{"total":80,"rows":[{"id":"2503.02453","title":"Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations","created":"2025-03-04","cited_by_count":35,"area":null},{"id":"2502.13581","title":"ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation","created":"2025-02-19","cited_by_count":18,"area":null},{"id":"2502.04397","title":"Multimodal Medical Code Tokenizer","created":"2025-02-06","cited_by_count":14,"area":null},{"id":"2508.04618","title":"HiD-VAE: Interpretable Generative Recommendation via Hierarchical and Disentangled Semantic IDs","created":"2025-08-06","cited_by_count":12,"area":null},{"id":"2511.22707","title":"CoFiRec: Coarse-to-Fine Tokenization for Generative Recommendation","created":"2025-11-27","cited_by_count":11,"area":null},{"id":"2508.15281","title":"MMQ: Multimodal Mixture-of-Quantization Tokenization for Semantic ID Generation and User Behavioral Adaptation","created":"2025-08-21","cited_by_count":10,"area":null},{"id":"2410.22809","title":"Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation","created":"2024-10-30","cited_by_count":8,"area":null},{"id":"2504.04405","title":"Universal Item Tokenization for Transferable Generative Recommendation","created":"2025-04-06","cited_by_count":7,"area":null},{"id":"2506.01673","title":"GRAM: Generative Recommendation via Semantic-aware Multi-granular Late Fusion","created":"2025-06-02","cited_by_count":7,"area":null},{"id":"2602.22732","title":"Generative Recommendation for Large-Scale Advertising","created":"2026-02-26","cited_by_count":7,"area":null},{"id":"2412.08604","title":"Preference Discerning with LLM-Enhanced Generative Retrieval","created":"2024-12-11","cited_by_count":6,"area":null},{"id":"2505.03336","title":"Eliminating Out-of-Domain Recommendations in LLM-based Recommender Systems: A Unified View","created":"2025-05-06","cited_by_count":6,"area":null},{"id":"2511.18793","title":"NEZHA: A Zero-sacrifice and Hyperspeed Decoding Architecture for Generative Recommendations","created":"2025-11-24","cited_by_count":6,"area":null},{"id":"2603.00632","title":"Stop Treating Collisions Equally: Qualification-Aware Semantic ID Learning for Recommendation at Industrial Scale","created":"2026-02-28","cited_by_count":6,"area":null},{"id":"2508.14646","title":"OneLoc: Geo-Aware Generative Recommender Systems for Local Life Service","created":"2025-08-20","cited_by_count":5,"area":null},{"id":"2604.05113","title":"CRAB: Codebook Rebalancing for Bias Mitigation in Generative Recommendation","created":"2026-04-06","cited_by_count":5,"area":null},{"id":"2604.14878","title":"GenRec: A Preference-Oriented Generative Framework for Large-Scale Recommendation","created":"2026-04-16","cited_by_count":5,"area":null},{"id":"2502.03041","title":"Large Language Model as Universal Retriever in Industrial-Scale Recommender System","created":"2025-02-05","cited_by_count":4,"area":null},{"id":"2504.04400","title":"Pre-training Generative Recommender with Multi-Identifier Item Tokenization","created":"2025-04-06","cited_by_count":4,"area":null},{"id":"2506.16683","title":"A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation","created":"2025-06-20","cited_by_count":4,"area":null},{"id":"2503.05493","title":"Can LLMs Outshine Conventional Recommenders? A Comparative Evaluation","created":"2025-03-07","cited_by_count":3,"area":null},{"id":"2503.23333","title":"Beyond Unimodal Boundaries: Generative Recommendation with Multimodal Semantics","created":"2025-03-30","cited_by_count":3,"area":null},{"id":"2510.21276","title":"Pctx: Tokenizing Personalized Context for Generative Recommendation","created":"2025-10-24","cited_by_count":3,"area":null},{"id":"2511.15122","title":"Multi-Aspect Cross-modal Quantization for Generative Recommendation","created":"2025-11-19","cited_by_count":3,"area":null},{"id":"2601.14697","title":"When Text-as-Vision Meets Semantic IDs in Generative Recommendation: An Empirical Study","created":"2026-01-21","cited_by_count":3,"area":null},{"id":"2602.10445","title":"End-to-End Semantic ID Generation for Generative Advertisement Recommendation","created":"2026-02-11","cited_by_count":3,"area":null},{"id":"2607.24995","title":"Understanding Semantic IDs: From Item Representation to Item Selection in Generative