3 citations · 5 across the 11 of their papers we have counts for
9 papers · 1 filter
Towards Seamless Interaction: Causal Turn-Level Modeling of Interactive 3D Conversational Head Dynamics
Junjie Chen, Fei Wang, Zhihao Huang +5
Human conversation involves continuous exchanges of speech and nonverbal cues such as head nods, gaze shifts, and facial expressions that convey attention and emotion. Modeling the…
Training-Free Multimodal Deepfake Detection via Graph Reasoning
Yuxin Liu, Fei Wang, Kun Li +5
Multimodal deepfake detection (MDD) aims to uncover manipulations across visual, textual, and auditory modalities, thereby reinforcing the reliability of modern information systems…
Forecast then Calibrate: Feature Caching as ODE for Efficient Diffusion Transformers
Shikang Zheng, Liang Feng, Xinyu Wang +8
Diffusion Transformers (DiTs) have demonstrated exceptional performance in high-fidelity image and video generation. To reduce their substantial computational costs, feature cachin…
HiCache: A Plug-in Scaled-Hermite Upgrade for Taylor-Style Cache-then-Forecast Diffusion Acceleration
Liang Feng, Shikang Zheng, Jiacheng Liu +8
Diffusion models have achieved remarkable success in content generation but often incur prohibitive computational costs due to iterative sampling. Recent feature caching methods ac…
TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration
Weiya Li, Junjie Chen, Bei Li +8
Machine translation has long been a central task in natural language processing. With the rapid advancement of large language models (LLMs), there has been remarkable progress in t…
dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching
Zhiyuan Liu, Yicun Yang, Yaojie Zhang +6
Autoregressive Models (ARMs) have long dominated the landscape of Large Language Models. Recently, a new paradigm has emerged in the form of diffusion-based Large Language Models (…
Shifting AI Efficiency From Model-Centric to Data-Centric Compression
Xuyang Liu, Zichen Wen, Shaobo Wang +14
The advancement of large language models (LLMs) and multi-modal LLMs (MLLMs) has historically relied on scaling model parameters. However, as hardware limits constrain further mode…
Seeing Sarcasm Through Different Eyes: Analyzing Multimodal Sarcasm Perception in Large Vision-Language Models
Junjie Chen, Xuyang Liu, Subin Huang +2
With the advent of large vision-language models (LVLMs) demonstrating increasingly human-like abilities, a pivotal question emerges: do different LVLMs interpret multimodal sarcasm…
From Reusing to Forecasting: Accelerating Diffusion Models with TaylorSeers
Jiacheng Liu, Chang Zou, Yuanhuiyi Lyu +2
Diffusion Transformers (DiT) have revolutionized high-fidelity image and video synthesis, yet their computational demands remain prohibitive for real-time applications. To solve th…