35 citations · 46 across the 13 of their papers we have counts for
17 papers
Von Neumann Type Inequalities for NC Operator Balls
Ran Kiri
We establish finite-dimensional von Neumann type inequalities for commuting matrix tuples in noncommutative operator balls. Let be the NC operator ball of a linear…
Multi-Dimensional Comparative Scale Construction for Efficient Personalized Subjective Judgment in High-Traffic Applications
Xianglong Shi, Shifeng Liu, Sirui Zhao +2
Subjective judgments are central to many high-traffic applications, but subjective intensity is difficult to quantify and perceptions vary substantially across individuals. To addr…
LSTMem: Hierarchical Long Short-Term Online Memory for Large Language Models
Xianglong Shi, Ruijie Yang, Sirui Zhao +4
Large language models increasingly serve as long-horizon assistants and agents, where they must both accumulate information across interactions and make the relevant parts availabl…
DynaForcing: Overcoming Dynamic Collapse in Self-Forcing Distillation for Streaming Avatar Generation
Yubo Huang, Sirui Zhao, Xinchen Yao +5
Audio-driven avatar generation requires realistic lip-sync, expressive motion, and real-time streaming. Recent work achieves the latter via self-forcing with Distribution Matching…
EviDep: Uncertainty-Aware Multimodal Depression Estimation via Disentangled Evidential Learning
Fangyuan Liu, Sirui Zhao, Yangsong Zhang +7
Audio--visual recordings provide complementary cues for estimating depression severity, but their informativeness varies across time and modalities. Point predictions alone do not…
Tango: Taming Visual Signals for Efficient Video Large Language Models
Shukang Yin, Sirui Zhao, Hanchao Wang +4
Token pruning has emerged as a mainstream approach for developing efficient Video Large Language Models (Video LLMs). This work revisits and advances the two predominant token-prun…
ActFER: Agentic Facial Expression Recognition via Active Tool-Augmented Visual Reasoning
Shifeng Liu, Zhengye Zhang, Sirui Zhao +7
Recent advances in Multimodal Large Language Models (MLLMs) have created new opportunities for facial expression recognition (FER), moving it beyond pure label prediction toward re…
DMP-TTS: Disentangled multi-modal Prompting for Controllable Text-to-Speech with Chained Guidance
Kang Yin, Chunyu Qiang, Sirui Zhao +6
Controllable text-to-speech (TTS) systems face significant challenges in achieving independent manipulation of speaker timbre and speaking style, often suffering from entanglement…
Live Avatar: Streaming Real-time Audio-Driven Avatar Generation with Infinite Length
Yubo Huang, Hailong Guo, Fangtai Wu +9
Audio-driven avatar interaction demands real-time, streaming, and infinite-length generation -- capabilities fundamentally at odds with the sequential denoising and long-horizon dr…
LIHE: Linguistic Instance-Split Hyperbolic-Euclidean Framework for Generalized Weakly-Supervised Referring Expression Comprehension
Xianglong Shi, Silin Cheng, Sirui Zhao +4
Existing Weakly-Supervised Referring Expression Comprehension (WREC) methods, while effective, are fundamentally limited by a one-to-one mapping assumption, hindering their ability…
Bind-Your-Avatar: Multi-Talking-Character Video Generation with Dynamic 3D-mask-based Embedding Router
Yubo Huang, Weiqiang Wang, Sirui Zhao +3
Recent years have witnessed remarkable advances in audio-driven talking head generation. However, existing approaches predominantly focus on single-character scenarios. While some…
MERba: Multi-Receptive Field MambaVision for Micro-Expression Recognition
Xinglong Mao, Shifeng Liu, Sirui Zhao +4
Micro-expressions (MEs) are brief, involuntary facial movements that reveal genuine emotions, offering valuable insights for psychological assessment and criminal investigations. D…
MER-CLIP: AU-Guided Vision-Language Alignment for Micro-Expression Recognition
Shifeng Liu, Xinglong Mao, Sirui Zhao +3
As a critical psychological stress response, micro-expressions (MEs) are fleeting and subtle facial movements revealing genuine emotions. Automatic ME recognition (MER) holds valua…
MELLM: A Flow-Guided Large Language Model for Micro-Expression Understanding
Sirui Zhao, Zhengye Zhang, Shifeng Liu +5
Micro-expressions (MEs), brief and low-intensity facial movements revealing concealed emotions, are crucial for affective computing. Despite notable progress in ME recognition, exi…
Sparrow: Data-Efficient Video-LLM with Text-to-Image Augmentation
Shukang Yin, Chaoyou Fu, Sirui Zhao +7
Recent years have seen the success of Multimodal Large Language Models (MLLMs) in the domain of vision understanding. The success of these models can largely be attributed to the d…
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Chaoyou Fu, Yuhan Dai, Yongdong Luo +18
In the quest for artificial general intelligence, Multi-modal Large Language Models (MLLMs) have emerged as a focal point in recent advancements. However, the predominant focus rem…
DFME: A New Benchmark for Dynamic Facial Micro-expression Recognition
Sirui Zhao, Huaying Tang, Xinglong Mao +5
One of the most important subconscious reactions, micro-expression (ME), is a spontaneous, subtle, and transient facial expression that reveals human beings' genuine emotion. There…