Fact or Facsimile? Evaluating the Factual Robustness of Modern Retrievers
Fuente:
arXiv
Saved in:
| Main Authors: | Wu, Haoyu, Zeng, Qingcheng, Ding, Kaize |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Dual-View Training for Instruction-Following Information Retrieval
by: Zeng, Qingcheng, et al.
Published: (2026)
by: Zeng, Qingcheng, et al.
Published: (2026)
Worse than Zero-shot? A Fact-Checking Dataset for Evaluating the Robustness of RAG Against Misleading Retrievals
by: Zeng, Linda, et al.
Published: (2025)
by: Zeng, Linda, et al.
Published: (2025)
Code-Switching Information Retrieval: Benchmarks, Analysis, and the Limits of Current Retrievers
by: Zeng, Qingcheng, et al.
Published: (2026)
by: Zeng, Qingcheng, et al.
Published: (2026)
FBAdtTracker: An Interactive Data Collection and Analysis Tool for Facebook Advertisements
by: Jeong, Ujun, et al.
Published: (2021)
by: Jeong, Ujun, et al.
Published: (2021)
IRB: Automated Generation of Robust Factuality Benchmarks
by: Do, Lam Thanh, et al.
Published: (2026)
by: Do, Lam Thanh, et al.
Published: (2026)
An Empirical Study of Position Bias in Modern Information Retrieval
by: Zeng, Ziyang, et al.
Published: (2025)
by: Zeng, Ziyang, et al.
Published: (2025)
Context-Efficient Retrieval with Factual Decomposition
by: Li, Yanhong, et al.
Published: (2025)
by: Li, Yanhong, et al.
Published: (2025)
FactIR: A Real-World Zero-shot Open-Domain Retrieval Benchmark for Fact-Checking
by: V, Venktesh, et al.
Published: (2025)
by: V, Venktesh, et al.
Published: (2025)
Enhancing Health Information Retrieval with RAG by Prioritizing Topical Relevance and Factual Accuracy
by: Uapadhyay, Rishabh, et al.
Published: (2025)
by: Uapadhyay, Rishabh, et al.
Published: (2025)
From Relevance to Utility: Evidence Retrieval with Feedback for Fact Verification
by: Zhang, Hengran, et al.
Published: (2023)
by: Zhang, Hengran, et al.
Published: (2023)
Structure Guided Retrieval-Augmented Generation for Factual Queries
by: Xie, Miao, et al.
Published: (2026)
by: Xie, Miao, et al.
Published: (2026)
Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation
by: Ren, Ruiyang, et al.
Published: (2023)
by: Ren, Ruiyang, et al.
Published: (2023)
FlashCheck: Exploration of Efficient Evidence Retrieval for Fast Fact-Checking
by: Nanekhan, Kevin, et al.
Published: (2025)
by: Nanekhan, Kevin, et al.
Published: (2025)
NeuCLIRBench: A Modern Evaluation Collection for Monolingual, Cross-Language, and Multilingual Information Retrieval
by: Lawrie, Dawn, et al.
Published: (2025)
by: Lawrie, Dawn, et al.
Published: (2025)
Evaluating Robustness of Generative Search Engine on Adversarial Factual Questions
by: Hu, Xuming, et al.
Published: (2024)
by: Hu, Xuming, et al.
Published: (2024)
Checking Fact with Better Retrieval: Dynamic Contrastive Learning for Evidence Retrieval
by: Hua, Zhongtian, et al.
Published: (2026)
by: Hua, Zhongtian, et al.
Published: (2026)
ModernVBERT: Towards Smaller Visual Document Retrievers
by: Teiletche, Paul, et al.
Published: (2025)
by: Teiletche, Paul, et al.
Published: (2025)
A Multi-Agent Perspective on Modern Information Retrieval
by: Nachimovsky, Haya, et al.
Published: (2025)
by: Nachimovsky, Haya, et al.
Published: (2025)
Response Quality Assessment for Retrieval-Augmented Generation via Conditional Conformal Factuality
by: Feng, Naihe, et al.
Published: (2025)
by: Feng, Naihe, et al.
Published: (2025)
Towards Dependable Retrieval-Augmented Generation Using Factual Confidence Prediction
by: Geissler, Florian, et al.
Published: (2026)
by: Geissler, Florian, et al.
Published: (2026)
Robust Information Retrieval
by: Liu, Yu-An, et al.
Published: (2024)
by: Liu, Yu-An, et al.
