha256:124071b4b3838b6cf1ac17361fe9d7097f70557f041d2eaac04ed1b2c800ab41

Pith citing papers

Observation 76b80eaf-5f02-4175-b7f1-fcac5525174f · inbound

Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda cites this paper.

Cloud-native and Distributed Systems for Efficient and Scalable Large Language Models -- A Research Agenda Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models

Reference 149

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arxiv_id, observed 2026-05-10T06:31:30.812951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-10T06:27:23.580445Z digest=sha256:3819d70dd0fb62d979b3bdae03da29fa8ab7e26043965df5dee995f1a25a7888

Observation b4df45f5-88bd-43cf-995d-37e2667e516c · inbound

ClusterRAG: Cluster-Based Collaborative Filtering for Personalized Retrieval-Augmented Generation cites this paper.

ClusterRAG: Cluster-Based Collaborative Filtering for Personalized Retrieval-Augmented Generation Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models

Reference 71

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arxiv_id, observed 2026-05-21T01:03:52.938509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-05-21T01:01:46.760396Z digest=sha256:0755bbd5e2dcfe3d2c65e6a4b8d0ae21c999220833f745e798e310c981697134

Observation ead5af15-9a44-414f-b2a2-6f37fbcc63fd · inbound

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection cites this paper.

Retrieval-Augmented Personalization with Foundation Models for Wearable Stress Detection Embedding-to-Prefix: Parameter-Efficient Personalization for Pre-Trained Large Language Models

Reference 49

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arxiv_id, observed 2026-06-26T00:28:42.962440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-06-26T00:27:41.609691Z digest=sha256:a3b24104369ac8be5dbad1f9563efe9d4402b9bf504df26f851fc3ec5690e0fc