Saved in:
| Main Authors: | Lu, Yusheng, Du, Zhaocheng, Li, Xiangyang, Jia, Pengyue, Wang, Yejing, Liu, Weiwen, Wang, Yichao, Guo, Huifeng, Tang, Ruiming, Dong, Zhenhua, Duan, Yongrui, Zhao, Xiangyu |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2408.06577 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
by: Jia, Pengyue, et al.
Published: (2024)
by: Jia, Pengyue, et al.
Published: (2024)
SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval
by: Li, Xiaopeng, et al.
Published: (2024)
by: Li, Xiaopeng, et al.
Published: (2024)
SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systems
by: Jia, Pengyue, et al.
Published: (2024)
by: Jia, Pengyue, et al.
Published: (2024)
SampleLLM: Optimizing Tabular Data Synthesis in Recommendations
by: Gao, Jingtong, et al.
Published: (2025)
by: Gao, Jingtong, et al.
Published: (2025)
Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark
by: Li, Xiaopeng, et al.
Published: (2024)
by: Li, Xiaopeng, et al.
Published: (2024)
Process vs. Outcome Reward: Which is Better for Agentic RAG Reinforcement Learning
by: Zhang, Wenlin, et al.
Published: (2025)
by: Zhang, Wenlin, et al.
Published: (2025)
LSRP: A Leader-Subordinate Retrieval Framework for Privacy-Preserving Cloud-Device Collaboration
by: Zhang, Yingyi, et al.
Published: (2025)
by: Zhang, Yingyi, et al.
Published: (2025)
Personalized Deep Research: A User-Centric Framework, Dataset, and Hybrid Evaluation for Knowledge Discovery
by: Li, Xiaopeng, et al.
Published: (2026)
by: Li, Xiaopeng, et al.
Published: (2026)
Exploring Recommender System Evaluation: A Multi-Modal User Agent Framework for A/B Testing
by: Zhang, Wenlin, et al.
Published: (2026)
by: Zhang, Wenlin, et al.
Published: (2026)
A Survey of Personalization: From RAG to Agent
by: Li, Xiaopeng, et al.
Published: (2025)
by: Li, Xiaopeng, et al.
Published: (2025)
LLM4Rerank: LLM-based Auto-Reranking Framework for Recommendations
by: Gao, Jingtong, et al.
Published: (2024)
by: Gao, Jingtong, et al.
Published: (2024)
LLM4MSR: An LLM-Enhanced Paradigm for Multi-Scenario Recommendation
by: Wang, Yuhao, et al.
Published: (2024)
by: Wang, Yuhao, et al.
Published: (2024)
Joint Modeling in Recommendations: A Survey
by: Zhao, Xiangyu, et al.
Published: (2025)
by: Zhao, Xiangyu, et al.
Published: (2025)
A Unified Framework for Multi-Domain CTR Prediction via Large Language Models
by: Fu, Zichuan, et al.
Published: (2023)
by: Fu, Zichuan, et al.
Published: (2023)
LLMTreeRec: Unleashing the Power of Large Language Models for Cold-Start Recommendations
by: Zhang, Wenlin, et al.
Published: (2024)
by: Zhang, Wenlin, et al.
Published: (2024)
Retrievable Domain-Sensitive Feature Memory for Multi-Domain Recommendation
by: Zhao, Yuang, et al.
Published: (2024)
by: Zhao, Yuang, et al.
Published: (2024)
HAMUR: Hyper Adapter for Multi-Domain Recommendation
by: Li, Xiaopeng, et al.
Published: (2023)
by: Li, Xiaopeng, et al.
Published: (2023)
Deep Research: A Survey of Autonomous Research Agents
by: Zhang, Wenlin, et al.
Published: (2025)
by: Zhang, Wenlin, et al.
Published: (2025)
No One Left Behind: How to Exploit the Incomplete and Skewed Multi-Label Data for Conversion Rate Prediction
by: Jia, Qinglin, et al.
Published: (2025)
by: Jia, Qinglin, et al.
Published: (2025)
CELA: Cost-Efficient Language Model Alignment for CTR Prediction
by: Wang, Xingmei, et al.
Published: (2024)
by: Wang, Xingmei, et al.