Published: (2024)
Collapse of Dense Retrievers: Short, Early, and Literal Biases Outranking Factual Evidence
by: Fayyaz, Mohsen, et al.
Published: (2025)
by: Fayyaz, Mohsen, et al.
Published: (2025)
Resolving Conflicting Evidence in Automated Fact-Checking: A Study on Retrieval-Augmented LLMs
by: Ge, Ziyu, et al.
Published: (2025)
by: Ge, Ziyu, et al.
Published: (2025)
Modernizing Facebook Scoped Search: Keyword and Embedding Hybrid Retrieval with LLM Evaluation
by: Su, Yongye, et al.
Published: (2025)
by: Su, Yongye, et al.
Published: (2025)
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)
Multi-Sourced, Multi-Agent Evidence Retrieval for Fact-Checking
by: Gong, Shuzhi, et al.
Published: (2026)
by: Gong, Shuzhi, et al.
Published: (2026)
Towards More Robust Retrieval-Augmented Generation: Evaluating RAG Under Adversarial Poisoning Attacks
by: Su, Jinyan, et al.
Published: (2024)
by: Su, Jinyan, et al.
Published: (2024)
Right Answer at the Right Time - Temporal Retrieval-Augmented Generation via Graph Summarization
by: Zhu, Zulun, et al.
Published: (2025)
by: Zhu, Zulun, et al.
Published: (2025)
BioPulse-QA: A Dynamic Biomedical Question-Answering Benchmark for Evaluating Factuality, Robustness, and Bias in Large Language Models
by: Bhattarai, Kriti, et al.
Published: (2026)
by: Bhattarai, Kriti, et al.
Published: (2026)
On the Factual Consistency of Text-based Explainable Recommendation Models
by: Kabongo, Ben, et al.
Published: (2025)
by: Kabongo, Ben, 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)
On the Robustness of Generative Information Retrieval Models
by: Liu, Yu-An, et al.
Published: (2024)
by: Liu, Yu-An, et al.
Published: (2024)
+VeriRel: Verification Feedback to Enhance Document Retrieval for Scientific Fact Checking
by: Deng, Xingyu, et al.
Published: (2025)
by: Deng, Xingyu, et al.
Published: (2025)
Mask-to-Correct$^+$: Leveraging Retriever Diversity for Masking-guided Faithful Fact Correction
by: Santra, Payel, et al.
Published: (2026)
by: Santra, Payel, et al.
Published: (2026)
Robust-IR @ SIGIR 2025: The First Workshop on Robust Information Retrieval
by: Liu, Yu-An, et al.
Published: (2025)
by: Liu, Yu-An, et al.
Published: (2025)
MMSRARec: Summarization and Retrieval Augumented Sequential Recommendation Based on Multimodal Large Language Model
by: Wang, Haoyu, et al.
Published: (2025)
by: Wang, Haoyu, et al.
Published: (2025)
MAIR: A Massive Benchmark for Evaluating Instructed Retrieval
by: Sun, Weiwei, et al.
Published: (2024)
by: Sun, Weiwei, et al.
Published: (2024)
Learning Contextual Retrieval for Robust Conversational Search
by: Yang, Seunghan, et al.
Published: (2025)
by: Yang, Seunghan, et al.
Published: (2025)
Enabling Collaborative Parametric Knowledge Calibration for Retrieval-Augmented Vision Question Answering
by: Deng, Jiaqi, et al.
Published: (2025)
by: Deng, Jiaqi, et al.
Published: (2025)
Generative Information Retrieval Evaluation
by: Alaofi, Marwah, et al.
Published: (2024)
by: Alaofi, Marwah, et al.
Published: (2024)
Similar Items
-
Dual-View Training for Instruction-Following Information Retrieval
by: Zeng, Qingcheng, et al.
Published: (2026) -
Worse than Zero-shot? A Fact-Checking Dataset for Evaluating the Robustness of RAG Against Misleading Retrievals
by: Zeng, Linda, et al.
Published: (2025) -
Code-Switching Information Retrieval: Benchmarks, Analysis, and the Limits of Current Retrievers
by: Zeng, Qingcheng, et al.
Published: (2026) -
FBAdtTracker: An Interactive Data Collection and Analysis Tool for Facebook Advertisements
by: Jeong, Ujun, et al.
Published: (2021) -
IRB: Automated Generation of Robust Factuality Benchmarks
by: Do, Lam Thanh, et al.
Published: (2026)