Paper Citation Record · LEDGER

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation

As of 18 August 2026, this Paper Citation Record lists 70 of 70 outbound references and 1 inbound Pith citation observation for arXiv:2506.21579.

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

pith.paper-citation-record.v1
2506.21579 v1

Coverage vector

measured 70 of 70 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:05:22.902551Z

measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T20:37:17.317538Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T20:37:17.920031Z

Reference resolution

70 of 70 outbound references displayed

verified exact2
verified fuzzy1
unresolved67
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e184a21f-c601-403d-b2f2-7ac3bb7f0023 · outbound

This paper cites A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.595767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 35ec42de-3ed0-49e0-a123-19866ca820e1 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.601359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0154a9d2-35b0-4961-8bd2-5473cd39f33c · outbound

This paper cites LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation LLM2Vec: Large Language Models Are Secretly Powerful Text Encoders

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.610379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cc999af9-5787-435f-a1ee-7c0b89c280e2 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.853961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 839a7e97-761f-4a3b-aa6c-4f7590eb3e13 · outbound

This paper cites HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation HLLM: Enhancing Sequential Recommendations via Hierarchical Large Language Models for Item and User Modeling

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.620201Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2f393d3-b271-434d-bc19-19447d0239a6 · outbound

This paper cites On Softmax Direct Preference Optimization for Recommendation.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation On Softmax Direct Preference Optimization for Recommendation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.625006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 03ccdc3b-af9d-4cad-a51a-6b89120db797 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.630133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 56a0bc6b-f162-4a87-a75d-6c93c5c23848 · outbound

This paper cites SimCSE: Simple Contrastive Learning of Sentence Embeddings.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation SimCSE: Simple Contrastive Learning of Sentence Embeddings

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.634975Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 21e993b3-0220-4f53-b987-fb3e58d2baa4 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.639647Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fb005b2-95c9-451e-bbe6-0859b09b9e8c · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 10

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.823165Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation feb7e3ca-0ab6-4058-9a97-ff2d9cbb2de0 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.647980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fdc31c62-d46b-460e-892b-920da38bdd8e · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.800646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation df6805ed-e653-4794-aa48-6c7c1a2a40f1 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.655561Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d55946b-757a-4a52-81fa-aeab90dcfe50 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 14

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.779341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 09dd1c93-6519-4e56-9b9f-eba9d9466c16 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.669163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c2860c45-6b72-4292-a48e-18b881590674 · outbound

This paper cites Dense Passage Retrieval for Open-Domain Question Answering.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Dense Passage Retrieval for Open-Domain Question Answering

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.673492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0191b77-cbcf-4634-b2f2-7e8cca9218b1 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.678655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cb70e26-a57d-4dd0-8122-d456827bc04e · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.684096Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e2e818b4-9118-4309-bd23-18cbad22f47b · outbound

This paper cites Gecko: Versatile Text Embeddings Distilled from Large Language Models.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Gecko: Versatile Text Embeddings Distilled from Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.688875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c75796e2-202c-40b1-89e4-7ffccd8e74eb · outbound

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

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.693331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 150474d8-602e-4fbd-b719-52ffe09a664f · outbound

This paper cites Making Text Embedders Few-Shot Learners.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Making Text Embedders Few-Shot Learners

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.697755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 909e3ec5-f24a-4cea-937c-bd414c292dc5 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 22

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.746843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 66a25e9b-1049-4b93-98aa-287627322da9 · outbound

This paper cites Towards General Text Embeddings with Multi-stage Contrastive Learning.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Towards General Text Embeddings with Multi-stage Contrastive Learning

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.711542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6393063e-f6b4-45e0-b152-e792f9d163ff · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.733066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9d9b091a-ddbd-4227-836a-d6b144dc18b9 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.720672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61c5c129-f5f5-42da-956f-4405d644893a · outbound

This paper cites A Practice-Friendly LLM-Enhanced Paradigm with Preference Parsing for Sequential Recommendation.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation A Practice-Friendly LLM-Enhanced Paradigm with Preference Parsing for Sequential Recommendation

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.725027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 90a3466d-c7c9-46bb-8a12-702f524acb6a · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.709673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5569a433-b31c-404f-872b-a60b4ccbde8e · outbound

This paper cites LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation LLMEmb: Large Language Model Can Be a Good Embedding Generator for Sequential Recommendation

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.733539Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 025477ca-ae13-480a-894e-b41d83d96cff · outbound

This paper cites LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation LLM-ESR: Large Language Models Enhancement for Long-tailed Sequential Recommendation

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.737588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10bc2929-9a40-4790-a426-2fa24867dbb6 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.696909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bd8af3d1-8ac9-4ad0-8005-acf501e2a7ea · outbound

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

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.745380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f2d3a34-0ef1-460b-bdb6-431637c71059 · outbound

This paper cites Decoupled Weight Decay Regularization.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Decoupled Weight Decay Regularization

