Cover Image

LTRR: Learning To Rank Retrievers for LLMs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kim, To Eun, Diaz, Fernando
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Towards Fair RAG: On the Impact of Fair Ranking in Retrieval-Augmented Generation
by: Kim, To Eun, et al.
Published: (2024)

Retrieval-Enhanced Machine Learning: Synthesis and Opportunities
by: Kim, To Eun, et al.
Published: (2024)

MoR: Better Handling Diverse Queries with a Mixture of Sparse, Dense, and Human Retrievers
by: Kalra, Jushaan Singh, et al.
Published: (2025)

Mistral-SPLADE: LLMs for better Learned Sparse Retrieval
by: Doshi, Meet, et al.
Published: (2024)

Learning to Rank for Multiple Retrieval-Augmented Models through Iterative Utility Maximization
by: Salemi, Alireza, et al.
Published: (2024)

Multilingual and Domain-Agnostic Tip-of-the-Tongue Query Generation for Simulated Evaluation
by: He, Xuhong, et al.
Published: (2026)

The Role of Vocabularies in Learning Sparse Representations for Ranking
by: Kim, Hiun, et al.
Published: (2025)

Rankify: A Comprehensive Python Toolkit for Retrieval, Re-Ranking, and Retrieval-Augmented Generation
by: Abdallah, Abdelrahman, et al.
Published: (2025)

Generative Pseudo-Labeling for Pre-Ranking with LLMs
by: Bi, Junyu, et al.
Published: (2026)

When to Retrieve: Teaching LLMs to Utilize Information Retrieval Effectively
by: Labruna, Tiziano, et al.
Published: (2024)

Shifting from Ranking to Set Selection for Retrieval Augmented Generation
by: Lee, Dahyun, et al.
Published: (2025)

Redefining Retrieval Evaluation in the Era of LLMs
by: Trappolini, Giovanni, et al.
Published: (2025)

HEISIR: Hierarchical Expansion of Inverted Semantic Indexing for Training-free Retrieval of Conversational Data using LLMs
by: Kim, Sangyeop, et al.
Published: (2025)

RankRAG: Unifying Context Ranking with Retrieval-Augmented Generation in LLMs
by: Yu, Yue, et al.
Published: (2024)

Don't Retrieve, Generate: Prompting LLMs for Synthetic Training Data in Dense Retrieval
by: Sinha, Aarush
Published: (2025)

CoRank: LLM-Based Compact Reranking with Document Features for Scientific Retrieval
by: Tian, Runchu, et al.
Published: (2025)

Beyond Ranked Lists: The SARAL Framework for Cross-Lingual Document Set Retrieval
by: Agarwal, Shantanu, et al.
Published: (2025)

NEAR$^2$: A Nested Embedding Approach to Efficient Product Retrieval and Ranking
by: Qian, Shenbin, et al.
Published: (2025)

Towards Fair Rankings: Leveraging LLMs for Gender Bias Detection and Measurement
by: Mousavian, Maryam, et al.
Published: (2025)

Study on LLMs for Promptagator-Style Dense Retriever Training
by: Gwon, Daniel, et al.
Published: (2025)

GME: Improving Universal Multimodal Retrieval by Multimodal LLMs
by: Zhang, Xin, et al.
Published: (2024)

Tip of the Tongue Query Elicitation for Simulated Evaluation
by: He, Yifan, et al.
Published: (2025)

Hybrid Retrieval for COVID-19 Literature: Comparing Rank Fusion and Projection Fusion with Diversity Reranking
by: Prajapati, Harishkumar Kishorkumar
Published: (2026)

Do Large Language Models Rank Fairly? An Empirical Study on the Fairness of LLMs as Rankers
by: Wang, Yuan, et al.
Published: (2024)

Towards a Search Engine for Machines: Unified Ranking for Multiple Retrieval-Augmented Large Language Models
by: Salemi, Alireza, et al.
Published: (2024)

CoRanking: Collaborative Ranking with Small and Large Ranking Agents
by: Liu, Wenhan, et al.
Published: (2025)

Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs
by: Ge, Ziyu, et al.
Published: (2025)

Grounding Arabic LLMs in the Doha Historical Dictionary: Retrieval-Augmented Understanding of Quran and Hadith
by: Eltanbouly, Somaya, et al.
Published: (2026)

No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Users
by: Hu, Mengxuan, et al.
Published: (2024)

STELLA: Self-Reflective Terminology-Aware Framework for Building an Aerospace Information Retrieval Benchmark
by: Kim, Bongmin
Published: (2026)

Enhancing Automatic Term Extraction with Large Language Models via Syntactic Retrieval
by: Chun, Yongchan, et al.
Published: (2025)

Adversarial Attacks against Neural Ranking Models via In-Context Learning
by: Bigdeli, Amin, et al.
Published: (2025)

Optimizing Retrieval for RAG via Reinforcement Learning
by: Zhou, Jiawei, et al.
Published: (2025)

Align then Train: Efficient Retrieval Adapter Learning
by: Maekawa, Seiji, et al.
Published: (2026)

On the Challenges and Opportunities of Learned Sparse Retrieval for Code
by: Lupart, Simon, et al.
Published: (2026)

Agentic-R: Learning to Retrieve for Agentic Search
by: Liu, Wenhan, et al.
Published: (2026)

RRAML: Reinforced Retrieval Augmented Machine Learning
by: Bacciu, Andrea, et al.
Published: (2023)

Ask Optimal Questions: Aligning Large Language Models with Retriever's Preference in Conversation
by: Yoon, Chanwoong, et al.
Published: (2024)

Scientific Paper Retrieval with LLM-Guided Semantic-Based Ranking
by: Zhang, Yunyi, et al.
Published: (2025)

Rank1: Test-Time Compute for Reranking in Information Retrieval
by: Weller, Orion, et al.
Published: (2025)