ARHN: Answer-Centric Relabeling of Hard Negatives with Open-Source LLMs for Dense Retrieval
Fuente:
arXiv
Saved in:
| Main Authors: | Choi, Hyewon, Choi, Jooyoung, Jang, Hansol, Kim, Hyun, Yun, Chulmin, Jun, ChangWook, Choi, Stanley Jungkyu |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
LGAI-EMBEDDING-Preview Technical Report
by: Choi, Jooyoung, et al.
Published: (2025)
by: Choi, Jooyoung, et al.
Published: (2025)
Beyond Hard Negatives: The Importance of Score Distribution in Knowledge Distillation for Dense Retrieval
by: Jang, Youngjoon, et al.
Published: (2026)
by: Jang, Youngjoon, et al.
Published: (2026)
SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval
by: Li, Xiaopeng, et al.
Published: (2024)
by: Li, Xiaopeng, et al.
Published: (2024)
Open-World Evaluation for Retrieving Diverse Perspectives
by: Chen, Hung-Ting, et al.
Published: (2024)
by: Chen, Hung-Ting, et al.
Published: (2024)
BiCA: Effective Biomedical Dense Retrieval with Citation-Aware Hard Negatives
by: Sinha, Aarush, et al.
Published: (2025)
by: Sinha, Aarush, et al.
Published: (2025)
Soft Filtering: Guiding Zero-shot Composed Image Retrieval with Prescriptive and Proscriptive Constraints
by: Jung, Youjin, et al.
Published: (2025)
by: Jung, Youjin, et al.
Published: (2025)
LILaC: Late Interacting in Layered Component Graph for Open-domain Multimodal Multihop Retrieval
by: Yun, Joohyung, et al.
Published: (2026)
by: Yun, Joohyung, et al.
Published: (2026)
Hard Negatives, Hard Lessons: Revisiting Training Data Quality for Robust Information Retrieval with LLMs
by: Thakur, Nandan, et al.
Published: (2025)
by: Thakur, Nandan, et al.
Published: (2025)
ARK: Answer-Centric Retriever Tuning via KG-augmented Curriculum Learning
by: Ding, Hang, et al.
Published: (2025)
by: Ding, Hang, et al.
Published: (2025)
SCONE: A Novel Stochastic Sampling to Generate Contrastive Views and Hard Negative Samples for Recommendation
by: Lee, Chaejeong, et al.
Published: (2024)
by: Lee, Chaejeong, et al.
Published: (2024)
Reliable Evaluation Protocol for Low-Precision Retrieval
by: Yang, Kisu, et al.
Published: (2025)
by: Yang, Kisu, 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)
by: Dinzinger, Michael, et al.
Published: (2026)
Leveraging LLMs for Unsupervised Dense Retriever Ranking
by: Khramtsova, Ekaterina, et al.
Published: (2024)
by: Khramtsova, Ekaterina, et al.
Published: (2024)
TriSampler: A Better Negative Sampling Principle for Dense Retrieval
by: Yang, Zhen, et al.
Published: (2024)
by: Yang, Zhen, et al.
Published: (2024)
Negative Data Mining for Contrastive Learning in Dense Retrieval at IKEA.com
by: Agapaki, Eva, et al.
Published: (2026)
by: Agapaki, Eva, et al.
Published: (2026)
RVR: Retrieve-Verify-Retrieve for Comprehensive Question Answering
by: Qian, Deniz, et al.
Published: (2026)
by: Qian, Deniz, et al.
Published: (2026)
XML: How It Will Be Applied to Digital Library Systems.
by: Kim, Hyun-Hee, et al.
Published: (2000)
by: Kim, Hyun-Hee, et al.
Published: (2000)
Identifying Key Terms in Prompts for Relevance Evaluation with GPT Models
by: Choi, Jaekeol
Published: (2024)
by: Choi, Jaekeol
Published: (2024)
Improving Dense Passage Retrieval with Multiple Positive Passages
by: Chang, Shuai
Published: (2025)
by: Chang, Shuai
Published: (2025)
Scaling Sparse and Dense Retrieval in Decoder-Only LLMs
by: Zeng, Hansi, et al.
Published: (2025)
by: Zeng, Hansi, et al.
Published: (2025)
ListT5: Listwise Reranking with Fusion-in-Decoder Improves Zero-shot Retrieval
by: Yoon, Soyoung, et al.
Published: (2024)
by: Yoon, Soyoung, et al.
