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Xiaoyu Qin

5 accepted papers

2026

Emotion-Conditioned Motion Sub-spaces with Flow Matching for Real-Time Audio-Driven Talking Heads

AAAI 2026technical

Recent advances in audio-driven talking-head synthesis have brought lip-sync precision close to human perception, yet emotional fidelity and real-time inference remain open challenges. Existing pipelines typically disentangle lip articulation, facial expression, and head pose in latent space; this

Cited by 0SourcePDFScholar
2026

From Natural Alignment to Conditional Controllability in Multimodal Dialogue

ICLR 2026poster

The recent advancement of Artificial Intelligence Generated Content (AIGC) has led to significant strides in modeling human interaction, particularly in the context of multi-modal dialogue. While current methods impressively generates realistic dialogue in speech and vision modalities, challenges r…

Cited by 0SourcecodeScholar
2026

Outlier Matters: Efficient Long-to-Short Reasoning via Outlier-Guided Model Merging

AAAI 2026technical

Large Reasoning Language Models (LRMs) have recently shown remarkable performance in complex reasoning tasks, but their extensive reasoning chains incur substantial computational overhead. To address this challenge, we propose Outlier-aware Reasoning Conciseness Adaptive Merge (ORCA), a novel plug-a

Cited by 0SourcePDFScholar
2026

Sub-MoE: Efficient Mixture-of-Expert LLMs Compression via Subspace Expert Merging

AAAI 2026technical

Mixture of Experts (MoE) LLMs face significant obstacles due to their massive parameter scale, which imposes memory, storage, and deployment challenges. Although recent expert merging methods aim to achieve greater efficiency by consolidating several experts, they are fundamentally hindered by param

Cited by 0SourcePDFScholar
2025

Minimal Impact ControlNet: Advancing Multi-ControlNet Integration

ICLR 2025poster

With the advancement of diffusion models, there is a growing demand for high-quality, controllable image generation, particularly through methods that utilize one or multiple control signals based on ControlNet. However, in current ControlNet training, each control is designed to influence all areas…

Cited by 0SourcePDFScholar