Multimodal Recommendation

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2 papers in the last four weeks, down 75% on the four weeks before. 0.0% of all new papers.

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Multimodal Graph Retrieval-Augmented Sequential Recommendation via Collaborative Filtering Paths
Oct 8, 2026Jason Marcell Setiadi, Xin Cao, Lina YaoRecommender Systems Sequential Recommendation
University of New South Wales, Sydney, Australia
MM-VeriRec: Failure-Guided Fusion for Verifiable Agentic Multimodal Recommendation
Sep 21, 2026Yufeng WangMultimodal Recommendation Multimodal Agents
Independent Research United States
Efficient Multimodal Generative Recommendation with Latent Narrative Reasoning
Sep 13, 2026Chenxing Wang, Nantao Zheng, Hao Miao +5Multimodal Recommendation Generative Recommendation
Weixin Group, Tencent · The Hong Kong Polytechnic University
Latent-Aligned Reasoning for Multimodal Recommendation
Sep 4, 2026Jiarui Jin, Anyang JiMultimodal Recommendation VLM Reasoning
Xiaohongshu Inc. · Nanjing University
MURAL: Multimodal Uncertainty-aware Recommendation via Adaptive edge Learning
Sep 4, 2026Ahmad Mousavi, Majid Alikhani, Yeon-Chang Lee +2Multimodal Recommendation Multimodal Graph Learning
Department of Mathematics and Statistics American University · Independent Researcher Toronto, Ontario, Canada · Independent Researcher +4
Beyond Modality Harmony: Orthogonal Purification and Topology-Guided MoE for Conflict-Aware Multimodal Recommendation
Sep 2, 2026Jialin Liu, Zhaorui Zhang, Ray C. C. CheungRecommender Systems Multimodal Recommendation
City University of Hong Kong Hong Kong, Hong Kong · The Hong Kong Polytechnic University Hong Kong, Hong Kong
From Gradient-Boosted Trees to Deep Recommenders: Practical Lessons from Migrating a Production Customer Support Recommender
Aug 25, 2026Sonia Sharma, Jeyendran Balakrishnan, Shreya Rajpal +3Recommender Systems Learning to Rank
Multi-Modal Semantic Expansion with Constrained LLM Reranking for Conversational Music Recommendation
Aug 24, 2026Naman Garg, Sarika Jain, George FazekasMultimodal Recommendation Large Language Model-Based Recommendation
National Institute of Technology Kurukshetra India · Queen Mary University of London United Kingdom
SA-RSQ: A Versatile Sparse Representation Framework for Multi-modal Recommender Systems
Aug 24, 2026Xiang Wang, Shigang Quan, Tingzhen Chang +5Vector Quantization Residual VQ
Tianjin University Tianjin, China · Meituan Beijing, China · Institute of Software Chinese Academy of Sciences Beijing, China
TimeRoute: Time-Aware Modality Routing and Diffusion for Multi-Modal Recommendation
Aug 11, 2026Pengyu Zhang, Yangqin Jiang, Klim Zaporojets +2Recommender Systems Multimodal Recommendation
University of Amsterdam Amsterdam, The Netherlands · University of Hong Kong Hong Kong, China · Aarhus University Aarhus, Denmark
Sequential Modality Dropout for Robust Multi-Modal Sequential Recommendation
Aug 10, 2026Guanqun Yang, Wenlong ZhangMissing-Modality Learning Multimodal Robustness
Stevens Institute of Technology Hoboken, NJ, USA
Shape Your Feed: An LLM-based Agentic System for Conversational Recommendation
Aug 6, 2026Ziyun Xu, Bosen Ding, Yue Zhang +10LLM Reranking Recommender Systems
Meta Platforms Menlo Park, California, USA
What to Edit Next: Visually Aligned Image-Editing Follow-Up Suggestions in Conversational Systems
Aug 3, 2026Zhijing Zhang, Jinpeng Yu, Xin Song +6Multimodal Recommendation Image Editing
1Qwen Business Unit of Alibaba · 2Southeast University
GALA: Generative Aligned Learning for Adaptive Multimodal Representation in the Taobao Shangou Recommender System
Jul 31, 2026Jiping Liu, Zhongmin Zhang, Zisen Sang +7Cross-Modal Alignment Multimodal Pretraining
Rajax Network Technology (Taobao Shangou of Alibaba) · Shanghai & Beijing, China · Central South University +1
PaletteID: Prototype-Composed Semantic Identifiers for Multimodal CTR Prediction
Jul 31, 2026Huanyu Liu, Baining Chen, Hui Liu +2Semantic ID Recommendation Prototype Learning
Huazhong University of Science and Technology Wuhan, Hubei, China · Central China Normal University Wuhan, Hubei, China
SlimPer: Make Personalization Model Slim and Smart
Jul 14, 2026Siqi Wang, Xianjie Chen, Shaofeng Deng +42Learning to Rank Memory-Efficient Inference
Multimodal Video-to-Music Recommendation via Semantic Retrieval and Temporal Reranking
Jul 7, 2026Seungheon Doh, Minhee Lee, Sangmoon Lee +2Cross-Modal Alignment Multimodal Embedding
Graduate School of Culture Technology, KAIST, South Korea · Gaudio Lab, Inc, South Korea
VCG: A Multimodal Retrieval Framework for E-Commerce Video Feeds under Extreme Cold-Start Conditions
Jun 17, 2026Katya Mirylenka, Egor Malykh, Mahdyar Ravanbakhsh +10Multimodal IR Cold-Start Recommendation
TU Wien, Vienna, Austria · Zalando Switzerland AG, Zurich, Switzerland · Zalando SE, Berlin, Germany
ReasonRec: A Reasoning-Augmented Multimodal Agent for Unified Recommendation
Jun 8, 2026Yihua Zhang, Mingfu Liang, Jiyan Yang +11Efficient Multimodal Inference Multimodal CoT Reasoning
Meta AI · Michigan State University · The University of North Carolina at Chapel Hill +1
Multimodal Music Recommendation System using LLMs
May 28, 2026Srikar Prabhas Kandagatla, Sreehitha R. Narayana, Chandana Magapu +6Sequential Recommendation Recommender Systems
University of Massachusetts Amherst, Massachusetts, USA · Dolby Laboratories Atlanta, Georgia, USA · Adobe Research San Jose, California, USA +2
FLUID: From Ephemeral IDs to Multimodal Semantic Codes for Industrial-Scale Livestreaming Recommendation
May 20, 2026Xinhang Yuan, Zexi Huang, Anjia Cao +6Semantic ID Recommendation Cold-Start Recommendation
TikTok · ByteDance
SynGR: Unleashing the Potential of Cross-Modal Synergy for Generative Recommendation
May 18, 2026Wei Chen, Xingyu Guo, Shuang Li +6Recommender Systems Multimodal Recommendation
School of Artificial Intelligence, Beihang University, Beijing, China · School of Computer Science and Engineering, Beihang University, Beijing, China
Band Together: Untargeted Adversarial Training with Multimodal Coordination against Evasion-based Promotion Attacks
May 7, 2026Guanmeng Xian, Ning Yang, Philip S. YuAdversarial Training Multimodal Robustness
Sichuan University, Chengdu, China · University of Illinois at Chicago, USA
TimeMM: Time-as-Operator Spectral Filtering for Dynamic Multimodal Recommendation
Apr 29, 2026Wei Yang, Rui Zhong, Zihan Lin +4Dynamic Graph Learning Recommender Systems
Xiaohongshu Inc. · Beijing, China
Where and What: Reasoning Dynamic and Implicit Preferences in Situated Conversational Recommendation
Apr 22, 2026Dongding Lin, Jian Wang, Yongqi Li +1Recommender Systems Large Language Model-Based Recommendation
Department of Computing, The Hong Kong Polytechnic University · College of Computer Science, Sichuan University
TRU: Targeted Reverse Update for Efficient Multimodal Recommendation Unlearning
Apr 2, 2026Zhanting Zhou, KaHou Tam, Zeyu Ma +2Recommender Systems Multimodal Recommendation
University of Electronic Science and Technology of China Chengdu, China · University of Macau Macau, Macao
IDProxy: CTR Prediction with Multimodal LLMs for Cold-Start Recommendation at Xiaohongshu
Mar 2, 2026Yubin Zhang, Haiming Xu, Guillaume Salha-Galvan +6Cold-Start Recommendation Multimodal Embedding
Xiaohongshu Inc. Shanghai, China · Shanghai Jiao Tong University Shanghai, China · Fudan University Shanghai, China
Modality-Guided Mixture of Structured Experts with Entropy-Triggered Routing for Multimodal Recommendation
Feb 24, 2026Ji Dai, Quan Fang, DeSheng CaiSparse Mixture-of-Experts Recommender Systems
Beijing University of Posts and Telecommunications, China · Beijing University of Posts and Telecommunications, Beijing, China · Tianjin University of Technology, China
EGRA:Toward Enhanced Behavior Graphs and Representation Alignment for Multimodal Recommendation
Aug 22, 2025Xiaoxiong Zhang, Xin Zhou, Zhiwei Zeng +2Cross-Modal Alignment Multimodal Embedding
College of Computing and Data Science, Nanyang Technological University, Singapore

