ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning | Paper Citation Record

Observation 79217f48-cd23-46a1-9ce4-a70d8e4e5e7e · outbound

This paper cites Efficient top-n recommendation for very large scale binary rated datasets.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Efficient top-n recommendation for very large scale binary rated datasets

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.417599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 8b913c5d-9ef4-4022-b2fd-5080e81b794b · outbound

This paper cites Bi-level optimization for generative recommendation: Bridging tokenization and generation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Bi-level optimization for generative recommendation: Bridging tokenization and generation

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.420918Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7a77d43a-7b0a-4984-aff3-bbb62ae20f83 · outbound

This paper cites Spectral Networks and Locally Connected Networks on Graphs.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Spectral Networks and Locally Connected Networks on Graphs

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:09.818051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 88d7e449-3c73-42ce-a7b2-4ff38c7ef869 · outbound

This paper cites 2nd workshop on information heterogeneity and fusion in recommender systems (hetrec 2011).

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning 2nd workshop on information heterogeneity and fusion in recommender systems (hetrec 2011)

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.423580Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 10e591d3-9358-4418-a592-54751bdefa69 · outbound

This paper cites Cross-domain recom- mendation with behavioral importance perception.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Cross-domain recom- mendation with behavioral importance perception

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.443945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 699f5dba-6536-4c06-8896-5353ca702aee · outbound

This paper cites Blurring-sharpening process models for collaborative filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Blurring-sharpening process models for collaborative filtering

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.414526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 19491011-af6c-447c-b58a-e4cb6ec78944 · outbound

This paper cites An overview of bilevel optimization.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning An overview of bilevel optimization

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.436790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 623b4c2d-fc1b-427f-a023-3023faab42ab · outbound

This paper cites Indexing by latent semantic analysis.Journal of the American Society for Information Science, 41(6):391–407.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Indexing by latent semantic analysis.Journal of the American Society for Information Science, 41(6):391–407

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.316029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ff20228d-7dcf-47a7-92d5-4598163af243 · outbound

This paper cites Convolutional neural networks on graphs with fast localized spectral filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Convolutional neural networks on graphs with fast localized spectral filtering

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.348821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c9443cb7-e1f7-491d-a0ef-afd0d425105b · outbound

This paper cites Neural message passing for quantum chemistry.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Neural message passing for quantum chemistry

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.398328Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9189d00d-976d-4fe1-88fa-334f84c15026 · outbound

This paper cites On manipulating signals of user-item graph: A jacobi polynomial-based graph collaborative filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning On manipulating signals of user-item graph: A jacobi polynomial-based graph collaborative filtering

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.339706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fee62d36-b0e3-4ae4-a9fd-471f0a6a5a07 · outbound

This paper cites Lgmrec: Local and global graph learning for multimodal recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Lgmrec: Local and global graph learning for multimodal recommendation

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.295186Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a00c35ca-a02a-49c0-8aec-656b1d71dc7f · outbound

This paper cites Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Ups and downs: Modeling the visual evolution of fashion trends with one-class collaborative filtering

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.336508Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f8eead74-9822-4282-9590-fbf16ab39af0 · outbound

This paper cites Lightgcn: Simplifying and powering graph convolution network for recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Lightgcn: Simplifying and powering graph convolution network for recommendation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.426809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 51284cb6-085c-496f-8fa2-4717019cb0cf · outbound

This paper cites Collaborative filtering meets spectrum shift: Connecting user-item interaction with graph-structured side information.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Collaborative filtering meets spectrum shift: Connecting user-item interaction with graph-structured side information

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.439005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation c886e3db-4473-4283-b654-e67e8c4c7051 · outbound

This paper cites Spectral graph neural networks are incomplete on graphs with a simple spectrum.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Spectral graph neural networks are incomplete on graphs with a simple spectrum

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.446337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 84c9a621-4662-4b1d-bea1-4c06ed5d4ab1 · outbound

This paper cites Whiteningbert: An easy unsupervised sentence embedding approach.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Whiteningbert: An easy unsupervised sentence embedding approach

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.453617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7f49d0c0-b975-432e-a38e-2b71f97ccb2c · outbound

This paper cites Challenging low homophily in social recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Challenging low homophily in social recommendation

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.448440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 58113c27-da8b-4ba1-9037-62f26c946861 · outbound

