Scaling Sparse and Dense Retrieval in Decoder-Only LLMs
Fuente:
arXiv
Saved in:
| Main Authors: | Zeng, Hansi, Killingback, Julian, Zamani, Hamed |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Hypencoder: Hypernetworks for Information Retrieval
by: Killingback, Julian, et al.
Published: (2025)
by: Killingback, Julian, et al.
Published: (2025)
Benchmarking Information Retrieval Models on Complex Retrieval Tasks
by: Killingback, Julian, et al.
Published: (2025)
by: Killingback, Julian, et al.
Published: (2025)
Scaling Laws for Embedding Dimension in Information Retrieval
by: Killingback, Julian, et al.
Published: (2026)
by: Killingback, Julian, et al.
Published: (2026)
Planning Ahead in Generative Retrieval: Guiding Autoregressive Generation through Simultaneous Decoding
by: Zeng, Hansi, et al.
Published: (2024)
by: Zeng, Hansi, et al.
Published: (2024)
A Unified Model and Document Representation for On-Device Retrieval-Augmented Generation
by: Killingback, Julian, et al.
Published: (2026)
by: Killingback, Julian, et al.
Published: (2026)
ExPerT: Effective and Explainable Evaluation of Personalized Long-Form Text Generation
by: Salemi, Alireza, et al.
Published: (2025)
by: Salemi, Alireza, et al.
Published: (2025)
TARSE: Test-Time Adaptation via Retrieval of Skills and Experience for Reasoning Agents
by: Wang, Junda, et al.
Published: (2026)
by: Wang, Junda, et al.
Published: (2026)
ProCIS: A Benchmark for Proactive Retrieval in Conversations
by: Samarinas, Chris, et al.
Published: (2024)
by: Samarinas, Chris, et al.
Published: (2024)
Evaluating Retrieval Quality in Retrieval-Augmented Generation
by: Salemi, Alireza, et al.
Published: (2024)
by: Salemi, Alireza, et al.
Published: (2024)
CoSearch: Joint Training of Reasoning and Document Ranking via Reinforcement Learning for Agentic Search
by: Zeng, Hansi, et al.
Published: (2026)
by: Zeng, Hansi, et al.
Published: (2026)
Decoding Dense Embeddings: Sparse Autoencoders for Interpreting and Discretizing Dense Retrieval
by: Park, Seongwan, et al.
Published: (2025)
by: Park, Seongwan, et al.
Published: (2025)
Uncertainty Quantification for Retrieval-Augmented Reasoning
by: Soudani, Heydar, et al.
Published: (2025)
by: Soudani, Heydar, et al.
Published: (2025)
Interactions with Generative Information Retrieval Systems
by: Aliannejadi, Mohammad, et al.
Published: (2024)
by: Aliannejadi, Mohammad, et al.
Published: (2024)
Learning to Rank for Multiple Retrieval-Augmented Models through Iterative Utility Maximization
by: Salemi, Alireza, et al.
Published: (2024)
by: Salemi, Alireza, et al.
Published: (2024)
Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
by: Jin, Bowen, et al.
Published: (2025)
by: Jin, Bowen, et al.
Published: (2025)
Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models
by: Salemi, Alireza, et al.
Published: (2024)
by: Salemi, Alireza, et al.
Published: (2024)
Plan-and-Refine: Diverse and Comprehensive Retrieval-Augmented Generation
by: Salemi, Alireza, et al.
Published: (2025)
by: Salemi, Alireza, et al.
Published: (2025)
Scaling Laws for Cross-Encoder Reranking
by: Seetharaman, Rahul, et al.
Published: (2026)
by: Seetharaman, Rahul, et al.
Published: (2026)
Optimization Methods for Personalizing Large Language Models through Retrieval Augmentation
by: Salemi, Alireza, et al.
Published: (2024)
by: Salemi, Alireza, et al.
Published: (2024)
Stochastic RAG: End-to-End Retrieval-Augmented Generation through Expected Utility Maximization
by: Zamani, Hamed, et al.
Published: (2024)
by: Zamani, Hamed, et al.
Published: (2024)
Interpret and Control Dense Retrieval with Sparse Latent Features
by: Kang, Hao, et al.
Published: (2024)
by: Kang, Hao, et al.
Published: (2024)
CIIR@LiveRAG 2025: Optimizing Multi-Agent Retrieval Augmented Generation through Self-Training
by: Salemi, Alireza, et al.
Published: (2025)
by: Salemi, Alireza, et al.