Published: (2024)
GLEN: Generative Retrieval via Lexical Index Learning
by: Lee, Sunkyung, et al.
Published: (2023)
by: Lee, Sunkyung, et al.
Published: (2023)
FinDER: Financial Dataset for Question Answering and Evaluating Retrieval-Augmented Generation
by: Choi, Chanyeol, et al.
Published: (2025)
by: Choi, Chanyeol, et al.
Published: (2025)
Optimizing Legal Document Retrieval in Vietnamese with Semi-Hard Negative Mining
by: Le, Van-Hoang, et al.
Published: (2025)
by: Le, Van-Hoang, et al.
Published: (2025)
Extracting Information from Scientific Literature via Visual Table Question Answering Models
by: Kim, Dongyoun, et al.
Published: (2025)
by: Kim, Dongyoun, et al.
Published: (2025)
The RAG Paradox: A Black-Box Attack Exploiting Unintentional Vulnerabilities in Retrieval-Augmented Generation Systems
by: Choi, Chanwoo, et al.
Published: (2025)
by: Choi, Chanwoo, et al.
Published: (2025)
Maximum-Entropy Regularized Decision Transformer with Reward Relabelling for Dynamic Recommendation
by: Chen, Xiaocong, et al.
Published: (2024)
by: Chen, Xiaocong, et al.
Published: (2024)
RARe: Retrieval Augmented Retrieval with In-Context Examples
by: Tejaswi, Atula, et al.
Published: (2024)
by: Tejaswi, Atula, et al.
Published: (2024)
Study on LLMs for Promptagator-Style Dense Retriever Training
by: Gwon, Daniel, et al.
Published: (2025)
by: Gwon, Daniel, et al.
Published: (2025)
Reference-Aligned Retrieval-Augmented Question Answering over Heterogeneous Proprietary Documents
by: Choi, Nayoung, et al.
Published: (2025)
by: Choi, Nayoung, et al.
Published: (2025)
Negation is Not Semantic: Diagnosing Dense Retrieval Failure Modes for Trade-offs in Contradiction-Aware Biomedical QA
by: Sahoo, Soumya Ranjan, et al.
Published: (2026)
by: Sahoo, Soumya Ranjan, et al.
Published: (2026)
Don't Retrieve, Generate: Prompting LLMs for Synthetic Training Data in Dense Retrieval
by: Sinha, Aarush
Published: (2025)
by: Sinha, Aarush
Published: (2025)
PairDistill: Pairwise Relevance Distillation for Dense Retrieval
by: Huang, Chao-Wei, et al.
Published: (2024)
by: Huang, Chao-Wei, et al.
Published: (2024)
Intent-Interest Disentanglement and Item-Aware Intent Contrastive Learning for Sequential Recommendation
by: Choi, Yijin, et al.
Published: (2025)
by: Choi, Yijin, et al.
Published: (2025)
Predicting Retrieval Utility and Answer Quality in Retrieval-Augmented Generation
by: Tian, Fangzheng, et al.
Published: (2026)
by: Tian, Fangzheng, et al.
Published: (2026)
History-Aware Conversational Dense Retrieval
by: Mo, Fengran, et al.
Published: (2024)
by: Mo, Fengran, et al.
Published: (2024)
Adaptive Hardness Negative Sampling for Collaborative Filtering
by: Lai, Riwei, et al.
Published: (2024)
by: Lai, Riwei, et al.
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)
Answer Retrieval in Legal Community Question Answering
by: Askari, Arian, et al.
Published: (2024)
by: Askari, Arian, et al.
Published: (2024)
Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QA
by: Chae, Kyubyung, et al.
Published: (2026)
by: Chae, Kyubyung, et al.
Published: (2026)
Similar Items
-
LGAI-EMBEDDING-Preview Technical Report
by: Choi, Jooyoung, et al.
Published: (2025) -
Beyond Hard Negatives: The Importance of Score Distribution in Knowledge Distillation for Dense Retrieval
by: Jang, Youngjoon, et al.
Published: (2026) -
SyNeg: LLM-Driven Synthetic Hard-Negatives for Dense Retrieval
by: Li, Xiaopeng, et al.
Published: (2024) -
Open-World Evaluation for Retrieving Diverse Perspectives
by: Chen, Hung-Ting, et al.
Published: (2024) -
BiCA: Effective Biomedical Dense Retrieval with Citation-Aware Hard Negatives
by: Sinha, Aarush, et al.
Published: (2025)