This paper cites How does message passing improve collaborative filtering? InAdvances in Neural Information Processing Systems (NeurIPS), volume 37, pages 8760–8784.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning How does message passing improve collaborative filtering? InAdvances in Neural Information Processing Systems (NeurIPS), volume 37, pages 8760–8784

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.406134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 36343873-0bd9-441d-b49b-a027067460f4 · outbound

This paper cites Graph spectral filtering with chebyshev interpolation for recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Graph spectral filtering with chebyshev interpolation for recommendation

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.409097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 15891481-8cac-49d1-afc0-0c4a4573d738 · outbound

This paper cites Adam: A Method for Stochastic Optimization.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Adam: A Method for Stochastic Optimization

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-11T20:11:09.757625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a9a11feb-fa7b-461e-8ecb-135c976b4528 · outbound

This paper cites Semi-supervised classification with graph convolutional networks.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Semi-supervised classification with graph convolutional networks

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.391707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 47329465-0504-4edf-9441-dddd51fb9e62 · outbound

This paper cites Deeper insights into graph convolutional networks for semi-supervised learning.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Deeper insights into graph convolutional networks for semi-supervised learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.394357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f99ef570-eea5-45fa-8824-f94b1dab5cc3 · outbound

This paper cites Gume: Graphs and user modalities enhancement for long-tail multimodal recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Gume: Graphs and user modalities enhancement for long-tail multimodal recommendation

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.399718Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e9a0c271-03fb-488e-8b3f-2ac88038df9e · outbound

This paper cites Improving graph collaborative filtering with neighborhood-enriched contrastive learning.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Improving graph collaborative filtering with neighborhood-enriched contrastive learning

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.402665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 266c479b-9f2f-4da0-acd4-be81d532d443 · outbound

This paper cites Interest-aware message-passing gcn for recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Interest-aware message-passing gcn for recommendation

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.383549Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 14e00f3b-9753-425f-af40-a0039c9d5d47 · outbound

This paper cites How do graph signals affect recommendation: Unveiling the mystery of low and high-frequency graph signals.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning How do graph signals affect recommendation: Unveiling the mystery of low and high-frequency graph signals

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:09.789409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6d9a4a3a-8aab-42ae-8bb1-1ffe42e9715f · outbound

This paper cites Personalized graph signal processing for collaborative filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Personalized graph signal processing for collaborative filtering

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.377498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3a43c1c4-6b54-4bcd-a310-d16434af22fd · outbound

This paper cites Revisiting graph contrastive learning from the perspective of graph spectrum.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Revisiting graph contrastive learning from the perspective of graph spectrum

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.386425Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f281a229-09d3-43c3-8341-acd2d3b4ed7a · outbound

This paper cites Optimizing millions of hyperparameters by implicit differentiation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Optimizing millions of hyperparameters by implicit differentiation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.389058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 495789f4-859f-452a-a080-a4f09b883188 · outbound

This paper cites Spectral-based graph neural networks for complementary item recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Spectral-based graph neural networks for complementary item recommendation

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.397100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 5b1fe1c6-cae0-4ca4-ac20-2150b47748dd · outbound

This paper cites Sfr-embedding-mistral: Enhance text retrieval with transfer learning.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Sfr-embedding-mistral: Enhance text retrieval with transfer learning

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.411806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 24430582-7c28-440a-b8b5-d8000bc8cd81 · outbound

This paper cites Auxiliary learning by implicit differentiation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Auxiliary learning by implicit differentiation

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.369860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 79218b59-83a1-435f-982a-4c9e877e0e9a · outbound

This paper cites Spectrum-based modality representation fusion graph convolutional network for multimodal recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Spectrum-based modality representation fusion graph convolutional network for multimodal recommendation

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.363970Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fbb5292f-c0cc-4ce1-a6b5-f56bb75333b3 · outbound

This paper cites Svd-gcn: A simplified graph convolution paradigm for recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Svd-gcn: A simplified graph convolution paradigm for recommendation

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.357978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e07be6c0-27cc-4fa6-a246-982a56d70eee · outbound

This paper cites How powerful is graph filtering for recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning How powerful is graph filtering for recommendation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.354998Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b0866c98-908a-447f-8f53-d70be71e8aa9 · outbound

This paper cites Polycf: Towards optimal spectral graph filters for collaborative filtering.ACM Transactions on Information Systems, 43(4):1–28.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Polycf: Towards optimal spectral graph filters for collaborative filtering.ACM Transactions on Information Systems, 43(4):1–28

