Cover Image

Hybrid Pooling with LLMs via Relevance Context Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Otero, David, Parapar, Javier
Format:	Preprint
Published:	2026
Subjects:	Information Retrieval
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LLM-Assisted Pseudo-Relevance Feedback
by: Otero, David, et al.
Published: (2026)

Limitations of Automatic Relevance Assessments with Large Language Models for Fair and Reliable Retrieval Evaluation
by: Otero, David, et al.
Published: (2024)

Towards Reliable Testing for Multiple Information Retrieval System Comparisons
by: Otero, David, et al.
Published: (2025)

Lost in the Evidence? Reproducing Document Position and Context Size Effects in RAG
by: Gabín, Jorge, et al.
Published: (2026)

Beyond Questions: Leveraging ColBERT for Keyphrase Search
by: Gabín, Jorge, et al.
Published: (2024)

Enhancing Automatic Keyphrase Labelling with Text-to-Text Transfer Transformer (T5) Architecture: A Framework for Keyphrase Generation and Filtering
by: Gabín, Jorge, et al.
Published: (2024)

LLMJudge: LLMs for Relevance Judgments
by: Rahmani, Hossein A., et al.
Published: (2024)

Whole-Pool Setwise Reranking with Long-Context Language Models
by: Li, Hang, et al.
Published: (2026)

Don't Use LLMs to Make Relevance Judgments
by: Soboroff, Ian
Published: (2024)

LLMs Can Patch Up Missing Relevance Judgments in Evaluation
by: Upadhyay, Shivani, et al.
Published: (2024)

Topic-Specific Classifiers are Better Relevance Judges than Prompted LLMs
by: Gienapp, Lukas, et al.
Published: (2025)

Decoding Recommendation Behaviors of In-Context Learning LLMs Through Gradient Descent
by: Xu, Yi, et al.
Published: (2025)

A Deep Learning Approach for Selective Relevance Feedback
by: Datta, Suchana, et al.
Published: (2024)

A Systematic Study of Pseudo-Relevance Feedback with LLMs
by: Jedidi, Nour, et al.
Published: (2026)

Detecting Cryptographically Relevant Software Packages with Collaborative LLMs
by: Hirsch, Eduard, et al.
Published: (2026)

LLMs can be Fooled into Labelling a Document as Relevant (best café near me; this paper is perfectly relevant)
by: Alaofi, Marwah, et al.
Published: (2025)

Optimizing Generative Ranking Relevance via Reinforcement Learning in Xiaohongshu Search
by: Zeng, Ziyang, et al.
Published: (2025)

Improving FIM Code Completions via Context & Curriculum Based Learning
by: Sagtani, Hitesh, et al.
Published: (2024)

Generalized Pseudo-Relevance Feedback
by: Tu, Yiteng, et al.
Published: (2025)

Learning Effective Representations for Retrieval Using Self-Distillation with Adaptive Relevance Margins
by: Gienapp, Lukas, et al.
Published: (2024)

Learning to Trust: Dynamic Utilization of Retrieval-Augmented Generation for E-commerce Search Relevance
by: Xu, Tingqiao, et al.
Published: (2025)

How Relevance Emerges: Interpreting LoRA Fine-Tuning in Reranking LLMs
by: Nijasure, Atharva, et al.
Published: (2025)

LUCid: Redefining Relevance For Lifelong Personalization
by: Okite, Chimaobi, et al.
Published: (2026)

Unbiased Learning to Rank with Query-Level Click Propensity Estimation: Beyond Pointwise Observation and Relevance
by: Yu, Lulu, et al.
Published: (2025)

Unified Supervision for Walmart's Sponsored Search Retrieval via Joint Semantic Relevance and Behavioral Engagement Modeling
by: Desai, Shasvat, et al.
Published: (2026)

Multimodal Item Scoring for Natural Language Recommendation via Gaussian Process Regression with LLM Relevance Judgments
by: Liu, Yifan, et al.
Published: (2025)

Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels
by: Zhuang, Honglei, et al.
Published: (2023)

From Reasoning LLMs to BERT: A Two-Stage Distillation Framework for Search Relevance
by: Xia, Runze, et al.
Published: (2025)

Towards Boosting LLMs-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Prompting
by: Chen, Zeyuan, et al.
Published: (2024)

Is Relevance Propagated from Retriever to Generator in RAG?
by: Tian, Fangzheng, et al.
Published: (2025)

Augmenting Sequential Recommendation with Balanced Relevance and Diversity
by: Dang, Yizhou, et al.
Published: (2024)

Generative Retrieval Meets Multi-Graded Relevance
by: Tang, Yubao, et al.
Published: (2024)

Migrating a Job Search Relevance Function
by: Mountain, Bennett, et al.
Published: (2025)

The Cranfield II Relevance Assessments: A Critical Evaluation
by: Harter, Stephen P.
Published: (1971)

Mitigating Pooling Bias in E-commerce Search via False Negative Estimation
by: Wang, Xiaochen, et al.
Published: (2023)

Modeling Ranking Properties with In-Context Learning
by: Sinhababu, Nilanjan, et al.
Published: (2025)

Generative Reasoning Recommendation via LLMs
by: Hong, Minjie, et al.
Published: (2025)

SARA: A Collection of Sensitivity-Aware Relevance Assessments
by: McKechnie, Jack, et al.
Published: (2024)

Counterfactual Query Rewriting to Use Historical Relevance Feedback
by: Keller, Jüri, et al.
Published: (2025)

Variations in Relevance Judgments and the Shelf Life of Test Collections
by: Parry, Andrew, et al.
Published: (2025)