Decoding in Latent Spaces for Efficient Inference in LLM-based Recommendation
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Chengbing, Zhang, Yang, Wang, Zhicheng, Shi, Tianhao, Bao, Keqin, Feng, Fuli, Chua, Tat-Seng |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Leveraging Memory Retrieval to Enhance LLM-based Generative Recommendation
by: Wang, Chengbing, et al.
Published: (2024)
by: Wang, Chengbing, et al.
Published: (2024)
Prospect Personalized Recommendation on Large Language Model-based Agent Platform
by: Zhang, Jizhi, et al.
Published: (2024)
by: Zhang, Jizhi, et al.
Published: (2024)
Heterogeneous User Modeling for LLM-based Recommendation
by: Bao, Honghui, et al.
Published: (2025)
by: Bao, Honghui, et al.
Published: (2025)
Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation
by: Bao, Keqin, et al.
Published: (2024)
by: Bao, Keqin, et al.
Published: (2024)
Data-efficient Fine-tuning for LLM-based Recommendation
by: Lin, Xinyu, et al.
Published: (2024)
by: Lin, Xinyu, et al.
Published: (2024)
Generative Recommendation: Towards Next-generation Recommender Paradigm
by: Wang, Wenjie, et al.
Published: (2023)
by: Wang, Wenjie, et al.
Published: (2023)
Efficient Inference for Large Language Model-based Generative Recommendation
by: Lin, Xinyu, et al.
Published: (2024)
by: Lin, Xinyu, et al.
Published: (2024)
Uplift Modeling for Target User Attacks on Recommender Systems
by: Wang, Wenjie, et al.
Published: (2024)
by: Wang, Wenjie, et al.
Published: (2024)
EARN: Efficient Inference Acceleration for LLM-based Generative Recommendation by Register Tokens
by: Yang, Chaoqun, et al.
Published: (2025)
by: Yang, Chaoqun, et al.
Published: (2025)
Order-agnostic Identifier for Large Language Model-based Generative Recommendation
by: Lin, Xinyu, et al.
Published: (2025)
by: Lin, Xinyu, et al.
Published: (2025)
Real-Time Personalization for LLM-based Recommendation with Customized In-Context Learning
by: Bao, Keqin, et al.
Published: (2024)
by: Bao, Keqin, et al.
Published: (2024)
CoLLM: Integrating Collaborative Embeddings into Large Language Models for Recommendation
by: Zhang, Yang, et al.
Published: (2023)
by: Zhang, Yang, et al.
Published: (2023)
Diffusion Recommender Model
by: Wang, Wenjie, et al.
Published: (2023)
by: Wang, Wenjie, et al.
Published: (2023)
Towards Sample-Efficient and Stable Reinforcement Learning for LLM-based Recommendation
by: Ding, Hongxun, et al.
Published: (2026)
by: Ding, Hongxun, et al.
Published: (2026)
Denoising Diffusion Recommender Model
by: Zhao, Jujia, et al.
Published: (2024)
by: Zhao, Jujia, et al.
Published: (2024)
Verifiable Reasoning for LLM-based Generative Recommendation
by: Lin, Xinyu, et al.
Published: (2026)
by: Lin, Xinyu, et al.
Published: (2026)
MiniRec: Data-Efficient Reinforcement Learning for LLM-based Recommendation
by: Wang, Lin, et al.
Published: (2026)
by: Wang, Lin, et al.
Published: (2026)
Temporally and Distributionally Robust Optimization for Cold-Start Recommendation
by: Lin, Xinyu, et al.
Published: (2023)
by: Lin, Xinyu, et al.
Published: (2023)
Causality-Enhanced Behavior Sequence Modeling in LLMs for Personalized Recommendation
by: Zhang, Yang, et al.
Published: (2024)
by: Zhang, Yang, et al.
Published: (2024)
Boosting Parameter Efficiency in LLM-Based Recommendation through Sophisticated Pruning
by: Zheng, Shanle, et al.
Published: (2025)
by: Zheng, Shanle, et al.
Published: (2025)
Learnable Item Tokenization for Generative Recommendation
by: Wang, Wenjie, et al.
Published: (2024)
by: Wang, Wenjie, et al.
