1 citations · 1 across the 9 of their papers we have counts for
10 papers
Hierarchical Vision-Language Interaction for Facial Action Unit Detection
Yong Li, Yi Ren, Yizhe Zhang +5
Facial Action Unit (AU) detection seeks to recognize subtle facial muscle activations as defined by the Facial Action Coding System (FACS). A primary challenge w.r.t AU detection i…
FlowConsist: Make Your Flow Consistent with Real Trajectory
Tianyi Zhang, Chengcheng Liu, Jinwei Chen +5
Fast flow models accelerate the iterative sampling process by learning to directly predict ODE path integrals, enabling one-step or few-step generation. However, we argue that curr…
Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective
Hao Fang, Tianyi Zhang, Tianqu Zhuang +6
Proprietary large language models (LLMs) embody substantial economic value and are generally exposed only as black-box APIs, yet adversaries can still exploit their outputs to extr…
Multimodal Functional Maximum Correlation for Emotion Recognition
Deyang Zheng, Tianyi Zhang, Wenming Zheng +1
Emotional states manifest as coordinated yet heterogeneous physiological responses across central and autonomic systems, posing a fundamental challenge for multimodal representatio…
Visionary Co-Driver: Enhancing Driver Perception of Potential Risks with LLM and HUD
Wei Xiang, Ziyue Lei, Jie Wang +5
Drivers' perception of risky situations has always been a challenge in driving. Existing risk-detection methods excel at identifying collisions but face challenges in assessing the…
IKnow: Instruction-Knowledge-Aware Continual Pretraining for Effective Domain Adaptation
Tianyi Zhang, Florian Mai, Lucie Flek
Continual pretraining promises to adapt large language models (LLMs) to new domains using only unlabeled test-time data, but naively applying standard self-supervised objectives to…
Sentence-level Reward Model can Generalize Better for Aligning LLM from Human Preference
Wenjie Qiu, Yi-Chen Li, Xuqin Zhang +4
Learning reward models from human preference datasets and subsequently optimizing language models via reinforcement learning has emerged as a fundamental paradigm for aligning LLMs…
Effective Two-Stage Knowledge Transfer for Multi-Entity Cross-Domain Recommendation
Jianyu Guan, Zongming Yin, Tianyi Zhang +5
In recent years, the recommendation content on e-commerce platforms has become increasingly rich -- a single user feed may contain multiple entities, such as selling products, shor…
Text as Image: Learning Transferable Adapter for Multi-Label Classification
Xuelin Zhu, Jiuxin Cao, Jian liu +7
Pre-trained vision-language models have notably accelerated progress of open-world concept recognition. Their impressive zero-shot ability has recently been transferred to multi-la…
Learning to Coordinate with Anyone
Lei Yuan, Lihe Li, Ziqian Zhang +5
In open multi-agent environments, the agents may encounter unexpected teammates. Classical multi-agent learning approaches train agents that can only coordinate with seen teammates…