Towards Efficient and Effective Unlearning of Large Language Models for Recommendation
Fuente:
arXiv
Saved in:
| Main Authors: | Wang, Hangyu, Lin, Jianghao, Chen, Bo, Yang, Yang, Tang, Ruiming, Zhang, Weinan, Yu, Yong |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations
by: Xi, Yunjia, et al.
Published: (2026)
by: Xi, Yunjia, et al.
Published: (2026)
FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction
by: Wang, Hangyu, et al.
Published: (2023)
by: Wang, Hangyu, et al.
Published: (2023)
Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
by: Shan, Rong, et al.
Published: (2025)
by: Shan, Rong, et al.
Published: (2025)
Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation
by: Zhu, Jiachen, et al.
Published: (2024)
by: Zhu, Jiachen, et al.
Published: (2024)
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation
by: Du, Kounianhua, et al.
Published: (2024)
by: Du, Kounianhua, et al.
Published: (2024)
ReLLa: Retrieval-enhanced Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
by: Lin, Jianghao, et al.
Published: (2023)
by: Lin, Jianghao, et al.
Published: (2023)
An Automatic Graph Construction Framework based on Large Language Models for Recommendation
by: Shan, Rong, et al.
Published: (2024)
by: Shan, Rong, et al.
Published: (2024)
ClickPrompt: CTR Models are Strong Prompt Generators for Adapting Language Models to CTR Prediction
by: Lin, Jianghao, et al.
Published: (2023)
by: Lin, Jianghao, et al.
Published: (2023)
How Can Recommender Systems Benefit from Large Language Models: A Survey
by: Lin, Jianghao, et al.
Published: (2023)
by: Lin, Jianghao, et al.
Published: (2023)
Learning Structure and Knowledge Aware Representation with Large Language Models for Concept Recommendation
by: Li, Qingyao, et al.
Published: (2024)
by: Li, Qingyao, et al.
Published: (2024)
Large Language Models Make Sample-Efficient Recommender Systems
by: Lin, Jianghao, et al.
Published: (2024)
by: Lin, Jianghao, et al.
Published: (2024)
LIBER: Lifelong User Behavior Modeling Based on Large Language Models
by: Zhu, Chenxu, et al.
Published: (2024)
by: Zhu, Chenxu, et al.
Published: (2024)
MemoCRS: Memory-enhanced Sequential Conversational Recommender Systems with Large Language Models
by: Xi, Yunjia, et al.
Published: (2024)
by: Xi, Yunjia, et al.
Published: (2024)
MuonRec: Shifting the Optimizer Paradigm Beyond Adam in Scalable Generative Recommendation
by: Shan, Rong, et al.
Published: (2026)
by: Shan, Rong, et al.
Published: (2026)
Play to Your Strengths: Collaborative Intelligence of Conventional Recommender Models and Large Language Models
by: Xi, Yunjia, et al.
Published: (2024)
by: Xi, Yunjia, et al.
Published: (2024)
A Survey on Diffusion Models for Recommender Systems
by: Lin, Jianghao, et al.
Published: (2024)
by: Lin, Jianghao, et al.
Published: (2024)
ELCoRec: Enhance Language Understanding with Co-Propagation of Numerical and Categorical Features for Recommendation
by: Chen, Jizheng, et al.
Published: (2024)
by: Chen, Jizheng, et al.
Published: (2024)
Efficient and Deployable Knowledge Infusion for Open-World Recommendations via Large Language Models
by: Xi, Yunjia, et al.
Published: (2024)
by: Xi, Yunjia, et al.
Published: (2024)
Retrieval-Oriented Knowledge for Click-Through Rate Prediction
by: Liu, Huanshuo, et al.
Published: (2024)
by: Liu, Huanshuo, et al.
Published: (2024)
Generative Representational Learning of Foundation Models for Recommendation
by: Zhou, Zheli, et al.
Published: (2025)
by: Zhou, Zheli, et al.
Published: (2025)
Efficiency Unleashed: Inference Acceleration for LLM-based Recommender Systems with Speculative Decoding
by: Xi, Yunjia, et al.
Published: (2024)
by: Xi, Yunjia, et al.
Published: (2024)
FINED: Feed Instance-Wise Information Need with Essential and Disentangled Parametric Knowledge from the Past
by: Du, Kounianhua, et al.
