Awesome Cold Start & Cross-Domain

Key papers

• LLM-Enhanced Multimodal Fusion for Cross-Domain Sequential Recommendation (2025)
  Wangyu Wu et al.
  7.72
• MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation (2025)
  Yi Xu et al.
  7.68
• Image Fusion for Cross-Domain Sequential Recommendation (2025)
  Wangyu Wu et al.
  7.64
• AlphaFuse: Learn ID Embeddings for Sequential Recommendation in Null Space of Language Embeddings (2025)
  Guoqing Hu et al.
  7.46
• Contrastive Learning for Cold Start Recommendation with Adaptive Feature Fusion (2025)
  Jiacheng Hu et al.
  7.19
• AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems (2025)
  Yu Shang et al.
  6.80
• ABXI: Invariant Interest Adaptation for Task-Guided Cross-Domain Sequential Recommendation (2025)
  Qingtian Bian et al.
  6.58
• Unified Representation Learning for Multi-Intent Diversity and Behavioral Uncertainty in Recommender Systems (2025)
  Wei Xu et al.
  6.56
• Align-for-Fusion: Harmonizing Triple Preferences via Dual-oriented Diffusion for Cross-domain Sequential Recommendation (2025)
  Yongfu Zha et al.
  6.23
• Enhancing User Intent for Recommendation Systems via Large Language Models (2025)
  Xiaochuan Xu et al.
  6.12
• Tricolore: Multi-Behavior User Profiling for Enhanced Candidate Generation in Recommender Systems (2025)
  Xiao Zhou et al.
  6.07
• Bridge the Domains: Large Language Models Enhanced Cross-domain Sequential Recommendation (2025)
  Qidong Liu et al.
  6.01
• Uncovering Cross-Domain Recommendation Ability of Large Language Models (2025)
  Xinyi Liu et al.
  5.96
• Unleashing the Potential of Two-Tower Models: Diffusion-Based Cross-Interaction for Large-Scale Matching (2025)
  Yihan Wang et al.
  5.90
• A Survey on Side Information-driven Session-based Recommendation: From a Data-centric Perspective (2025)
  Xiaokun Zhang et al.
  5.76
• A Comprehensive Survey on Cross-Domain Recommendation: Taxonomy, Progress, and Prospects (2025)
  Hao Zhang et al.
  5.65
• Continual Recommender Systems (2025)
  Hyunsik Yoo et al.
  5.52
• A Comprehensive Review on Harnessing Large Language Models to Overcome Recommender System Challenges (2025)
  Rahul Raja et al.
  5.52
• Bridging the Semantic-Collaborative Gap: An Asymmetric Graph Architecture for Cold-Start Item Recommendation (2026)
  Anh Truong et al.
  5.49
• DisCo: Graph-Based Disentangled Contrastive Learning for Cold-Start Cross-Domain Recommendation (2024)
  Hourun Li et al.
  5.13
• TransRec: Learning Transferable Recommendation from Mixture-of-Modality Feedback (2022)
  Jie Wang et al.
  5.06
• Capturing User Interests from Data Streams for Continual Sequential Recommendation (2025)
  Gyuseok Lee et al.
  5.04
• The Application of Large Language Models in Recommendation Systems (2025)
  Peiyang Yu et al.
  4.76
• On Inherited Popularity Bias in Cold-Start Item Recommendation (2025)
  Gregor Meehan and Johan Pauwels
  4.75
• Think before Recommendation: Autonomous Reasoning-enhanced Recommender (2025)
  Xiaoyu Kong et al.
  4.75
• Efficient Cold-Start Recommendation via BPE Token-Level Embedding Initialization with LLM (2025)
  Yushang Zhao et al.
  4.69
• Does Multimodality Improve Recommender Systems as Expected? A Critical Analysis and Future Directions (2025)
  Hongyu Zhou et al.
  4.64
• Recommendation Is a Dish Better Served Warm (2025)
  Danil Gusak et al.
  4.64
• Refining Contrastive Learning and Homography Relations for Multi-Modal Recommendation (2025)
  Shouxing Ma et al.
  4.64
• Revealing Potential Biases in LLM-Based Recommender Systems in the Cold Start Setting (2025)
  Alexandre Andre et al.