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.360945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fde51961-9f50-4861-b231-686950542c67 · outbound

This paper cites Qwen2.5: A party of foundation models, September 2024.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Qwen2.5: A party of foundation models, September 2024

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.366810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b8a7e447-9159-48a7-88f4-fee4838f0873 · outbound

This paper cites GSPRec: On Improving Item Representations in Graph Signal Processing for Collaborative Filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning GSPRec: On Improving Item Representations in Graph Signal Processing for Collaborative Filtering

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-07-22T03:21:56.692570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f1a02b40-b8e2-45cb-beb9-f333a072b99e · outbound

This paper cites Bpr: Bayesian personalized ranking from implicit feedback.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Bpr: Bayesian personalized ranking from implicit feedback

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.380737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3f1c0546-88d5-4e91-8a5f-38061c11415f · outbound

This paper cites A stochastic approximation method.The Annals of Mathematical Statistics, pages 400–407.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning A stochastic approximation method.The Annals of Mathematical Statistics, pages 400–407

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.450856Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0ec12cc0-3dd6-48db-bdcf-bbd9a66e74e6 · outbound

This paper cites How powerful is graph convolution for recommendation? InACM International Conference on Information and Knowledge Management (CIKM), pages 1619–1629.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning How powerful is graph convolution for recommendation? InACM International Conference on Information and Knowledge Management (CIKM), pages 1619–1629

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.346249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ca6111e5-c5bf-4e4f-a08a-c392b8ba918d · outbound

This paper cites Language representations can be what recommenders need: Findings and potentials.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Language representations can be what recommenders need: Findings and potentials

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.373683Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation cfb43b68-289e-4a81-9650-c2275f4cd748 · outbound

This paper cites What matters in llm-based feature extractor for recommender? a systematic analysis of prompts, models, and adaptation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning What matters in llm-based feature extractor for recommender? a systematic analysis of prompts, models, and adaptation

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:09.826968Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 7fcaddd4-4865-4323-8c04-cfa0c7d684a6 · outbound

This paper cites an unresolved cited work.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-05-26T15:27:57.393559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation aa427771-8732-422a-b1b5-df1967de804a · outbound

This paper cites Whitening Sentence Representations for Better Semantics and Faster Retrieval.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Whitening Sentence Representations for Better Semantics and Faster Retrieval

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:09.808474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 6fe6c3f2-2dd4-43b4-a6e1-1d557a036e06 · outbound

This paper cites an unresolved cited work.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Unresolved cited work

Reference 47

Resolution: unresolved; raw_fallback, observed 2026-05-26T15:27:57.327821Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bfeb01db-882f-4d1c-8fd2-9367d739c10c · outbound

This paper cites Towards representation alignment and uniformity in collaborative filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Towards representation alignment and uniformity in collaborative filtering

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.320798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bfe1b478-42c7-4498-8826-5235787f8e83 · outbound

This paper cites Denoised self-augmented learning for social recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Denoised self-augmented learning for social recommendation

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.323173Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a6a130d9-3fe3-4bb7-9cef-d6edcfa20f32 · outbound

This paper cites Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Minilm: Deep self-attention distillation for task-agnostic compression of pre-trained transformers

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.325739Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2db81edb-1c09-4529-8bd7-bfad2d33d8d6 · outbound

This paper cites Neural graph collabo- rative filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Neural graph collabo- rative filtering

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.330122Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation bb4f50ff-56a1-42cc-8e36-a31c4fdebdec · outbound

This paper cites Disentangled graph collaborative filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Disentangled graph collaborative filtering

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.345810Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f93bdea2-8749-48e2-a8f8-2e0fc600d20e · outbound

This paper cites How powerful are spectral graph neural networks.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning How powerful are spectral graph neural networks

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.317823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 580b2ffb-6968-491c-bcf4-0beeff401a32 · outbound

This paper cites Efficient bi-level optimization for recommendation denoising.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Efficient bi-level optimization for recommendation denoising

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.304610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 2bd3d721-3b37-4928-9c0b-1cb138fcda0f · outbound

This paper cites Bi-nas: Towards effective and personalized explanation for recommender systems via bi-level neural architecture search.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Bi-nas: Towards effective and personalized explanation for recommender systems via bi-level neural architecture search

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.313291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation ba6cff8f-3c15-41db-a067-0925ff4e684f · outbound

