Papers by Runlin Liu

2 papers
Uni-Dubbing: Zero-Shot Speech Synthesis from Visual Articulation (2024.acl-long)

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Challenge: Multimodal speech synthesis is a key challenge due to the scarcity of datasets that pair audio with corresponding video.
Approach: They propose a method that incorporates modality alignment during the pre-training phase on multimodal datasets and freezes the video modality extraction component and the encoder module within the pretrained weights.
Outcome: The proposed method achieves a reduced word error rate (WER) of 31.73%, surpassing the previous best of 33.9% with single-modality audio.
Beyond Superficial Tests: Adversarial Refinement for Reliable Property-Based Testing (2026.findings-acl)

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Challenge: Large Language Models (LLMs) have demonstrated remarkable proficiency in code generation, yet their application to Property-Based Testing (PBT) remains fraught with a superficiality gap.
Approach: They propose an agentic framework that hardens software properties through Adversarial Refinement.
Outcome: a new framework hardens software properties through Adversarial Refinement that detects and fixes bugs in top-tier libraries.

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