  4.64
• Leave No One Behind: Fairness-Aware Cross-Domain Recommender Systems for Non-Overlapping Users (2025)
  Weixin Chen and Yuhan Zhao and Li Chen and Weike Pan
  4.58
• Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems (2025)
  Langming Liu et al.
  4.53
• MDVT: Enhancing Multimodal Recommendation with Model-Agnostic Multimodal-Driven Virtual Triplets (2025)
  Jinfeng Xu et al.
  4.47
• Semantic-enhanced Co-attention Prompt Learning for Non-overlapping Cross-Domain Recommendation (2025)
  Lei Guo et al.
  4.47
• Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation (2025)
  Chendi Ge et al.
  4.42
• Enhancing New-item Fairness in Dynamic Recommender Systems (2025)
  Huizhong Guo et al.
  4.42
• Taiji: Pareto Optimal Policy Optimization with Semantics-IDs Trade-off for Industrial LLM-Enhanced Recommendation (2026)
  Yuecheng Li et al.
  4.39
• Beyond Relevance: An Adaptive Exploration-Based Framework for Personalized Recommendations (2025)
  Edoardo Bianchi
  4.36
• CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation (2023)
  Yang Zhang et al.
  4.35
• Intent Representation Learning with Large Language Model for Recommendation (2025)
  Yu Wang and Lei Sang and Yi Zhang and Yiwen Zhang
  4.30
• Order-agnostic Identifier for Large Language Model-based Generative Recommendation (2025)
  Xinyu Lin et al.
  4.30
• Exploring Preference-Guided Diffusion Model for Cross-Domain Recommendation (2025)
  Xiaodong Li et al.
  4.25
• A Contrastive Framework with User, Item and Review Alignment for Recommendation (2025)
  Hoang V. Dong et al.
  4.25
• Topic-Aware Knowledge Graph with Large Language Models for Interoperability in Recommender Systems (2024)
  Minhye Jeon et al.
  4.19
• WeaveRec: An LLM-Based Cross-Domain Sequential Recommendation Framework with Model Merging (2025)
  Min Hou et al.
  4.09
• RankGraph: Unified Heterogeneous Graph Learning for Cross-Domain Recommendation (2025)
  Renzhi Wu and Junjie Yang and Li Chen and Hong Li and Li Yu and Hong Yan
  4.03
• Multimodal Foundation Model-Driven User Interest Modeling and Behavior Analysis on Short Video Platforms (2025)
  Yushang Zhao et al.
  4.03
• A Survey of Real-World Recommender Systems: Challenges, Constraints, and Industrial Perspectives (2025)
  Kuan Zou et al.
  4.03
• TransFR: Transferable Federated Recommendation with Adapter Tuning on Pre-trained Language Models (2024)
  Honglei Zhang et al.
  4.02
• Dual prototype attentive graph network for cross-market recommendation (2025)
  Li Fan et al.
  3.97
• DenseRec: Revisiting Dense Content Embeddings for Sequential Transformer-based Recommendation (2025)
  Jan Malte Lichtenberg and Antonio De Candia and Matteo Ruffini
  3.97
• Leveraging Multimodal Data and Side Users for Diffusion Cross-Domain Recommendation (2025)
  Fan Zhang et al.
  3.92
• Heterogeneous User Modeling for LLM-based Recommendation (2025)
  Honghui Bao et al.
  3.92
• Personalized Diffusion Model Reshapes Cold-Start Bundle Recommendation (2025)
  Tuan-Nghia Bui et al.
  3.81
• Addressing Cold-start Problem in Click-Through Rate Prediction via Supervised Diffusion Modeling (2025)
  Wenqiao Zhu et al.
  3.75
• SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation (2025)
  Nicolas Bougie and Narimasa Watanabe
  3.75
• MMHCL: Multi-Modal Hypergraph Contrastive Learning for Recommendation (2025)
  Xu Guo et al.
  3.75
• Separated Contrastive Learning for Matching in Cross-domain Recommendation with Curriculum Scheduling (2025)
  Heng Chang et al.
  3.64
• Atomic Intent Reasoning: Bringing LLM Semantics to Industrial Cross-Domain Recommendations (2026)
  Zhuohang Jiang et al.
  3.51
• Towards Generalizable and Efficient Large-Scale Generative Recommenders (2026)
  Qiuling Xu et al.
  3.45