Axiomatic Causal Interventions for Reverse Engineering Relevance Computation in Neural Retrieval Models
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Catherine, Merullo, Jack, Eickhoff, Carsten |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Interpreting Multilingual and Document-Length Sensitive Relevance Computations in Neural Retrieval Models through Axiomatic Causal Interventions
by: Savolainen, Oliver, et al.
Published: (2025)
by: Savolainen, Oliver, et al.
Published: (2025)
Pathway to Relevance: How Cross-Encoders Implement a Semantic Variant of BM25
by: Lu, Meng, et al.
Published: (2025)
by: Lu, Meng, et al.
Published: (2025)
Evaluating Search System Explainability with Psychometrics and Crowdsourcing
by: Chen, Catherine, et al.
Published: (2022)
by: Chen, Catherine, et al.
Published: (2022)
SSE: A Metric for Evaluating Search System Explainability
by: Chen, Catherine, et al.
Published: (2023)
by: Chen, Catherine, et al.
Published: (2023)
MechIR: A Mechanistic Interpretability Framework for Information Retrieval
by: Parry, Andrew, et al.
Published: (2025)
by: Parry, Andrew, et al.
Published: (2025)
Retrieval Augmented Zero-Shot Text Classification
by: Abdullahi, Tassallah, et al.
Published: (2024)
by: Abdullahi, Tassallah, et al.
Published: (2024)
Understanding Wacky Weights: A Dissection of SPLADE's Learned Term Importance
by: Polyakov, Gregory, et al.
Published: (2026)
by: Polyakov, Gregory, et al.
Published: (2026)
From Topology to Retrieval: Decoding Embedding Spaces with Unified Signatures
by: Rottach, Florian, et al.
Published: (2025)
by: Rottach, Florian, et al.
Published: (2025)
Beyond Contrastive Learning: Synthetic Data Enables List-wise Training with Multiple Levels of Relevance
by: Esfandiarpoor, Reza, et al.
Published: (2025)
by: Esfandiarpoor, Reza, et al.
Published: (2025)
Beyond Content Relevance: Evaluating Instruction Following in Retrieval Models
by: Zhou, Jianqun, et al.
Published: (2024)
by: Zhou, Jianqun, et al.
Published: (2024)
Reverse-Engineering the Retrieval Process in GenIR Models
by: Reusch, Anja, et al.
Published: (2025)
by: Reusch, Anja, et al.
Published: (2025)
Generative Retrieval Meets Multi-Graded Relevance
by: Tang, Yubao, et al.
Published: (2024)
by: Tang, Yubao, et al.
Published: (2024)
Towards an In-Depth Comprehension of Case Relevance for Better Legal Retrieval
by: Li, Haitao, et al.
Published: (2024)
by: Li, Haitao, et al.
Published: (2024)
Is Relevance Propagated from Retriever to Generator in RAG?
by: Tian, Fangzheng, et al.
Published: (2025)
by: Tian, Fangzheng, et al.
Published: (2025)
SARA: A Collection of Sensitivity-Aware Relevance Assessments
by: McKechnie, Jack, et al.
Published: (2024)
by: McKechnie, Jack, et al.
Published: (2024)
Discovering Biases in Information Retrieval Models Using Relevance Thesaurus as Global Explanation
by: Kim, Youngwoo, et al.
Published: (2024)
by: Kim, Youngwoo, et al.
Published: (2024)
Graded Relevance Scoring of Written Essays with Dense Retrieval
by: Albatarni, Salam, et al.
Published: (2024)
by: Albatarni, Salam, et al.
Published: (2024)
Limitations of Automatic Relevance Assessments with Large Language Models for Fair and Reliable Retrieval Evaluation
by: Otero, David, et al.
Published: (2024)
by: Otero, David, et al.
Published: (2024)
TPRF: A Transformer-based Pseudo-Relevance Feedback Model for Efficient and Effective Retrieval
by: Li, Hang, et al.
Published: (2024)
by: Li, Hang, et al.
Published: (2024)
Reproducing and Extending Causal Insights Into Term Frequency Computation in Neural Rankers
by: van Marken, Cile, et al.
Published: (2025)
by: van Marken, Cile, et al.
Published: (2025)
Leveraging Large Language Models for Relevance Judgments in Legal Case Retrieval
by: Ma, Shengjie, et al.
Published: (2024)
by: Ma, Shengjie, et al.
Published: (2024)
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)
The Overlooked Role of Graded Relevance Thresholds in Multilingual Dense Retrieval
by: Wullach, Tomer, et al.