Published: (2024)
by: Du, Kounianhua, et al.
Published: (2024)
DynaTree: Dynamic Agentic Retrieval Tree for Time-Sensitive News Retrieval
by: Qi, Siyuan, et al.
Published: (2026)
by: Qi, Siyuan, et al.
Published: (2026)
Retrieval-Augmented Process Reward Model for Generalizable Mathematical Reasoning
by: Zhu, Jiachen, et al.
Published: (2025)
by: Zhu, Jiachen, et al.
Published: (2025)
M-scan: A Multi-Scenario Causal-driven Adaptive Network for Recommendation
by: Zhu, Jiachen, et al.
Published: (2024)
by: Zhu, Jiachen, et al.
Published: (2024)
MassTool: A Multi-Task Search-Based Tool Retrieval Framework for Large Language Models
by: Lin, Jianghao, et al.
Published: (2025)
by: Lin, Jianghao, et al.
Published: (2025)
Agentic Information Retrieval
by: Zhang, Weinan, et al.
Published: (2024)
by: Zhang, Weinan, et al.
Published: (2024)
Retrieval and Distill: A Temporal Data Shift-Free Paradigm for Online Recommendation System
by: Zheng, Lei, et al.
Published: (2024)
by: Zheng, Lei, et al.
Published: (2024)
Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models
by: Huang, Chengkai, et al.
Published: (2025)
by: Huang, Chengkai, et al.
Published: (2025)
GR-LLMs: Recent Advances in Generative Recommendation Based on Large Language Models
by: Yang, Zhen, et al.
Published: (2025)
by: Yang, Zhen, et al.
Published: (2025)
Enhancing ID-based Recommendation with Large Language Models
by: Chen, Lei, et al.
Published: (2024)
by: Chen, Lei, et al.
Published: (2024)
Enhancing Sequential Recommender with Large Language Models for Joint Video and Comment Recommendation
by: Zheng, Bowen, et al.
Published: (2024)
by: Zheng, Bowen, et al.
Published: (2024)
BEAR: Towards Beam-Search-Aware Optimization for Recommendation with Large Language Models
by: Yang, Weiqin, et al.
Published: (2026)
by: Yang, Weiqin, et al.
Published: (2026)
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
by: Jia, Pengyue, et al.
Published: (2024)
by: Jia, Pengyue, et al.
Published: (2024)
RecMind: Large Language Model Powered Agent For Recommendation
by: Wang, Yancheng, et al.
Published: (2023)
by: Wang, Yancheng, et al.
Published: (2023)
A Survey on Recommendation Unlearning: Fundamentals, Taxonomy, Evaluation, and Open Questions
by: Li, Yuyuan, et al.
Published: (2024)
by: Li, Yuyuan, et al.
Published: (2024)
Superplatforms Have to Attack AI Agents
by: Lin, Jianghao, et al.
Published: (2025)
by: Lin, Jianghao, et al.
Published: (2025)
Simulating Filter Bubble on Short-video Recommender System with Large Language Model Agents
by: Sukiennik, Nicholas, et al.
Published: (2025)
by: Sukiennik, Nicholas, et al.
Published: (2025)
Sell It Before You Make It: Revolutionizing E-Commerce with Personalized AI-Generated Items
by: Lin, Jianghao, et al.
Published: (2025)
by: Lin, Jianghao, et al.
Published: (2025)
Mitigating Propensity Bias of Large Language Models for Recommender Systems
by: Zhang, Guixian, et al.
Published: (2024)
by: Zhang, Guixian, et al.
Published: (2024)
Similar Items
-
Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations
by: Xi, Yunjia, et al.
Published: (2026) -
FLIP: Fine-grained Alignment between ID-based Models and Pretrained Language Models for CTR Prediction
by: Wang, Hangyu, et al.
Published: (2023) -
Full-Stack Optimized Large Language Models for Lifelong Sequential Behavior Comprehension in Recommendation
by: Shan, Rong, et al.
Published: (2025) -
Lifelong Personalized Low-Rank Adaptation of Large Language Models for Recommendation
by: Zhu, Jiachen, et al.
Published: (2024) -
DisCo: Towards Harmonious Disentanglement and Collaboration between Tabular and Semantic Space for Recommendation
by: Du, Kounianhua, et al.
Published: (2024)