Multimodal Recommendation

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

5 leaderboard tables shown for this task, 5 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.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 33 papers with code (59 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.

• A Comprehensive Survey on Multimodal Recommender Systems: Taxonomy, Evaluation, and Future Directions
  9 Feb 2023 2 repositories listed
  Recommendation systems have become popular and effective tools to help users discover their interesting items by modeling the user preference and item property based on implicit interactions (e.
• A Tale of Two Graphs: Freezing and Denoising Graph Structures for Multimodal Recommendation
  13 Nov 2022 2 repositories listed
  Based on this finding, we propose a simple yet effective model, dubbed as FREEDOM, that FREEzes the item-item graph and DenOises the user-item interaction graph simultaneously for Multimodal recommendation.
• Quadratic Interest Network for Multimodal Click-Through Rate Prediction
  24 Apr 2025 1 repository listed
  Multimodal click-through rate (CTR) prediction is a key technique in industrial recommender systems.
• COHESION: Composite Graph Convolutional Network with Dual-Stage Fusion for Multimodal Recommendation
  6 Apr 2025 1 repository listed
  Two key processes in multimodal recommendations are modality fusion and representation learning.
• Collaborative Filtering Meets Spectrum Shift: Connecting User-Item Interaction with Graph-Structured Side Information
  12 Feb 2025 1 repository listed
  However, when graph-structured side information (e.
• Generating with Fairness: A Modality-Diffused Counterfactual Framework for Incomplete Multimodal Recommendations
  21 Jan 2025 1 repository listed
  However, two significant gaps persist: 1) the difficulty in accurately generating missing data due to the limited ability to capture modality distributions; and 2) the critical but overlooked visibility bias, where…
• Dynamic Multimodal Fusion via Meta-Learning Towards Micro-Video Recommendation
  13 Jan 2025 1 repository listed
  In this paper, we develop a novel meta-learning-based multimodal fusion framework called Meta Multimodal Fusion (MetaMMF), which dynamically assigns parameters to the multimodal fusion function for each micro-video…
• Spectrum-based Modality Representation Fusion Graph Convolutional Network for Multimodal Recommendation
  19 Dec 2024 1 repository listed
  Moreover, the variation of noise that is unique within each modality results in noise alleviation and fusion being more challenging.
• Modality-Independent Graph Neural Networks with Global Transformers for Multimodal Recommendation
  18 Dec 2024 1 repository listed
  Our results indicate that the optimal K for certain modalities on specific datasets can be as low as 1 or 2, which may restrict the GNNs' capacity to capture global information.
• Beyond Graph Convolution: Multimodal Recommendation with Topology-aware MLPs
  16 Dec 2024 1 repository listed
  Given the large volume of side information from different modalities, multimodal recommender systems have become increasingly vital, as they exploit richer semantic information beyond user-item interactions.
• STAIR: Manipulating Collaborative and Multimodal Information for E-Commerce Recommendation
  16 Dec 2024 1 repository listed
  In order to combine the two distinct types of information, some additional challenges are encountered: 1) Modality erasure: Vanilla graph convolution, which proves rather useful in collaborative filtering, however…
• A Multimodal Single-Branch Embedding Network for Recommendation in Cold-Start and Missing Modality Scenarios
  26 Sep 2024 1 repository listed
  We show that SiBraR's recommendations are accurate in missing modality scenarios, and that the model is able to map different modalities to the same region of the shared embedding space, hence reducing the modality gap.
• Train Once, Deploy Anywhere: Matryoshka Representation Learning for Multimodal Recommendation
  25 Sep 2024 1 repository listed
  Our fMRLRec captures item features at different granularities, learning informative representations for efficient recommendation across multiple dimensions.
• Ducho meets Elliot: Large-scale Benchmarks for Multimodal Recommendation
  24 Sep 2024 1 repository listed
  In specific domains like fashion, music, and movie recommendation, the multi-faceted features characterizing products and services may influence each customer on online selling platforms differently, paving the way to…
