Papers by Ziqi Liang

2 papers
OpenVNA: A Framework for Analyzing the Behavior of Multimodal Language Understanding System under Noisy Scenarios (2024.acl-demos)

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Challenge: OpenVNA is an open-source framework for analyzing the behavior of multimodal language understanding systems under noisy conditions.
Approach: They propose to use OpenVNA to analyze behavior of multimodal language understanding systems under noisy conditions.
Outcome: The proposed framework provides high flexibility and extensibility, enabling customization with user-defined noise types and models.
AlignCap: Aligning Speech Emotion Captioning to Human Preferences (2024.emnlp-main)

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Challenge: Existing methods for speech emotion capture often produce hallucinations and lose generalization on unseen speech.
Approach: They propose to align speech emotion captioning to human preference based on large language model (LLM) and human preference regularization to eliminate factuality and faithfulness hallucinations.
Outcome: Experiments show that AlignCap performs better than existing methods on Zero-shot SEC task.

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