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Joseph Liu

7 accepted papers

2026

REINA: Regularized Entropy Information-Based Loss for Efficient Simultaneous Speech Translation

AAAI 2026technical

Simultaneous Speech Translation (SimulST) systems stream in audio while simultaneously emitting translated text or speech. Such systems face the significant challenge of balancing translation quality and latency. We introduce a strategy to optimize this tradeoff: wait for more input only if you gain

Cited by 0SourcePDFScholar
2026

RoMo: A Large-Scale, Richly Organized Dataset and Semantic Taxonomy for Human Motion Generation

CVPR 2026

Success in generative modeling across language, image, and video demonstrates that large, well-curated datasets are the key driver for building capable models. 3D Human motion, however, has lagged behind, constrained by an unsatisfying choice between small, high-fidelity motion capture datasets and

Cited by 0SourceScholar
2025

Less is More: Improving Motion Diffusion Models with Sparse Keyframes

ICCV 2025poster

Recent advances in motion diffusion models have led to remarkable progress in diverse motion generation tasks, including text-to-motion synthesis.However, existing approaches represent motions as dense frame sequences, requiring the model to process redundant or less informative frames.The processin…

Cited by 0SourcePDFScholar
2025

StyleMotif: Multi-Modal Motion Stylization using Style-Content Cross Fusion

ICCV 2025poster

We present StyleMotif, a novel Stylized Motion Latent Diffusion model, generating motion conditioned on both content and style from multiple modalities. Unlike existing approaches that either focus on generating diverse motion content or transferring style from sequences, StyleMotif seamlessly synth…

2025

Symbolic Representation for Any-to-Any Generative Tasks

CVPR 2025poster

We propose a symbolic generative task description language and a corresponding inference engine that can represent arbitrary multimodal tasks as structured symbolic flows. Unlike conventional generative models, which rely on large-scale training and implicit neural representations to learn cross-mod…

2024

Voice Toxicity Detection Using Multi-Task Learning

ICASSP 2024accepted

Social communication systems must identify toxic voice audio to support moderation that protects the safety and civility of their communities. Toxicity classification for voice depends on both audio style, such as volume and tone, and content, such as the words in the speech individually and in cont…

Cited by 0SourceScholar