Cover Image

CSRv2: Unlocking Ultra-Sparse Embeddings

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Guo, Lixuan, Wang, Yifei, Wen, Tiansheng, Wang, Yifan, Feng, Aosong, Chen, Bo, Jegelka, Stefanie, You, Chenyu
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Artificial Intelligence Information Retrieval Information Theory
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

No More K-means: Single-Stage Sparse Coding for Efficient Multi-Vector Retrieval
by: Guo, Lixuan, et al.
Published: (2026)

Route Experts by Sequence, not by Token
by: Wen, Tiansheng, et al.
Published: (2025)

Beyond Matryoshka: Revisiting Sparse Coding for Adaptive Representation
by: Wen, Tiansheng, et al.
Published: (2025)

Embedding in Recommender Systems: A Survey
by: Wang, Maolin, et al.
Published: (2023)

Concurrent Brainstorming & Hypothesis Satisfying: An Iterative Framework for Enhanced Retrieval-Augmented Generation (R2CBR3H-SR)
by: Shahmansoori, Arash
Published: (2024)

Evaluating Embedding Models and Pipeline Optimization for AI Search Quality
by: Zhong, Philip, et al.
Published: (2025)

InBox: Recommendation with Knowledge Graph using Interest Box Embedding
by: Xu, Zezhong, et al.
Published: (2024)

Citation-Driven Multi-View Training for Patent Embeddings: QaECTER and Sophia-Bench
by: Djemmal, Younes, et al.
Published: (2026)

Unlocking the Potential of Large Language Models for Explainable Recommendations
by: Luo, Yucong, et al.
Published: (2023)

Training-free Adjustable Polynomial Graph Filtering for Ultra-fast Multimodal Recommendation
by: Roh, Yu-Seung, et al.
Published: (2025)

Coarse-to-Fine Lightweight Meta-Embedding for ID-Based Recommendation
by: Wang, Yang, et al.
Published: (2025)

Empowering Denoising Sequential Recommendation with Large Language Model Embeddings
by: Wu, Tongzhou, et al.
Published: (2025)

Modernizing Facebook Scoped Search: Keyword and Embedding Hybrid Retrieval with LLM Evaluation
by: Su, Yongye, et al.
Published: (2025)

Why not Collaborative Filtering in Dual View? Bridging Sparse and Dense Models
by: Guo, Hanze, et al.
Published: (2026)

XGraphRAG: Interactive Visual Analysis for Graph-based Retrieval-Augmented Generation
by: Wang, Ke, et al.
Published: (2025)

Sparse Meets Dense: Unified Generative Recommendations with Cascaded Sparse-Dense Representations
by: Yang, Yuhao, et al.
Published: (2025)

Towards Competitive Search Relevance For Inference-Free Learned Sparse Retrievers
by: Geng, Zhichao, et al.
Published: (2024)

ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
by: Jia, Pengyue, et al.
Published: (2024)

Empowering Large Language Model for Sequential Recommendation via Multimodal Embeddings and Semantic IDs
by: Wang, Yuhao, et al.
Published: (2025)

pEBR: A Probabilistic Approach to Embedding Based Retrieval
by: Zhang, Han, et al.
Published: (2024)

Leveraging Evidence-Guided LLMs to Enhance Trustworthy Depression Diagnosis
by: Yuan, Yining, et al.
Published: (2025)

Training Sparse Mixture Of Experts Text Embedding Models
by: Nussbaum, Zach, et al.
Published: (2025)

SearchRAG: Can Search Engines Be Helpful for LLM-based Medical Question Answering?
by: Shi, Yucheng, et al.
Published: (2025)

Towards Sustainable Growth: A Multi-Value-Aware Retrieval Framework for E-Commerce Search
by: Wang, Yifan, et al.
Published: (2026)

Next Point-of-interest (POI) Recommendation Model Based on Multi-modal Spatio-temporal Context Feature Embedding
by: Zhang, Lingyu, et al.
Published: (2025)

Pairwise Judgment Formulation for Semantic Embedding Model in Web Search
by: Hong, Mengze, et al.
Published: (2024)

Toward a Theory of Hierarchical Memory for Language Agents
by: Talebirad, Yashar, et al.
Published: (2026)

LLMRS: Unlocking Potentials of LLM-Based Recommender Systems for Software Purchase
by: John, Angela, et al.
Published: (2024)

A Recommendation Model Utilizing Separation Embedding and Self-Attention for Feature Mining
by: Liu, Wenyi, et al.
Published: (2024)

Popularity-Aware Alignment and Contrast for Mitigating Popularity Bias
by: Cai, Miaomiao, et al.
Published: (2024)

Disaggregating Embedding Recommendation Systems with FlexEMR
by: Huang, Yibo, et al.
Published: (2024)

When SparseMoE Meets Noisy Interactions: An Ensemble View on Denoising Recommendation
by: Chen, Weipu, et al.
Published: (2024)

Learn Before Represent: Bridging Generative and Contrastive Learning for Domain-Specific LLM Embeddings
by: Liang, Xiaoyu, et al.
Published: (2026)

InteractiveSurvey: An LLM-based Personalized and Interactive Survey Paper Generation System
by: Wen, Zhiyuan, et al.
Published: (2025)

LLM4DSR: Leveraging Large Language Model for Denoising Sequential Recommendation
by: Wang, Bohao, et al.
Published: (2024)

Unlocking Legal Knowledge with Multi-Layered Embedding-Based Retrieval
by: Lima, João Alberto de Oliveira
Published: (2024)

TME-PSR: Time-aware, Multi-interest, and Explanation Personalization for Sequential Recommendation
by: Wang, Qingzhuo, et al.
Published: (2026)

The Ranking Blind Spot: Decision Hijacking in LLM-based Text Ranking
by: Qian, Yaoyao, et al.
Published: (2025)

Action is All You Need: Dual-Flow Generative Ranking Network for Recommendation
by: Guo, Hao, et al.
Published: (2025)

LaPuda: LLM-Enabled Policy-Based Query Optimizer for Multi-modal Data
by: Wang, Yifan, et al.
Published: (2024)