Papers by Haoxing Zhang

3 papers
Dynamic Model-Bank Test-Time Adaptation for Automatic Speech Recognition (2025.emnlp-main)

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Challenge: Existing ASR TTA methods struggle with instability under continual and long-term distribution shifts.
Approach: They propose a continuous adaptive model-bank framework that adapts to domain shifts in ASR test-time scenarios.
Outcome: Experiments on diverse, continuously shifting ASR benchmarks show that DMSUTA outperforms existing continual TTA baselines.
Prompt-Based Meta-Learning For Few-shot Text Classification (2022.emnlp-main)

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Challenge: Existing methods to learn text labels require large amounts of data to build many few-shot tasks.
Approach: They propose a Prompt-Based Meta-Learning model that adds the prompting mechanism to the meta-learning method.
Outcome: The proposed method improves on four text classification datasets with high accuracy and robustness.
CogAtom: From Cognitive Atoms to Olympiad-level Mathematical Reasoning in Large Language Models (2025.findings-emnlp)

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Challenge: Existing methods for generating high-quality, multi-step reasoning are limited . we present a new framework for synthesising rigorous, cognitively diverse problems .
Approach: They propose a cognitive atom-based framework for synthesizing mathematically rigorous problems.
Outcome: The proposed framework outperforms existing methods in accuracy, reasoning depth and diversity while exceeding the difficulty of AIME.

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