Recommendation","created":"2026-07-27","cited_by_count":3,"area":null},{"id":"2408.08686","title":"MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender","created":"2024-08-16","cited_by_count":2,"area":null},{"id":"2509.02017","title":"Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs","created":"2025-09-02","cited_by_count":2,"area":null},{"id":"2509.13957","title":"Enhancing Time Awareness in Generative Recommendation","created":"2025-09-17","cited_by_count":2,"area":null},{"id":"2509.23649","title":"From Past To Path: Masked History Learning for Next-Item Prediction in Generative Recommendation","created":"2025-09-28","cited_by_count":2,"area":null},{"id":"2510.25093","title":"Continual Low-Rank Adapters for LLM-based Generative Recommender Systems","created":"2025-10-29","cited_by_count":2,"area":null},{"id":"2602.02338","title":"Rethinking Generative Recommender Tokenizer: Recsys-Native Encoding and Semantic Quantization Beyond LLMs","created":"2026-02-02","cited_by_count":2,"area":null},{"id":"2604.02324","title":"Grounded Token Initialization for New Vocabulary in LMs for Generative Recommendation","created":"2026-04-02","cited_by_count":2,"area":null},{"id":"2605.16825","title":"Echoes in Filter Bubble: Diagnosing and Curing Popularity Bias in Generative Recommenders","created":"2026-05-16","cited_by_count":2,"area":null},{"id":"2605.17648","title":"SAPO: Step-Aligned Policy Optimization for Reasoning-Based Generative Recommendation","created":"2026-05-17","cited_by_count":2,"area":null},{"id":"2607.21101","title":"Can Generative Recommendation Reach Cold Items? A Temporal Perspective on Semantic-ID Generation","created":"2026-07-23","cited_by_count":2,"area":null},{"id":"2505.23053","title":"Augment or Not? A Comparative Study of Pure and Augmented Large Language Model Recommenders","created":"2025-05-29","cited_by_count":1,"area":null},{"id":"2511.17913","title":"Token-Controlled Re-ranking for Sequential Recommendation via LLMs","created":"2025-11-22","cited_by_count":1,"area":null},{"id":"2511.20673","title":"Semantics Meet Signals: Dual Codebook Representationl Learning for Generative Recommendation","created":"2025-11-15","cited_by_count":1,"area":null},{"id":"2512.24787","title":"HiGR: Industrial-Scale Hierarchical Generative Slate Recommendation Framework in Tencent","created":"2025-12-31","cited_by_count":1,"area":null},{"id":"2601.17438","title":"UniGRec: Unified Generative Recommendation with Soft Identifiers for End-to-End Optimization","created":"2026-01-24","cited_by_count":1,"area":null},{"id":"2603.14259","title":"GenRecEdit: Adapting Model Editing for Generative Recommendation with Cold-Start Items","created":"2026-03-15","cited_by_count":1,"area":null},{"id":"2605.07125","title":"An Embarrassingly Simple Graph Heuristic Reveals Shortcut-Solvable Benchmarks for Sequential Recommendation","created":"2026-05-08","cited_by_count":1,"area":null},{"id":"2605.17779","title":"Learning Variable-Length Tokenization for Generative Recommendation","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2605.18920","title":"SynGR: Unleashing the Potential of Cross-Modal Synergy for Generative Recommendation","created":"2026-05-18","cited_by_count":1,"area":null},{"id":"2606.14260","title":"ChronoID: Infusing Explicit Temporal Signals into Semantic IDs for Generative Recommendation","created":"2026-06-12","cited_by_count":1,"area":null},{"id":"2607.25216","title":"TopoGR: Revealing and Preserving Latent Structure of Semantic ID in Generative Recommendation","created":"2026-07-28","cited_by_count":1,"area":null},{"id":"2608.29179","title":"History-Conditioned Joint-Prefix Alignment for Generative Recommendation","created":"2026-08-29","cited_by_count":1,"area":null},{"id":"2609.03522","title":"EPIC: Explicit Posterior Item Conditioning for Semantic ID Diffusion Recommendation","created":"2026-09-03","cited_by_count":1,"area":null},{"id":"2609.30576","title":"T-RoPE: Time-Aware Rotary Position Embedding for Sequential Recommendation","created":"2026-09-24","cited_by_count":1,"area":null},{"id":"2501.13344","title":"Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation","created":"2025-01-23","cited_by_count":0,"area":null},{"id":"2507.12871","title":"Generative Multi-Target Cross-Domain Recommendation","created":"2025-07-17","cited_by_count":0,"area":null},{"id":"2508.14910","title":"Closing the Performance Gap in Generative Recommenders with Collaborative Tokenization and Efficient Modeling","created":"2025-08-12","cited_by_count":0,"area":null},{"id":"2509.10468","title":"Learning