Oct 8, 2026, cs.LGJ/K move · Enter open · S save

Multimodal Graph Retrieval-Augmented Sequential Recommendation via Collaborative Filtering Paths

Jason Marcell Setiadi, Xin Cao, Lina Yao

University of New South Wales, Sydney, Australia

Recommender Systems Sequential Recommendation Multimodal Recommendation Large Language Model-Based Recommendation

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Multimodal Large Language Models (MLLMs) have demonstrated strong potential for sequential recommendation through their ability to reason over complex multimodal data. However, existing approaches either rely solely on the target user's own interaction history, neglecting collaborative signals from neighboring users, or incur substantial computational overhead through repeated MLLM inference over long interaction histories. To address these challenges, we propose MGRASRec, a multimodal graph retrieval-augmented framework for sequential recommendation. MGRASRec injects collaborative filtering signals conditioned on the candidate item directly into the MLLM prompt by retrieving structured paths from a user-item interaction graph, extended via multimodal similarity to increase coverage beyond exact co-interaction overlap. This retrieval also surfaces the history items most relevant to the candidate at no additional cost, removing the need for recurrent summarization and keeping inference to a single forward pass per candidate. All components are unified into an augmented prompt for parameter-efficient fine-tuning of an MLLM. Extensive evaluations across three publicly available datasets validate the effectiveness of MGRASRec, achieving the best performance on all metrics with particularly strong gains in ranking quality.

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Latest papers 22