5 papers · 1 filter
A Mechanistic Analysis of Gender Sensitivity in Dense Retrieval Models
Catherine Chen, Maarten de Rijke, Carsten Eickhoff
While gender bias in dense retrieval models is well documented, with prior work showing that models often score male-gendered documents higher than female or neutral variants, the…
Pathway to Relevance: How Cross-Encoders Implement a Semantic Variant of BM25
Meng Lu, Catherine Chen, Carsten Eickhoff
Mechanistic interpretation has greatly contributed to a more detailed understanding of generative language models, enabling significant progress in identifying structures that impl…
Axiomatic Causal Interventions for Reverse Engineering Relevance Computation in Neural Retrieval Models
Catherine Chen, Jack Merullo, Carsten Eickhoff
Neural models have demonstrated remarkable performance across diverse ranking tasks. However, the processes and internal mechanisms along which they determine relevance are still l…
MechIR: A Mechanistic Interpretability Framework for Information Retrieval
Andrew Parry, Catherine Chen, Carsten Eickhoff +1
Mechanistic interpretability is an emerging diagnostic approach for neural models that has gained traction in broader natural language processing domains. This paradigm aims to pro…
Evaluating Search System Explainability with Psychometrics and Crowdsourcing
Catherine Chen, Carsten Eickhoff
As information retrieval (IR) systems, such as search engines and conversational agents, become ubiquitous in various domains, the need for transparent and explainable systems grow…