19 citations · 37 across the 13 of their papers we have counts for
16 papers
Gamma: Grounded Multi-Agent Memory with Mechanical Audit for Memory-Intensive Manipulation
Yudong Liu, Yueqian Lin, Zijia Tang +11
Pretrained vision-language-action (VLA) policies fail on memory tasks, behaviour that depends on events observed long before the current frame, because their training data is overw…
Diffusion Meta-Prompting and Steering for Generalizable Foundation Model Adaptation
Deepak Sridhar, Yi Li, Kartikeya Bhardwaj +7
Prompt learning is a popular method for adapting foundation models, but learned prompts are typically task-specific and fail to generalize to new classes, domains, or compositions…
Conditional Multi-Event Temporal Grounding in Long-Form Video
Yuanhao Zou, Arthad Kulkarni, Lucas Tonanez +12
Multimodal large language models have made rapid progress in video temporal grounding, yet real-world applications routinely require localizing every event that satisfies compositi…
Beyond Layer Importance in Layer-wise Sparsity: An Inter-Layer Perturbation-Absorption Perspective
Tao Jing, Ningxin Wu, Chen Kang +3
The considerable layer-wise redundancy in large language models (LLMs) has established non-uniform sparsity allocation across layers as the standard pruning approach for efficient…
Latent Bridge: Feature Delta Prediction for Efficient Dual-System Vision-Language-Action Model Inference
Yudong Liu, Yuan Li, Zijia Tang +12
Dual-system Vision-Language-Action (VLA) models achieve state-of-the-art robotic manipulation but are bottlenecked by the VLM backbone, which must execute at every control step whi…
ForeSea: AI Forensic Search with Multi-modal Queries for Video Surveillance
Hyojin Park, Yi Li, Janghoon Cho +8
Despite decades of work, surveillance still struggles in searching and reasoning about specific targets across long, multi-camera videos. Existing methods - tracking, retrieval, an…
DiSa: Saliency-Aware Foreground-Background Disentangled Framework for Open-Vocabulary Semantic Segmentation
Zhen Yao, Xin Li, Taotao Jing +2
Open-vocabulary semantic segmentation aims to assign labels to every pixel in an image based on text labels. Existing approaches typically utilize vision-language models (VLMs), su…
VLMs Guided Interpretable Decision Making for Autonomous Driving
Xin Hu, Taotao Jing, Renran Tian +1
Recent advancements in autonomous driving (AD) have explored the use of vision-language models (VLMs) within visual question answering (VQA) frameworks for direct driving decision-…
iBARLE: imBalance-Aware Room Layout Estimation
Taotao Jing, Lichen Wang, Naji Khosravan +4
Room layout estimation predicts layouts from a single panorama. It requires datasets with large-scale and diverse room shapes to train the models. However, there are significant im…
PSI: A Benchmark for Human Interpretation and Response in Traffic Interactions
Taotao Jing, Tina Chen, Renran Tian +5
Accurately modeling pedestrian intention and understanding driver decision-making processes are critical for the development of safe and socially aware autonomous driving systems.…
Towards Novel Target Discovery Through Open-Set Domain Adaptation
Taotao Jing, Hongfu Liu, Zhengming Ding
Open-set domain adaptation (OSDA) considers that the target domain contains samples from novel categories unobserved in external source domain. Unfortunately, existing OSDA methods…
Towards Fair Knowledge Transfer for Imbalanced Domain Adaptation
Taotao Jing, Bingrong Xu, Jingjing Li +1
Domain adaptation (DA) becomes an up-and-coming technique to address the insufficient or no annotation issue by exploiting external source knowledge. Existing DA algorithms mainly…
Adversarial Dual Distinct Classifiers for Unsupervised Domain Adaptation
Taotao Jing, Zhengming Ding
Unsupervised Domain adaptation (UDA) attempts to recognize the unlabeled target samples by building a learning model from a differently-distributed labeled source domain. Conventio…
Adaptively-Accumulated Knowledge Transfer for Partial Domain Adaptation
Taotao Jing, Haifeng Xia, Zhengming Ding
Partial domain adaptation (PDA) attracts appealing attention as it deals with a realistic and challenging problem when the source domain label space substitutes the target domain.…
Discriminative Cross-Domain Feature Learning for Partial Domain Adaptation
Taotao Jing, Ming Shao, Zhengming Ding
Partial domain adaptation aims to adapt knowledge from a larger and more diverse source domain to a smaller target domain with less number of classes, which has attracted appealing…
EV-Action: Electromyography-Vision Multi-Modal Action Dataset
Lichen Wang, Bin Sun, Joseph Robinson +2
Multi-modal human action analysis is a critical and attractive research topic. However, the majority of the existing datasets only provide visual modalities (i.e., RGB, depth and s…