Collaborative Filtering

Benchmarks archive 2025-07-28

4 leaderboard tables shown for this task, 4 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

6 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Most implemented papers archive 2025-07-28

30 shown of 461 papers with code (1,309 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Neural Collaborative Filtering
  16 Aug 2017 43 repositories listed
  When it comes to model the key factor in collaborative filtering -- the interaction between user and item features, they still resorted to matrix factorization and applied an inner product on the latent features of…
• Neural Graph Collaborative Filtering
  20 May 2019 21 repositories listed Syntology ran 6 of 7 samples · 1 unverified
  Further analysis verifies the importance of embedding propagation for learning better user and item representations, justifying the rationality and effectiveness of NGCF.
• LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
  6 Feb 2020 18 repositories listed Syntology ran 2 of 7 samples · 5 unverified · 2 pointer-only (licence)
  We propose a new model named LightGCN, including only the most essential component in GCN -- neighborhood aggregation -- for collaborative filtering.
• Variational Autoencoders for Collaborative Filtering
  16 Feb 2018 18 repositories listed Syntology ran 2 of 21 samples · 19 unverified · 1 pointer-only (licence)
  This non-linear probabilistic model enables us to go beyond the limited modeling capacity of linear factor models which still largely dominate collaborative filtering research.
• Graph Convolutional Matrix Completion
  7 Jun 2017 17 repositories listed
  We consider matrix completion for recommender systems from the point of view of link prediction on graphs.
• Recurrent Neural Networks with Top-k Gains for Session-based Recommendations
  12 Jun 2017 12 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  RNNs have been shown to be excellent models for sequential data and in particular for data that is generated by users in an session-based manner.
• A Contextual-Bandit Approach to Personalized News Article Recommendation
  28 Feb 2010 12 repositories listed Syntology ran 1 of 3 samples · 2 unverified · 1 pointer-only (licence)
  In this work, we model personalized recommendation of news articles as a contextual bandit problem, a principled approach in which a learning algorithm sequentially selects articles to serve users based on contextual…
• Training Deep AutoEncoders for Collaborative Filtering
  5 Aug 2017 10 repositories listed
  Our model is based on deep autoencoder with 6 layers and is trained end-to-end without any layer-wise pre-training.
• Embarrassingly Shallow Autoencoders for Sparse Data
  8 May 2019 9 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  Combining simple elements from the literature, we define a linear model that is geared toward sparse data, in particular implicit feedback data for recommender systems.
• RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems
  9 Mar 2018 9 repositories listed Syntology ran 1 of 7 samples · 6 unverified · 1 pointer-only (licence)
  To address the sparsity and cold start problem of collaborative filtering, researchers usually make use of side information, such as social networks or item attributes, to improve recommendation performance.
• Knowledge Graph Convolutional Networks for Recommender Systems
  18 Mar 2019 8 repositories listed Syntology ran 1 of 5 samples · 4 unverified · 1 pointer-only (licence)
  To alleviate sparsity and cold start problem of collaborative filtering based recommender systems, researchers and engineers usually collect attributes of users and items, and design delicate algorithms to exploit these…
• Item2Vec: Neural Item Embedding for Collaborative Filtering
  14 Mar 2016 7 repositories listed
  Many Collaborative Filtering (CF) algorithms are item-based in the sense that they analyze item-item relations in order to produce item similarities.
• Mixed Dimension Embeddings with Application to Memory-Efficient Recommendation Systems
  25 Sep 2019 6 repositories listed Syntology ran 2 of 26 samples · 24 unverified · 26 pointer-only (licence)
  Embedding representations power machine intelligence in many applications, including recommendation systems, but they are space intensive -- potentially occupying hundreds of gigabytes in large-scale settings.
• Towards an Appropriate Query, Key, and Value Computation for Knowledge Tracing