Published: (2026)
by: Wullach, Tomer, et al.
Published: (2026)
Beyond Relevance: Evaluate and Improve Retrievers on Perspective Awareness
by: Zhao, Xinran, et al.
Published: (2024)
by: Zhao, Xinran, et al.
Published: (2024)
PairDistill: Pairwise Relevance Distillation for Dense Retrieval
by: Huang, Chao-Wei, et al.
Published: (2024)
by: Huang, Chao-Wei, et al.
Published: (2024)
Unified Supervision for Walmart's Sponsored Search Retrieval via Joint Semantic Relevance and Behavioral Engagement Modeling
by: Desai, Shasvat, et al.
Published: (2026)
by: Desai, Shasvat, et al.
Published: (2026)
Towards Boosting LLMs-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Prompting
by: Chen, Zeyuan, et al.
Published: (2024)
by: Chen, Zeyuan, et al.
Published: (2024)
Domain Adaptation for Dense Retrieval and Conversational Dense Retrieval through Self-Supervision by Meticulous Pseudo-Relevance Labeling
by: Li, Minghan, et al.
Published: (2024)
by: Li, Minghan, et al.
Published: (2024)
Learning Effective Representations for Retrieval Using Self-Distillation with Adaptive Relevance Margins
by: Gienapp, Lukas, et al.
Published: (2024)
by: Gienapp, Lukas, et al.
Published: (2024)
TRUE: A Reproducible Framework for LLM-Driven Relevance Judgment in Information Retrieval
by: Dewan, Mouly, et al.
Published: (2025)
by: Dewan, Mouly, et al.
Published: (2025)
Imagine All The Relevance: Scenario-Profiled Indexing with Knowledge Expansion for Dense Retrieval
by: Lee, Sangam, et al.
Published: (2025)
by: Lee, Sangam, et al.
Published: (2025)
Breaking the Lens of the Telescope: Online Relevance Estimation over Large Retrieval Sets
by: Rathee, Mandeep, et al.
Published: (2025)
by: Rathee, Mandeep, 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)
Data, Not Model: Explaining Bias toward LLM Texts in Neural Retrievers
by: Huang, Wei, et al.
Published: (2026)
by: Huang, Wei, et al.
Published: (2026)
Human-Computer Interaction as a basis for assessing Geographic Information Retrieval Systems.
by: Manuel Enrique Puebla Martínez
Published: (2018)
by: Manuel Enrique Puebla Martínez
Published: (2018)
Why Uncertainty Estimation Methods Fall Short in RAG: An Axiomatic Analysis
by: Soudani, Heydar, et al.
Published: (2025)
by: Soudani, Heydar, et al.
Published: (2025)
Learning to Trust: Dynamic Utilization of Retrieval-Augmented Generation for E-commerce Search Relevance
by: Xu, Tingqiao, et al.
Published: (2025)
by: Xu, Tingqiao, et al.
Published: (2025)
RAG-Match: Retrieval-Augmented Knowledge Injection and Hierarchical Reasoning for Calibrated Semantic Relevance
by: Jiang, Hengjun, et al.
Published: (2026)
by: Jiang, Hengjun, et al.
Published: (2026)
Illusions of Relevance: Arbitrary Content Injection Attacks Deceive Retrievers, Rerankers, and LLM Judges
by: Tamber, Manveer Singh, et al.
Published: (2025)
by: Tamber, Manveer Singh, et al.
Published: (2025)
Prism-Reranker: Beyond Relevance Scoring -- Jointly Producing Contributions and Evidence for Agentic Retrieval
by: Zhang, Dun
Published: (2026)
by: Zhang, Dun
Published: (2026)
Similar Items
-
Interpreting Multilingual and Document-Length Sensitive Relevance Computations in Neural Retrieval Models through Axiomatic Causal Interventions
by: Savolainen, Oliver, et al.
Published: (2025) -
Pathway to Relevance: How Cross-Encoders Implement a Semantic Variant of BM25
by: Lu, Meng, et al.
Published: (2025) -
Evaluating Search System Explainability with Psychometrics and Crowdsourcing
by: Chen, Catherine, et al.
Published: (2022) -
SSE: A Metric for Evaluating Search System Explainability
by: Chen, Catherine, et al.
Published: (2023) -
MechIR: A Mechanistic Interpretability Framework for Information Retrieval
by: Parry, Andrew, et al.
Published: (2025)