Papers by Xunlong Wang

3 papers
MERaLiON-AudioLLM: Advancing Speech and Language Understanding for Singapore (2025.acl-demo)

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Challenge: MERaLiON-AudioLLM is the first general-purpose audio-based large language model for multitask learning.
Approach: They introduce MERaLiON-AudioLLM, a general-purpose audio-based large language model for multitask learning with a focus on Singlish understanding.
Outcome: The proposed model exhibits strong generalization across a diverse set of tasks . it is a leading solution for region-specific AI applications.
AudioBench: A Universal Benchmark for Audio Large Language Models (2025.naacl-long)

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Challenge: Existing evaluation regimes for audio large language models do not cover the breadth of their possible use cases.
Approach: They propose to use AudioBench to evaluate audio large language models . they found that no single model excels consistently across all tasks .
Outcome: The proposed evaluation targets speech understanding, audio scene understanding, and voice understanding (paralinguistic) . no single model excels consistently across all tasks, the paper found .
Influence-based Online Experience Selection for Effective RLHF (2026.acl-long)

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Challenge: Existing methods for RL fail to establish an interpretable connection between data and optimization objectives.
Approach: They propose a data selection method that dynamically estimates the influence of individual training samples on policy optimization.
Outcome: The proposed method significantly improves training effectiveness with fewer optimization steps.

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