• Do We Really Need to Drop Items with Missing Modalities in Multimodal Recommendation?
  21 Aug 2024 1 repository listed Syntology ran 4 of 5 samples · 1 unverified · 5 pointer-only (licence)
  Generally, items with missing modalities are dropped in multimodal recommendation.
• Harnessing Multimodal Large Language Models for Multimodal Sequential Recommendation
  19 Aug 2024 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  Recent advances in Large Language Models (LLMs) have demonstrated significant potential in the field of Recommendation Systems (RSs).
• Modality-Balanced Learning for Multimedia Recommendation
  26 Jul 2024 1 repository listed
  To address these issues, we propose a Counterfactual Knowledge Distillation method that could solve the imbalance problem and make the best use of all modalities.
• GUME: Graphs and User Modalities Enhancement for Long-Tail Multimodal Recommendation
  17 Jul 2024 1 repository listed Syntology ran 5 of 6 samples · 1 unverified · 6 pointer-only (licence)
  By using the user modality enhancement strategy to maximize mutual information between these two features, we improve the generalization ability of user modality representations.
• End-to-end training of Multimodal Model and ranking Model
  9 Apr 2024 1 repository listed
  In this paper, we propose an industrial multimodal recommendation framework named EM3: End-to-end training of Multimodal Model and ranking Model, which sufficiently utilizes multimodal information and allows…
• AlignRec: Aligning and Training in Multimodal Recommendations
  19 Mar 2024 1 repository listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  Each alignment is characterized by a specific objective function and is integrated into our multimodal recommendation framework.
• Ducho 2.0: Towards a More Up-to-Date Unified Framework for the Extraction of Multimodal Features in Recommendation
  7 Mar 2024 1 repository listed
  In this work, we introduce Ducho 2.
• MENTOR: Multi-level Self-supervised Learning for Multimodal Recommendation
  29 Feb 2024 1 repository listed
  It utilizes multimodal information to alleviate the data sparsity problem in recommendation systems, thus improving recommendation accuracy.
• Disentangled Graph Variational Auto-Encoder for Multimodal Recommendation with Interpretability
  25 Feb 2024 1 repository listed
  While the incorporation of multimodal information could enhance the interpretability of these systems, current multimodal models represent users and items utilizing entangled numerical vectors, rendering them arduous to…
• Mirror Gradient: Towards Robust Multimodal Recommender Systems via Exploring Flat Local Minima
  17 Feb 2024 1 repository listed
  This strategy can implicitly enhance the model's robustness during the optimization process, mitigating instability risks arising from multimodal information inputs.
• LGMRec: Local and Global Graph Learning for Multimodal Recommendation
  27 Dec 2023 1 repository listed
  The multimodal recommendation has gradually become the infrastructure of online media platforms, enabling them to provide personalized service to users through a joint modeling of user historical behaviors (e.
• Causality-Inspired Fair Representation Learning for Multimodal Recommendation
  26 Oct 2023 1 repository listed
  Recently, multimodal recommendations (MMR) have gained increasing attention for alleviating the data sparsity problem of traditional recommender systems by incorporating modality-based representations.
• Semantic-Guided Feature Distillation for Multimodal Recommendation
  6 Aug 2023 1 repository listed
  The teacher model first extracts rich modality features from the generic modality feature by considering both the semantic information of items and the complementary information of multiple modalities.
• LightGT: A Light Graph Transformer for Multimedia Recommendation
  18 Jul 2023 1 repository listed
  Considering its challenges in effectiveness and efficiency, we propose a novel Transformer-based recommendation model, termed as Light Graph Transformer model (LightGT).
• Ducho: A Unified Framework for the Extraction of Multimodal Features in Recommendation
  29 Jun 2023 1 repository listed
  Motivated by the outlined aspects, we propose \framework, a unified framework for the extraction of multimodal features in recommendation.
• MMRec: Simplifying Multimodal Recommendation
  2 Feb 2023 1 repository listed
  This paper presents an open-source toolbox, MMRec for multimodal recommendation.

Syntology lines on 4 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.