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InterCorrect: Intersection-Aware Correction of Demographic Model Merging for Fair ASR

Paper recorded by Signals 4 on 2026-10-06 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-06 on arXiv · recorded by Signals 4 on 2026-10-07

Category: cs.CL · 自然语言处理 · first seen 2026-10-07

Abstract

Automatic Speech Recognition (ASR) systems often show uneven performance across demographic groups, and errors can be especially difficult to address for speakers belonging to multiple demographic groups. This work studies demographic-aware model merging for fair Speech-LLM-based ASR. Starting from a SLAM-ASR-based model, we fine-tune only the connector on demographic-specific subsets and merge th

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#316 most recent of 660 cs.CL papers we have recorded · ↑ newer: Towards In-Parameter Memory Augmentation for Large Language Models · ↓ older: Generative AI translations in high-stakes emergency messaging
Cite this page: InterCorrect: Intersection-Aware Correction of Demographic Model Merging for Fair ASR: the #316 most recent of 660 cs.CL papers we have recorded (as of 2026-10-06). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/intercorrect-intersection-aware-correction-of-demographic-model-merging-for-fair.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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