Cover Image

Hard Negatives, Hard Lessons: Revisiting Training Data Quality for Robust Information Retrieval with LLMs

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Thakur, Nandan, Zhang, Crystina, Ma, Xueguang, Lin, Jimmy
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

ORBIT: Scalable and Verifiable Data Generation for Search Agents on a Tight Budget
by: Thakur, Nandan, et al.
Published: (2026)

Leveraging LLMs for Synthesizing Training Data Across Many Languages in Multilingual Dense Retrieval
by: Thakur, Nandan, et al.
Published: (2023)

Still Fresh? Evaluating Temporal Drift in Retrieval Benchmarks
by: Kuissi, Nathan, et al.
Published: (2026)

FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents
by: Thakur, Nandan, et al.
Published: (2025)

LACONIC: Dense-Level Effectiveness for Scalable Sparse Retrieval via a Two-Phase Training Curriculum
by: Xu, Zhichao, et al.
Published: (2026)

Ragnarök: A Reusable RAG Framework and Baselines for TREC 2024 Retrieval-Augmented Generation Track
by: Pradeep, Ronak, et al.
Published: (2024)

Enhancing Retrieval Performance: An Ensemble Approach For Hard Negative Mining
by: Meghwani, Hansa
Published: (2024)

Support Evaluation for the TREC 2024 RAG Track: Comparing Human versus LLM Judges
by: Thakur, Nandan, et al.
Published: (2025)

WebFAQ 2.0: A Multilingual QA Dataset with Mined Hard Negatives for Dense Retrieval
by: Dinzinger, Michael, et al.
Published: (2026)

Rethinking Agentic Search with Pi-Serini: Is Lexical Retrieval Sufficient?
by: Hsu, Tz-Huan, et al.
Published: (2026)

A Survey on Retrieval-Augmented Text Generation for Large Language Models
by: Huang, Yizheng, et al.
Published: (2024)

MAGMaR Shared Task System Description: Video Retrieval with OmniEmbed
by: Zhan, Jiaqi Samantha, et al.
Published: (2025)

ECI: Effective Contrastive Information to Evaluate Hard-Negatives
by: Sinha, Aarush, et al.
Published: (2026)

Exploring ChatGPT for Next-generation Information Retrieval: Opportunities and Challenges
by: Huang, Yizheng, et al.
Published: (2024)

Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining
by: Le, Van-Hoang, et al.
Published: (2025)

Utilizing BERT for Information Retrieval: Survey, Applications, Resources, and Challenges
by: Wang, Jiajia, et al.
Published: (2024)

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

Generative Query Expansion with Multilingual LLMs for Cross-Lingual Information Retrieval
by: Macmillan-Scott, Olivia, et al.
Published: (2025)

BiCA: Effective Biomedical Dense Retrieval with Citation-Aware Hard Negatives
by: Sinha, Aarush, et al.
Published: (2025)

DRAMA: Diverse Augmentation from Large Language Models to Smaller Dense Retrievers
by: Ma, Xueguang, et al.
Published: (2025)

Bridging Language Gaps: Advances in Cross-Lingual Information Retrieval with Multilingual LLMs
by: Goworek, Roksana, et al.
Published: (2025)

Rankers, Judges, and Assistants: Towards Understanding the Interplay of LLMs in Information Retrieval Evaluation
by: Balog, Krisztian, et al.
Published: (2025)

Scaling Retrieval Augmented Generation with RAG Fusion: Lessons from an Industry Deployment
by: Medrano, Luigi, et al.
Published: (2026)

Unsupervised Information Refinement Training of Large Language Models for Retrieval-Augmented Generation
by: Xu, Shicheng, et al.
Published: (2024)

Are LLMs Truly Multilingual? Exploring Zero-Shot Multilingual Capability of LLMs for Information Retrieval: An Italian Healthcare Use Case
by: Kembu, Vignesh Kumar, et al.
Published: (2025)

OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesis
by: Li, Zhuofeng, et al.
Published: (2026)

R^2AG: Incorporating Retrieval Information into Retrieval Augmented Generation
by: Ye, Fuda, et al.
Published: (2024)

Graph Neural Network Enhanced Retrieval for Question Answering of LLMs
by: Li, Zijian, et al.
Published: (2024)

Unleashing the Power of LLMs in Dense Retrieval with Query Likelihood Modeling
by: Zhang, Hengran, et al.
Published: (2025)

SPARQL Query Generation with LLMs: Measuring the Impact of Training Data Memorization and Knowledge Injection
by: Gashkov, Aleksandr, et al.
Published: (2025)

Retrieval-Augmented Generation by Evidence Retroactivity in LLMs
by: Xiao, Liang, et al.
Published: (2025)

"Knowing When You Don't Know": A Multilingual Relevance Assessment Dataset for Robust Retrieval-Augmented Generation
by: Thakur, Nandan, et al.
Published: (2023)

Token-wise Influential Training Data Retrieval for Large Language Models
by: Lin, Huawei, et al.
Published: (2024)

Self-Retrieval: End-to-End Information Retrieval with One Large Language Model
by: Tang, Qiaoyu, et al.
Published: (2024)

Vector Retrieval with Similarity and Diversity: How Hard Is It?
by: Gao, Hang, et al.
Published: (2024)

Retro*: Optimizing LLMs for Reasoning-Intensive Document Retrieval
by: Lan, Junwei, et al.
Published: (2025)

LLM Alignment as Retriever Optimization: An Information Retrieval Perspective
by: Jin, Bowen, et al.
Published: (2025)

Benchmarking Information Retrieval Models on Complex Retrieval Tasks
by: Killingback, Julian, et al.
Published: (2025)

Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning
by: Zhuang, Shengyao, et al.
Published: (2025)

Training for Compositional Sensitivity Reduces Dense Retrieval Generalization
by: Ralev, Radoslav, et al.
Published: (2026)