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.749495Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 55417690-3f9c-48e1-9706-65bbe77e3360 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 34

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.682228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 7736b3b5-28c1-4b19-951d-654a16101178 · outbound

This paper cites SGPT: GPT Sentence Embeddings for Semantic Search.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation SGPT: GPT Sentence Embeddings for Semantic Search

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.758107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 110582b7-f0d0-4d93-8375-c4fd95775877 · outbound

This paper cites Generative Representational Instruction Tuning.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Generative Representational Instruction Tuning

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.762675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f0f3e59-f6ba-4294-b082-31a518a2f3b9 · outbound

This paper cites MTEB: Massive Text Embedding Benchmark.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation MTEB: Massive Text Embedding Benchmark

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.767101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f601dbc2-c496-4877-ae36-9eb5e10f0f02 · outbound

This paper cites Large Dual Encoders Are Generalizable Retrievers.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Large Dual Encoders Are Generalizable Retrievers

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.771521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 824c50d4-c87f-4f4f-a367-64d4c25022ab · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.775923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation adf94b59-c2d7-4de1-86a3-5cfea1c4edaa · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 40

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.668038Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d606e977-5655-43f2-bdb1-5fde7aad1e89 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.785135Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8342c20a-9ac9-4d82-8ba8-a4fc43e657ab · outbound

This paper cites Repetition Improves Language Model Embeddings.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Repetition Improves Language Model Embeddings

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.794180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f73ced3d-2d3a-4ffa-83a4-f8473790a1ad · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.798747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6d79317-9ed0-4ba0-8b10-af9b1a35c156 · outbound

This paper cites Language Representations Can be What Recommenders Need: Findings and Potentials.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Language Representations Can be What Recommenders Need: Findings and Potentials

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.789464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7e724591-810c-4bae-b4fd-74f0bff5fae0 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.812056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47a5509c-6daa-4cea-bd1c-95c2d98a8291 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation LLaMA: Open and Efficient Foundation Language Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.816374Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d2069f4-2dc0-4d65-bf50-4e97e6a043b8 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.603130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c79785d0-5131-4bef-a757-5a29e49dfc8d · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.807931Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4a37d0d1-543d-4a0e-957a-6393fdd6bf5d · outbound

This paper cites Text Embeddings by Weakly-Supervised Contrastive Pre-training.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Text Embeddings by Weakly-Supervised Contrastive Pre-training

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.829922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 59816ab0-6bdb-4044-8fb8-c492e69120f7 · outbound

This paper cites Improving Text Embeddings with Large Language Models.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Improving Text Embeddings with Large Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.834291Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47d8bbde-fa6e-42b2-bf25-e59378e82f72 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.838622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c737eaf-7dca-4570-8f4b-54610e93a5cd · outbound

This paper cites Fine-Grained Spoiler Detection from Large-Scale Review Corpora.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Fine-Grained Spoiler Detection from Large-Scale Review Corpora

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-08-15T20:05:23.026374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d6d2566b-241e-4bb0-a63b-6493d5e600b7 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.846747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6cbaea54-23b4-4d35-9839-19b968beb7b9 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.850888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d362dda8-ea29-4dd7-a187-7f7eeea8898c · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.855665Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da9e1505-f72d-468e-8246-17e94027a7cf · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 56

Resolution: unresolved; raw_fallback, observed 2026-08-15T20:05:23.578238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation dfe2bb72-4d7b-47fa-a6d6-ad870cc5b1a8 · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.863077Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 500588c0-f1c9-4015-ad80-33aa7512e30f · outbound

This paper cites Qwen2 Technical Report.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Qwen2 Technical Report

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.866782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites an unresolved cited work.

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Reference 60

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This paper cites an unresolved cited work.

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Reference 61

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This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 62

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Reference 63

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Observation 257bc7d0-edd4-4f34-bf51-94335843e580 · outbound

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LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 64

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This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 65

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Reference 67

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Observation 8a74d1bd-b77b-4723-9400-6c5f48a6f8cf · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 69

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Observation aafff725-16e8-43be-9c1f-303acb15ca6e · outbound

This paper cites an unresolved cited work.

LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Unresolved cited work

Reference 2019

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LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Cross-Domain Recommendation: Challenges, Progress, and Prospects

Reference 2021

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Observation 8a55147f-abf4-486a-9ea6-87a90bd06240 · outbound

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LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation InRecSys

Reference 2023

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Observation 79182004-b224-40e4-921e-77829d70f3cb · outbound

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LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation Bridging Language and Items for Retrieval and Recommendation: Benchmarking LLMs as Semantic Encoders

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:22.659816Z

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Pith citing papers

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Beyond Semantic Understanding: Preserving Collaborative Frequency Components in LLM-based Recommendation cites this paper.

Beyond Semantic Understanding: Preserving Collaborative Frequency Components in LLM-based Recommendation LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation

Reference 15

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