Published: (2024)
Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrieval
by: Zhang, Yingyi, et al.
Published: (2025)
by: Zhang, Yingyi, et al.
Published: (2025)
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era
by: Chen, Bo, et al.
Published: (2024)
by: Chen, Bo, et al.
Published: (2024)
MTRec: Learning to Align with User Preferences via Mental Reward Models
by: Zhao, Mengchen, et al.
Published: (2025)
by: Zhao, Mengchen, et al.
Published: (2025)
Evaluating Conversational Recommender Systems via Large Language Models: A User-Centric Framework
by: Chen, Nuo, et al.
Published: (2025)
by: Chen, Nuo, et al.
Published: (2025)
LLM-EDT: Large Language Model Enhanced Cross-domain Sequential Recommendation with Dual-phase Training
by: Liu, Ziwei, et al.
Published: (2025)
by: Liu, Ziwei, et al.
Published: (2025)
Bridging Relevance and Reasoning: Rationale Distillation in Retrieval-Augmented Generation
by: Jia, Pengyue, et al.
Published: (2024)
by: Jia, Pengyue, et al.
Published: (2024)
From Human Memory to AI Memory: A Survey on Memory Mechanisms in the Era of LLMs
by: Wu, Yaxiong, et al.
Published: (2025)
by: Wu, Yaxiong, et al.
Published: (2025)
Evoking User Memory: Personalizing LLM via Recollection-Familiarity Adaptive Retrieval
by: Zhang, Yingyi, et al.
Published: (2026)
by: Zhang, Yingyi, et al.
Published: (2026)
TayFCS: Towards Light Feature Combination Selection for Deep Recommender Systems
by: Wang, Xianquan, et al.
Published: (2025)
by: Wang, Xianquan, et al.
Published: (2025)
FairFS: Addressing Deep Feature Selection Biases for Recommender System
by: Wang, Xianquan, et al.
Published: (2026)
by: Wang, Xianquan, et al.
Published: (2026)
Inference Computation Scaling for Feature Augmentation in Recommendation Systems
by: Liu, Weihao, et al.
Published: (2025)
by: Liu, Weihao, et al.
Published: (2025)
RecSys Arena: Pair-wise Recommender System Evaluation with Large Language Models
by: Wu, Zhuo, et al.
Published: (2024)
by: Wu, Zhuo, et al.
Published: (2024)
D2K: Turning Historical Data into Retrievable Knowledge for Recommender Systems
by: Qin, Jiarui, et al.
Published: (2024)
by: Qin, Jiarui, et al.
Published: (2024)
AIE: Auction Information Enhanced Framework for CTR Prediction in Online Advertising
by: Yang, Yang, et al.
Published: (2024)
by: Yang, Yang, et al.
Published: (2024)
MemSearch-o1: Empowering Large Language Models with Reasoning-Aligned Memory Growth in Agentic Search
by: Zhang, Sheng, et al.
Published: (2026)
by: Zhang, Sheng, et al.
Published: (2026)
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)
Large Language Model Enhanced Recommender Systems: A Survey
by: Liu, Qidong, et al.
Published: (2024)
by: Liu, Qidong, et al.
Published: (2024)
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)
Embedding Compression in Recommender Systems: A Survey
by: Li, Shiwei, et al.
Published: (2024)
by: Li, Shiwei, et al.
Published: (2024)
To Search or Not to Search: Aligning the Decision Boundary of Deep Search Agents via Causal Intervention
by: Zhang, Wenlin, et al.
Published: (2026)
by: Zhang, Wenlin, et al.
Published: (2026)
Similar Items
-
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
by: Jia, Pengyue, et al.
Published: (2024) -
SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval
by: Li, Xiaopeng, et al.
Published: (2024) -
SELF: Surrogate-light Feature Selection with Large Language Models in Deep Recommender Systems
by: Jia, Pengyue, et al.
Published: (2024) -
SampleLLM: Optimizing Tabular Data Synthesis in Recommendations
by: Gao, Jingtong, et al.
Published: (2025) -
Scenario-Wise Rec: A Multi-Scenario Recommendation Benchmark
by: Li, Xiaopeng, et al.
Published: (2024)