Published: (2025)
On the Scaling of Robustness and Effectiveness in Dense Retrieval
by: Liu, Yu-An, et al.
Published: (2025)
by: Liu, Yu-An, et al.
Published: (2025)
Can Instructed Retrieval Models Really Support Exploration?
by: Maheshwari, Piyush, et al.
Published: (2026)
by: Maheshwari, Piyush, et al.
Published: (2026)
Leveraging Decoder Architectures for Learned Sparse Retrieval
by: Qiao, Jingfen, et al.
Published: (2025)
by: Qiao, Jingfen, et al.
Published: (2025)
LSTM-based Selective Dense Text Retrieval Guided by Sparse Lexical Retrieval
by: Yang, Yingrui, et al.
Published: (2025)
by: Yang, Yingrui, et al.
Published: (2025)
Leveraging LLMs for Unsupervised Dense Retriever Ranking
by: Khramtsova, Ekaterina, et al.
Published: (2024)
by: Khramtsova, Ekaterina, et al.
Published: (2024)
Truncated Step-Level Sampling with Process Rewards for Retrieval-Augmented Reasoning
by: Samarinas, Chris, et al.
Published: (2026)
by: Samarinas, Chris, et al.
Published: (2026)
Operational Advice for Dense and Sparse Retrievers: HNSW, Flat, or Inverted Indexes?
by: Lin, Jimmy
Published: (2024)
by: Lin, Jimmy
Published: (2024)
Future of Information Retrieval Research in the Age of Generative AI
by: Allan, James, et al.
Published: (2024)
by: Allan, James, et al.
Published: (2024)
Efficient and Effective Retrieval of Dense-Sparse Hybrid Vectors using Graph-based Approximate Nearest Neighbor Search
by: Zhang, Haoyu, et al.
Published: (2024)
by: Zhang, Haoyu, et al.
Published: (2024)
ScalingNote: Scaling up Retrievers with Large Language Models for Real-World Dense Retrieval
by: Huang, Suyuan, et al.
Published: (2024)
by: Huang, Suyuan, et al.
Published: (2024)
Open-Ended and Knowledge-Intensive Video Question Answering
by: Alam, Md Zarif Ul, et al.
Published: (2025)
by: Alam, Md Zarif Ul, et al.
Published: (2025)
Scaling Laws For Dense Retrieval
by: Fang, Yan, et al.
Published: (2024)
by: Fang, Yan, et al.
Published: (2024)
Learning to Reason for Multi-Step Retrieval of Personal Context in Personalized Question Answering
by: Amirizaniani, Maryam, et al.
Published: (2026)
by: Amirizaniani, Maryam, et al.
Published: (2026)
Critic-R: Improving Agentic Search using Instruction-tuned Retrievers with Natural Language Introspective Feedback
by: Alam, Md Zarif Ul, et al.
Published: (2026)
by: Alam, Md Zarif Ul, et al.
Published: (2026)
Distillation and Refinement of Reasoning in Small Language Models for Document Re-ranking
by: Samarinas, Chris, et al.
Published: (2025)
by: Samarinas, Chris, et al.
Published: (2025)
Sparse Meets Dense: A Hybrid Approach to Enhance Scientific Document Retrieval
by: Mandikal, Priyanka, et al.
Published: (2024)
by: Mandikal, Priyanka, et al.
Published: (2024)
Improving User Privacy in Personalized Generation: Client-Side Retrieval-Augmented Modification of Server-Side Generated Speculations
by: Salemi, Alireza, et al.
Published: (2026)
by: Salemi, Alireza, et al.
Published: (2026)
Sparse and Dense Retrievers Learn Better Together: Joint Sparse-Dense Optimization for Text-Image Retrieval
by: Song, Jonghyun, et al.
Published: (2025)
by: Song, Jonghyun, et al.
Published: (2025)
Similar Items
-
Hypencoder: Hypernetworks for Information Retrieval
by: Killingback, Julian, et al.
Published: (2025) -
Benchmarking Information Retrieval Models on Complex Retrieval Tasks
by: Killingback, Julian, et al.
Published: (2025) -
Scaling Laws for Embedding Dimension in Information Retrieval
by: Killingback, Julian, et al.
Published: (2026) -
Planning Ahead in Generative Retrieval: Guiding Autoregressive Generation through Simultaneous Decoding
by: Zeng, Hansi, et al.
Published: (2024) -
A Unified Model and Document Representation for On-Device Retrieval-Augmented Generation
by: Killingback, Julian, et al.
Published: (2026)