Decomposed Contextual Token Representations from Pretrained and Collaborative Signals for Generative Recommendation","created":"2025-08-22","cited_by_count":0,"area":null},{"id":"2510.08932","title":"MATT-CTR: Unleashing a Model-Agnostic Test-Time Paradigm for CTR Prediction with Confidence-Guided Inference Paths","created":"2025-10-10","cited_by_count":0,"area":null},{"id":"2602.21677","title":"Trie-Aware Transformers for Generative Recommendation","created":"2026-02-25","cited_by_count":0,"area":null},{"id":"2605.09040","title":"UxSID: Semantic-Aware User Interests Modeling for Ultra-Long Sequence","created":"2026-05-09","cited_by_count":0,"area":null},{"id":"2605.11447","title":"Conditional Memory Enhanced Item Representation for Generative Recommendation","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2606.17276","title":"On the Memorization Behavior of LLMs in Generative Recommendation: Observations, Implications, and Training Strategies","created":"2026-06-15","cited_by_count":0,"area":null},{"id":"2606.21911","title":"The Pitfall of Scaling Up: Uncovering and Mitigating Popularity Bias Amplification in Scaling Transformer-based Recommenders","created":"2026-06-20","cited_by_count":0,"area":null},{"id":"2607.25209","title":"VaLiDRec: Variable-Length LLM-Aligned Semantic IDs for Generative Recommendation","created":"2026-07-28","cited_by_count":0,"area":null},{"id":"2607.27944","title":"Interpretable Representation via LLM-Driven Generative Disentanglement for Local-Life Service Recommendation","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2608.10929","title":"FedCGR: Federated Cross-Domain Generative Recommendation","created":"2026-08-11","cited_by_count":0,"area":null},{"id":"2608.12570","title":"Attribute-Conditioned Multimodal Slot Factorization for Controllable Fashion Retrieval","created":"2026-08-12","cited_by_count":0,"area":null},{"id":"2608.18779","title":"SIDScope: A Diagnostic Resource for Semantic-ID Interfaces in Generative Recommendation","created":"2026-08-19","cited_by_count":0,"area":null},{"id":"2608.21012","title":"From a Static Multi-Level Small Semantic Codebook to a Dynamic Single-Level Large Semantic Codebook for Generative Recommendation","created":"2026-08-21","cited_by_count":0,"area":null},{"id":"2608.22979","title":"SA-RSQ: A Versatile Sparse Representation Framework for Multi-modal Recommender Systems","created":"2026-08-24","cited_by_count":0,"area":null},{"id":"2608.24176","title":"Tlow: Flow-based Item Tokenizer for Recommendation","created":"2026-08-25","cited_by_count":0,"area":null},{"id":"2608.30606","title":"Generative Retrieval for E-commerce: Jointly Learning Embedding and Codebook with Same Product Cluster","created":"2026-08-31","cited_by_count":0,"area":null},{"id":"2609.15598","title":"Self-Evolving Memory for Generative Recommendation","created":"2026-09-14","cited_by_count":0,"area":null},{"id":"2609.16070","title":"Efficient Multimodal Generative Recommendation with Latent Narrative Reasoning","created":"2026-09-13","cited_by_count":0,"area":null},{"id":"2609.22227","title":"Guiding the coarse levels of semantic IDs makes the fine levels learnable","created":"2026-09-03","cited_by_count":0,"area":null},{"id":"2609.29973","title":"Learning Better Reasoning for Generative Recommendation with Semantic IDs","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2609.29983","title":"From Interests to Semantic IDs: Retrieval-Grounded Credit Assignment for Generative Recommendation","created":"2026-09-24","cited_by_count":0,"area":null},{"id":"2609.36670","title":"FineSID: Scalable and Efficient Semantic Identifier Learning for Generative Recommendation","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2610.01533","title":"Neither Black nor White: Balancing Semantic and Collaborative Signals with Graph-Informed Semantic IDs (GrIS)","created":"2026-10-01","cited_by_count":0,"area":null},{"id":"2610.16979","title":"WeGR: Unified Generative Retrieval for Industrial Search Systems in WeChat","created":"2026-10-12","cited_by_count":0,"area":null},{"id":"2610.17368","title":"HASTE: Hierarchical and Attribute-aware Supervision for Generative Recommendation","created":"2026-10-12","cited_by_count":0,"area":null},{"id":"2610.18672","title":"SMI: Ontology-Grounded Semantic IDs for Hierarchy-Aware Medical Concept Representation","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}