When Forgetting Looks Like Improvement: Metric Masking in Streaming Diarizer Adaptation and the Price of Rehearsal

arXiv:2610.08828 · cs.CL, cs.SD, eess.AS · Submitted 2026-09-26 · Read on arXiv

cs.CL, cs.SD, eess.AS

Submitted: 2026-09-26

Updated: 2026-09-26

Comments: 5 pages, 4 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Adaptation — 1× in this paper · explained in 1 episode

Sources

• Benchmarking Diarization Models
• NeMo: a toolkit for building AI applications using Neural Modules
• On Tiny Episodic Memories in Continual Learning
• EasyCom: An Augmented Reality Dataset to Support Algorithms for Easy Communication in Noisy Environments
• Dissecting the Segmentation Model of End-to-End Diarization with Vector Clustering

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering