Copertina

Rethinking Deep Research from the Perspective of Web Content Distribution Matching

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Yu, Zixuan, Tang, Zhenheng, Liu, Tongliang, Zhang, Chengqi, Chu, Xiaowen, Han, Bo
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	Machine Learning Information Retrieval
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

CSRec: Rethinking Sequential Recommendation from A Causal Perspective
di: Liu, Xiaoyu, et al.
Pubblicazione: (2024)

From Web Search towards Agentic Deep Research: Incentivizing Search with Reasoning Agents
di: Zhang, Weizhi, et al.
Pubblicazione: (2025)

From Scaling to Structured Expressivity: Rethinking Transformers for CTR Prediction
di: Yan, Bencheng, et al.
Pubblicazione: (2025)

Content-Agnostic Moderation for Stance-Neutral Recommendation
di: Li, Nan, et al.
Pubblicazione: (2024)

LLM-based Relevance Assessment for Web-Scale Search Evaluation at Pinterest
di: Wang, Han, et al.
Pubblicazione: (2025)

On-device Content-based Recommendation with Single-shot Embedding Pruning: A Cooperative Game Perspective
di: Tran, Hung Vinh, et al.
Pubblicazione: (2024)

OmniReview: A Large-scale Benchmark and LLM-enhanced Framework for Realistic Reviewer Recommendation
di: Huang, Yehua, et al.
Pubblicazione: (2026)

Probability Distribution Learning and Its Application in Deep Learning
di: Qi, Binchuan, et al.
Pubblicazione: (2024)

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

Evaluation on Entity Matching in Recommender Systems
di: Huang, Zihan, et al.
Pubblicazione: (2026)

An Efficient Continuous Control Perspective for Reinforcement-Learning-based Sequential Recommendation
di: Wang, Jun, et al.
Pubblicazione: (2024)

PSL: Rethinking and Improving Softmax Loss from Pairwise Perspective for Recommendation
di: Yang, Weiqin, et al.
Pubblicazione: (2024)

UDuo: Universal Dual Optimization Framework for Online Matching
di: Li, Bin, et al.
Pubblicazione: (2025)

ID Embedding as Subtle Features of Content and Structure for Multimodal Recommendation
di: Liu, Yuting, et al.
Pubblicazione: (2023)

Federated Vision-Language-Recommendation with Personalized Fusion
di: Li, Zhiwei, et al.
Pubblicazione: (2024)

Personalized Federated Collaborative Filtering: A Variational AutoEncoder Approach
di: Li, Zhiwei, et al.
Pubblicazione: (2024)

Joint Model Parameter Scaling and Universal-Domain Data Integration for E-commerce Search Ranking
di: Yu, Liren, et al.
Pubblicazione: (2026)

OptDist: Learning Optimal Distribution for Customer Lifetime Value Prediction
di: Weng, Yunpeng, et al.
Pubblicazione: (2024)

Navigating the Future of Federated Recommendation Systems with Foundation Models
di: Li, Zhiwei, et al.
Pubblicazione: (2024)

PinLanding: Content-First Keyword Landing Page Generation via Multi-Modal AI for Web-Scale Discovery
di: Zhang, Faye, et al.
Pubblicazione: (2025)

Rethinking Convolutional Networks for Attribute-Aware Sequential Recommendation
di: Elsayed, Shereen, et al.
Pubblicazione: (2026)

Hashing-Baseline: Rethinking Hashing in the Age of Pretrained Models
di: Moummad, Ilyass, et al.
Pubblicazione: (2025)

Scenario-Adaptive Fine-Grained Personalization Network: Tailoring User Behavior Representation to the Scenario Context
di: Zhang, Moyu, et al.
Pubblicazione: (2024)

MODRL-TA:A Multi-Objective Deep Reinforcement Learning Framework for Traffic Allocation in E-Commerce Search
di: Cheng, Peng, et al.
Pubblicazione: (2024)

SEGMN: A Structure-Enhanced Graph Matching Network for Graph Similarity Learning
di: Wang, Wenjun, et al.
Pubblicazione: (2024)

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

Understanding Matching Mechanisms in Cross-Encoders
di: Vast, Mathias, et al.
Pubblicazione: (2025)

Multi-Epoch learning with Data Augmentation for Deep Click-Through Rate Prediction
di: Fan, Zhongxiang, et al.
Pubblicazione: (2024)

Learning Cascade Ranking as One Network
di: Wang, Yunli, et al.
Pubblicazione: (2025)

Reconstructing Content via Collaborative Attention to Improve Multimodal Embedding Quality
di: Chen, Jiahan, et al.
Pubblicazione: (2026)

Off-Policy Evaluation and Learning for Matching Markets
di: Hayashi, Yudai, et al.
Pubblicazione: (2025)

Tree-based Focused Web Crawling with Reinforcement Learning
di: Kontogiannis, Andreas, et al.
Pubblicazione: (2021)

Beyond Static Evaluation: Rethinking the Assessment of Personalized Agent Adaptability in Information Retrieval
di: Kaur, Kirandeep, et al.
Pubblicazione: (2025)

Systematic Literature Review on Clinical Trial Eligibility Matching
di: Sharif, Muhammad Talha, et al.
Pubblicazione: (2025)

Content-based Recommendation Engine for Video Streaming Platform
di: Khadka, Puskal, et al.
Pubblicazione: (2023)

Make It Long, Keep It Fast: End-to-End 10K Long User Behavior Sequence Modeling for Billion-Scale Douyin Recommendation
di: Guan, Lin, et al.
Pubblicazione: (2025)

GNNAnatomy: Rethinking Model-Level Explanations for Graph Neural Networks
di: Lu, Hsiao-Ying, et al.
Pubblicazione: (2024)

Domain-Adaptive and Scalable Dense Retrieval for Content-Based Recommendation
di: Pandey, Mritunjay
Pubblicazione: (2026)

Revisiting Feature Interactions from the Perspective of Quadratic Neural Networks for Click-through Rate Prediction
di: Li, Honghao, et al.
Pubblicazione: (2025)

SemStruct: Contextualizing Semantic Embeddings with Structural Information for Schema Matching
di: Kang, Inwon, et al.
Pubblicazione: (2026)