Published: (2024)
A Federated Framework for LLM-based Recommendation
by: Zhao, Jujia, et al.
Published: (2024)
by: Zhao, Jujia, et al.
Published: (2024)
Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
by: Lin, Xinyu, et al.
Published: (2023)
by: Lin, Xinyu, et al.
Published: (2023)
Debias Can be Unreliable: Mitigating Bias Issue in Evaluating Debiasing Recommendation
by: Wang, Chengbing, et al.
Published: (2024)
by: Wang, Chengbing, et al.
Published: (2024)
Item-side Fairness of Large Language Model-based Recommendation System
by: Jiang, Meng, et al.
Published: (2024)
by: Jiang, Meng, et al.
Published: (2024)
Brownian Bridge Diffusion for Sequential Recommendation
by: Bai, Yimeng, et al.
Published: (2025)
by: Bai, Yimeng, et al.
Published: (2025)
Bringing Reasoning to Generative Recommendation Through the Lens of Cascaded Ranking
by: Lin, Xinyu, et al.
Published: (2026)
by: Lin, Xinyu, et al.
Published: (2026)
NextQuill: Causal Preference Modeling for Enhancing LLM Personalization
by: Zhao, Xiaoyan, et al.
Published: (2025)
by: Zhao, Xiaoyan, et al.
Published: (2025)
Text-like Encoding of Collaborative Information in Large Language Models for Recommendation
by: Zhang, Yang, et al.
Published: (2024)
by: Zhang, Yang, et al.
Published: (2024)
On Generative Agents in Recommendation
by: Zhang, An, et al.
Published: (2023)
by: Zhang, An, et al.
Published: (2023)
NextMem: Towards Latent Factual Memory for LLM-based Agents
by: Zhang, Zeyu, et al.
Published: (2026)
by: Zhang, Zeyu, et al.
Published: (2026)
Causal Distillation for Alleviating Performance Heterogeneity in Recommender Systems
by: Zhang, Shengyu, et al.
Published: (2024)
by: Zhang, Shengyu, et al.
Published: (2024)
LLM2Rec: Large Language Models Are Powerful Embedding Models for Sequential Recommendation
by: He, Yingzhi, et al.
Published: (2025)
by: He, Yingzhi, et al.
Published: (2025)
A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems
by: Bao, Keqin, et al.
Published: (2023)
by: Bao, Keqin, et al.
Published: (2023)
Preliminary Study on Incremental Learning for Large Language Model-based Recommender Systems
by: Shi, Tianhao, et al.
Published: (2023)
by: Shi, Tianhao, et al.
Published: (2023)
Exact and Efficient Unlearning for Large Language Model-based Recommendation
by: Hu, Zhiyu, et al.
Published: (2024)
by: Hu, Zhiyu, et al.
Published: (2024)
Agentic Feedback Loop Modeling Improves Recommendation and User Simulation
by: Cai, Shihao, et al.
Published: (2024)
by: Cai, Shihao, et al.
Published: (2024)
A Survey of Generative Search and Recommendation in the Era of Large Language Models
by: Li, Yongqi, et al.
Published: (2024)
by: Li, Yongqi, et al.
Published: (2024)
K-order Ranking Preference Optimization for Large Language Models
by: Cai, Shihao, et al.
Published: (2025)
by: Cai, Shihao, et al.
Published: (2025)
Language Representations Can be What Recommenders Need: Findings and Potentials
by: Sheng, Leheng, et al.
Published: (2024)
by: Sheng, Leheng, et al.
Published: (2024)
Similar Items
-
Leveraging Memory Retrieval to Enhance LLM-based Generative Recommendation
by: Wang, Chengbing, et al.
Published: (2024) -
Prospect Personalized Recommendation on Large Language Model-based Agent Platform
by: Zhang, Jizhi, et al.
Published: (2024) -
Heterogeneous User Modeling for LLM-based Recommendation
by: Bao, Honghui, et al.
Published: (2025) -
Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation
by: Bao, Keqin, et al.
Published: (2024) -
Data-efficient Fine-tuning for LLM-based Recommendation
by: Lin, Xinyu, et al.
Published: (2024)