  14 Feb 2020 5 repositories listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  To the best of our knowledge, this is the first work to suggest an encoder-decoder model for knowledge tracing that applies deep self-attentive layers to exercises and responses separately.
• Deep Reinforcement Learning based Recommendation with Explicit User-Item Interactions Modeling
  29 Oct 2018 5 repositories listed
  The DRR framework treats recommendation as a sequential decision making procedure and adopts an "Actor-Critic" reinforcement learning scheme to model the interactions between the users and recommender systems, which can…
• Learning Heterogeneous Knowledge Base Embeddings for Explainable Recommendation
  9 May 2018 5 repositories listed
  Specifically, we propose a knowledge-base representation learning framework to embed heterogeneous entities for recommendation, and based on the embedded knowledge base, a soft matching algorithm is proposed to generate…
• Collaborative Memory Network for Recommendation Systems
  29 Apr 2018 5 repositories listed
  We propose Collaborative Memory Networks (CMN), a deep architecture to unify the two classes of CF models capitalizing on the strengths of the global structure of latent factor model and local neighborhood-based…
• LECF: Recommendation via Learnable Edge Collaborative Filtering
  23 Dec 2021 4 repositories listed
  In this paper, we model an interaction between user and item as an edge and propose a novel CF framework, called learnable edge collaborative filtering (LECF).
• Neural Collaborative Filtering vs. Matrix Factorization Revisited
  19 May 2020 4 repositories listed
  This approach is often referred to as neural collaborative filtering (NCF).
• DiffNet++: A Neural Influence and Interest Diffusion Network for Social Recommendation
  15 Jan 2020 4 repositories listed
  Recently, we propose a preliminary work of a neural influence diffusion network (i.
• Hybrid Recommender System based on Autoencoders
  24 Jun 2016 4 repositories listed
  A standard model for Recommender Systems is the Matrix Completion setting: given partially known matrix of ratings given by users (rows) to items (columns), infer the unknown ratings.
• A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems
  16 Aug 2023 3 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  As the focus on Large Language Models (LLMs) in the field of recommendation intensifies, the optimization of LLMs for recommendation purposes (referred to as LLM4Rec) assumes a crucial role in augmenting their…
• Popularity Bias in Collaborative Filtering-Based Multimedia Recommender Systems
  1 Mar 2022 3 repositories listed
  In this paper, we investigate a potential issue of such collaborative-filtering based multimedia recommender systems, namely popularity bias that leads to the underrepresentation of unpopular items in the recommendation…
• An Evaluation Study of Generative Adversarial Networks for Collaborative Filtering
  5 Jan 2022 3 repositories listed
  This work explores the reproducibility of CFGAN.
• Pareto Optimality for Fairness-constrained Collaborative Filtering
  17 Sep 2021 3 repositories listed
  To balance overall recommendation performance and fairness, prevalent solutions apply fairness constraints or regularizations to enforce equality of certain performance across different subgroups.
• GLocal-K: Global and Local Kernels for Recommender Systems
  27 Aug 2021 3 repositories listed
  Then, the pre-trained auto encoder is fine-tuned with the rating matrix, produced by a convolution-based global kernel, which captures the characteristics of each item.
• Federated Reconstruction: Partially Local Federated Learning
  5 Feb 2021 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  We also describe the successful deployment of this approach at scale for federated collaborative filtering in a mobile keyboard application.
• Learning User Representations with Hypercuboids for Recommender Systems
  11 Nov 2020 3 repositories listed
  Furthermore, we present two variants of hypercuboids to enhance the capability in capturing the diversities of user interests.
• Self-supervised Graph Learning for Recommendation
  21 Oct 2020 3 repositories listed
  In this work, we explore self-supervised learning on user-item graph, so as to improve the accuracy and robustness of GCNs for recommendation.
• Neural Collaborative Reasoning
  16 May 2020 3 repositories listed
  Existing Collaborative Filtering (CF) methods are mostly designed based on the idea of matching, i.

Syntology lines on 12 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.