Copertina

High Fidelity Textual User Representation over Heterogeneous Sources via Reinforcement Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Arora, Rajat, Tao, Ye, Shen, Jianqiang, Liu, Ping, Wu, Muchen, Shen, Qianqi, Le, Benjamin, Borisyuk, Fedor, Wu, Jingwei, Zhang, Wenjing
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Information Retrieval Artificial Intelligence Computation and Language Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Powering Job Search at Scale: LLM-Enhanced Query Understanding in Job Matching Systems
di: Liu, Ping, et al.
Pubblicazione: (2025)

Policy-Grounded Dynamic Facet Suggestions for Job Search
di: Xu, Dan, et al.
Pubblicazione: (2026)

Learning to Retrieve for Job Matching
di: Shen, Jianqiang, et al.
Pubblicazione: (2024)

Efficient user history modeling with amortized inference for deep learning recommendation models
di: Hertel, Lars, et al.
Pubblicazione: (2024)

FedUTR: Federated Recommendation with Augmented Universal Textual Representation for Sparse Interaction Scenarios
di: Fu, Kang, et al.
Pubblicazione: (2026)

TEARS: Textual Representations for Scrutable Recommendations
di: Penaloza, Emiliano, et al.
Pubblicazione: (2024)

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models
di: Shi, Wentao, et al.
Pubblicazione: (2025)

MultiSlot ReRanker: A Generic Model-based Re-Ranking Framework in Recommendation Systems
di: Xiao, Qiang Charles, et al.
Pubblicazione: (2024)

Faithful Temporal Question Answering over Heterogeneous Sources
di: Jia, Zhen, et al.
Pubblicazione: (2024)

MixLM: High-Throughput and Effective LLM Ranking via Text-Embedding Mix-Interaction
di: Li, Guoyao, et al.
Pubblicazione: (2025)

TRACE: A Time-Relational Approximate Cubing Engine for Fast Data Insights
di: Sivakumar, Suharsh, et al.
Pubblicazione: (2024)

Bridging Textual Profiles and Latent User Embeddings for Personalization
di: Tan, Zhaoxuan, et al.
Pubblicazione: (2026)

A Framework for Elastic Adaptation of User Multiple Intents in Sequential Recommendation
di: Wang, Zhikai, et al.
Pubblicazione: (2025)

SAGE: Scalable AI Governance & Evaluation
di: Le, Benjamin, et al.
Pubblicazione: (2026)

From Atom to Community: Structured and Evolving Agent Memory for User Behavior Modeling
di: Liao, Yuxin, et al.
Pubblicazione: (2026)

Mixture of Demonstrations for Textual Graph Understanding and Question Answering
di: Wu, Yukun, et al.
Pubblicazione: (2026)

Threat Behavior Textual Search by Attention Graph Isomorphism
di: Bae, Chanwoo, et al.
Pubblicazione: (2024)

Heterogeneous User Modeling for LLM-based Recommendation
di: Bao, Honghui, et al.
Pubblicazione: (2025)

Next-User Retrieval: Enhancing Cold-Start Recommendations via Generative Next-User Modeling
di: Lan, Yu-Ting, et al.
Pubblicazione: (2025)

Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval
di: Wu, Haolun, et al.
Pubblicazione: (2023)

Graph-based Recommendation for Sparse and Heterogeneous User Interactions
di: Bruun, Simone Borg, et al.
Pubblicazione: (2023)

Query2GMM: Learning Representation with Gaussian Mixture Model for Reasoning over Knowledge Graphs
di: Wu, Yuhan, et al.
Pubblicazione: (2023)

Accelerating the Surrogate Retraining for Poisoning Attacks against Recommender Systems
di: Wu, Yunfan, et al.
Pubblicazione: (2024)

Recency Ranking by Diversification of Result Set
di: Styskin, Andrey, et al.
Pubblicazione: (2024)

Breaking the Length Barrier: LLM-Enhanced CTR Prediction in Long Textual User Behaviors
di: Geng, Binzong, et al.
Pubblicazione: (2024)

Retention Induced Biases in a Recommendation System with Heterogeneous Users
di: Ma, Shichao
Pubblicazione: (2024)

Learning Universal User Representations Leveraging Cross-domain User Intent at Snapchat
di: Ju, Clark Mingxuan, et al.
Pubblicazione: (2025)

UNION: A Lightweight Target Representation for Efficient Zero-Shot Image-Guided Retrieval with Optional Textual Queries
di: Le, Hoang-Bao, et al.
Pubblicazione: (2025)

Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning
di: Wu, Yuhang, et al.
Pubblicazione: (2026)

LinkSAGE: Optimizing Job Matching Using Graph Neural Networks
di: Liu, Ping, et al.
Pubblicazione: (2024)

Collaborative User Prompt for Personalized Generative Recommendation
di: Ramos, Jerome, et al.
Pubblicazione: (2024)

Semantic Search At LinkedIn
di: Borisyuk, Fedor, et al.
Pubblicazione: (2026)

Towards Robust Cross-Domain Recommendation with Joint Identifiability of User Preference
di: Du, Jing, et al.
Pubblicazione: (2024)

Robust Recommender System: A Survey and Future Directions
di: Zhang, Kaike, et al.
Pubblicazione: (2023)

Integrating Visual and Textual Inputs for Searching Large-Scale Map Collections with CLIP
di: Mahowald, Jamie, et al.
Pubblicazione: (2024)

Enhancing Recommender Systems Using Textual Embeddings from Pre-trained Language Models
di: Le, Ngoc Luyen, et al.
Pubblicazione: (2025)

HGCH: A Hyperbolic Graph Convolution Network Model for Heterogeneous Collaborative Graph Recommendation
di: Zhang, Lu, et al.
Pubblicazione: (2023)

Mitigating Recommendation Biases via Group-Alignment and Global-Uniformity in Representation Learning
di: Cai, Miaomiao, et al.
Pubblicazione: (2025)

Towards Bridging Review Sparsity in Recommendation with Textual Edge Graph Representation
di: Wang, Leyao, et al.
Pubblicazione: (2025)

Learning Item Representations Directly from Multimodal Features for Effective Recommendation
di: Zhou, Xin, et al.
Pubblicazione: (2025)