This paper cites Afdgcf: Adaptive feature de-correlation graph collaborative filtering for recommendations.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Afdgcf: Adaptive feature de-correlation graph collaborative filtering for recommendations

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.315490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1d42b9b1-4ff6-449d-a18e-92fd8b52d075 · outbound

This paper cites Bilevel optimization with lower- level uniform convexity: Theory and algorithm.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Bilevel optimization with lower- level uniform convexity: Theory and algorithm

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.348633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a0240193-1ce2-4c92-86ac-c85840d7d4ef · outbound

This paper cites Stablegcn: Decoupling and reconciling information propagation for collaborative filtering.IEEE Transactions on Knowledge and Data Engineering (TKDE), 36(6):2659–2670.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Stablegcn: Decoupling and reconciling information propagation for collaborative filtering.IEEE Transactions on Knowledge and Data Engineering (TKDE), 36(6):2659–2670

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.292705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e1f02fb2-325f-4ff2-b62e-4daafb9cec9d · outbound

This paper cites Stair: Manipulating collaborative and multimodal information for e-commerce recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Stair: Manipulating collaborative and multimodal information for e-commerce recommendation

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.302223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation a7fb35c5-0c2d-4d24-a48b-5a9c3ff78e96 · outbound

This paper cites Dataset regeneration for sequential recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Dataset regeneration for sequential recommendation

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.285077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 00299f33-9cc3-4c35-a798-8d3cb9e85623 · outbound

This paper cites Mind individual information! principal graph learning for multimedia recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Mind individual information! principal graph learning for multimedia recommendation

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.287891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation fef8b688-0ae6-4cd6-b578-7bdba7098ffe · outbound

This paper cites BiFair: A Fairness-aware Training Framework for LLM-enhanced Recommender Systems via Bi-level Optimization.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning BiFair: A Fairness-aware Training Framework for LLM-enhanced Recommender Systems via Bi-level Optimization

Reference 62

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:09.743213Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 76713c4d-7e26-4d06-8d7f-2b7af563fafc · outbound

This paper cites Mining latent structures for multimedia recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Mining latent structures for multimedia recommendation

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.290394Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 912d328b-d9a5-4c80-aaf0-05cb9cd8b384 · outbound

This paper cites Dual-view whitening on pre-trained text embeddings for sequential recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Dual-view whitening on pre-trained text embeddings for sequential recommendation

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.297381Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 60be1e84-e802-43d8-8094-e32678c1979a · outbound

This paper cites Are id embeddings necessary? whitening pre-trained text embeddings for effective sequential recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Are id embeddings necessary? whitening pre-trained text embeddings for effective sequential recommendation

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.299774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f0e86dbc-6d04-4add-9c84-4d5d0471a99d · outbound

This paper cites Llminit: A free lunch from large language models for selective initialization of recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Llminit: A free lunch from large language models for selective initialization of recommendation

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.282615Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b9dd846c-9d80-4941-824e-3963cfd16259 · outbound

This paper cites Spectral collaborative filtering.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Spectral collaborative filtering

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.431883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 9eccf312-62c3-4e85-a88e-2e47955e57cb · outbound

This paper cites MMRec: Simplifying Multimodal Recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning MMRec: Simplifying Multimodal Recommendation

Reference 68

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:09.769115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 75bff4c2-f245-4475-a85f-5dbf3a3c6d99 · outbound

This paper cites A tale of two graphs: Freezing and denoising graph structures for multimodal recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning A tale of two graphs: Freezing and denoising graph structures for multimodal recommendation

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.441062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1baeba77-bc4a-4c93-933c-aa81dabd6b7e · outbound

This paper cites Bootstrap latent representations for multi-modal recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning Bootstrap latent representations for multi-modal recommendation

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.429816Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 42f17480-ce56-4a1f-85d4-7610eaf3584c · outbound

This paper cites CM$^3$: Calibrating Multimodal Recommendation.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning CM$^3$: Calibrating Multimodal Recommendation

Reference 71

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:11:09.834682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 1bb4554c-0f60-4e11-aa25-9bcf503724ef · outbound

This paper cites (1−p +)∇+ − MX m=1 p− m∇− m # =−E.

ASPIRE: Make Spectral Graph Collaborative Filtering Great Again via Adaptive Filter Learning (1−p +)∇+ − MX m=1 p− m∇− m # =−E

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-05-26T15:27:57.434324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers