1 citations · 1 across the 28 of their papers we have counts for
30 papers
FASA: Feedback-Aware Sampling Adaptation for Efficient Diffusion-Based VLA Models
Yuchen Han, Jianhan Wu, Xiaoyang Qu +3
Diffusion-based Vision-Language-Action (VLA) models achieve strong performance in embodied tasks, but their iterative sampling imposes heavy computational and memory-access cost, b…
ProbPlug: A Plugin Uncertainty Network for Reliable Confidence in LLM Binary Classification
Jianzong Wang, Chuhang Liu, Botao Zhao +6
Large language models (LLMs) have achieved strong performance across a broad range of classification settings, yet the reliability of their predictions remains a major obstacle to…
DIVA: Harnessing the Representation Divergence in Unified Multimodal Models for Mutual Reinforcement
Renjie Lu, Xulong Zhang, Xiaoyang Qu +2
Unified Multimodal models (UMMs) built on a single architecture have shown impressive performance in both understanding and generation. We identify a fundamental challenge that lie…
WindowQuant: Mixed-Precision KV Cache Quantization based on Window-Level Similarity for VLMs Inference Optimization
Wei Tao, Xiaoyang Qu, Peiqiang Wang +4
Recently, video language models (VLMs) have been applied in various fields. However, the visual token sequence of the VLM is too long, which may cause intolerant inference latency…
Evolvable Embodied Agent for Robotic Manipulation via Long Short-Term Reflection and Optimization
Jianzong Wang, Botao Zhao, Yayun He +2
Achieving general-purpose robotics requires empowering robots to adapt and evolve based on their environment and feedback. Traditional methods face limitations such as extensive tr…
From Inheritance to Saturation: Disentangling the Evolution of Visual Redundancy for Architecture-Aware MLLM Inference Acceleration
Jiaqi Shi, Yuechan Li, Xulong Zhang +2
High-resolution Multimodal Large Language Models (MLLMs) face prohibitive computational costs during inference due to the explosion of visual tokens. Existing acceleration strategi…
VLA-InfoEntropy: A Training-Free Vision-Attention Information Entropy Approach for Vision-Language-Action Models Inference Acceleration and Success
Chuhang Liu, Yayun He, Zuheng Kang +2
Vision-Language-Action (VLA) models integrate visual perception, language understanding, and action decision-making for cross-modal semantic alignment, exhibiting broad application…
Confusion-Aware In-Context-Learning for Vision-Language Models in Robotic Manipulation
Yayun He, Zuheng Kang, Botao Zhao +3
Vision-language models (VLMs) have significantly improved the generalization capabilities of robotic manipulation. However, VLM-based systems often suffer from a lack of robustness…
Vista: Scene-Aware Optimization for Streaming Video Question Answering under Post-Hoc Queries
Haocheng Lu, Nan Zhang, Wei Tao +4
Streaming video question answering (Streaming Video QA) poses distinct challenges for multimodal large language models (MLLMs), as video frames arrive sequentially and user queries…
From Knowing to Doing Precisely: A General Self-Correction and Termination Framework for VLA models
Wentao Zhang, Aolan Sun, Wentao Mo +3
While vision-language-action (VLA) models for embodied agents integrate perception, reasoning, and control, they remain constrained by two critical weaknesses: first, during graspi…
Attention-weighted Centered Kernel Alignment for Knowledge Distillation in Large Audio-Language Models Applied to Speech Emotion Recognition
Qingran Yang, Botao Zhao, Zuheng Kang +7
The emergence of Large Audio-Language Models (LALMs) has advanced Speech Emotion Recognition (SER), but their size limits deployment in resource-constrained environments. While Kno…
MiTa: A Hierarchical Multi-Agent Collaboration Framework with Memory-integrated and Task Allocation
XiaoJie Zhang, JianHan Wu, Xiaoyang Qu +1
Recent advances in large language models (LLMs) have substantially accelerated the development of embodied agents. LLM-based multi-agent systems mitigate the inefficiency of single…
Triage: Hierarchical Visual Budgeting for Efficient Video Reasoning in Vision-Language Models
Anmin Wang, Nan Zhang, Wei Tao +4
Vision-Language Models (VLMs) face significant computational challenges in video processing due to massive data redundancy, which creates prohibitively long token sequences. To add…
MIRRORTALK: Forging Personalized Avatars Via Disentangled Style and Hierarchical Motion Control
Renjie Lu, Xulong Zhang, Xiaoyang Qu +2
Synthesizing personalized talking faces that uphold and highlight a speaker's unique style while maintaining lip-sync accuracy remains a significant challenge. A primary limitation…
CARE: Multi-Task Pretraining for Latent Continuous Action Representation in Robot Control
Jiaqi Shi, Xulong Zhang, Xiaoyang Qu +1
Recent advances in Vision-Language-Action (VLA) models have shown promise for robot control, but their dependence on action supervision limits scalability and generalization. To ad…
Federated Domain Generalization with Domain-specific Soft Prompts Generation
Jianhan Wu, Xiaoyang Qu, Zhangcheng Huang +1
Prompt learning has become an efficient paradigm for adapting CLIP to downstream tasks. Compared with traditional fine-tuning, prompt learning optimizes a few parameters yet yields…
EMO-RL: Emotion-Rule-Based Reinforcement Learning Enhanced Audio-Language Model for Generalized Speech Emotion Recognition
Pengcheng Li, Botao Zhao, Zuheng Kang +4
Although Large Audio-Language Models (LALMs) have exhibited outstanding performance in auditory understanding, their performance in affective computing scenarios, particularly in e…
Publicly Verifiable Private Information Retrieval Protocols Based on Function Secret Sharing
Lin Zhu, Lingwei Kong, Xin Ning +2
Private Information Retrieval (PIR) is a fundamental cryptographic primitive that enables users to retrieve data from a database without revealing which item is being accessed, the…
MoQAE: Mixed-Precision Quantization for Long-Context LLM Inference via Mixture of Quantization-Aware Experts
Wei Tao, Haocheng Lu, Xiaoyang Qu +4
One of the primary challenges in optimizing large language models (LLMs) for long-context inference lies in the high memory consumption of the Key-Value (KV) cache. Existing approa…
Hierarchical-Task-Aware Multi-modal Mixture of Incremental LoRA Experts for Embodied Continual Learning
Ziqi Jia, Anmin Wang, Xiaoyang Qu +2
Previous continual learning setups for embodied intelligence focused on executing low-level actions based on human commands, neglecting the ability to learn high-level planning and…
EPSpatial: Achieving Efficient and Private Statistical Analytics of Geospatial Data
Chuan Zhang, Xuhao Ren, Zhangcheng Huang +3
Geospatial data statistics involve the aggregation and analysis of location data to derive the distribution of clients within geospatial. The need for privacy protection in geospat…
RATE-Nav: Region-Aware Termination Enhancement for Zero-shot Object Navigation with Vision-Language Models
Junjie Li, Nan Zhang, Xiaoyang Qu +4
Object Navigation (ObjectNav) is a fundamental task in embodied artificial intelligence. Although significant progress has been made in semantic map construction and target directi…
BAGNet: A Boundary-Aware Graph Attention Network for 3D Point Cloud Semantic Segmentation
Wei Tao, Xiaoyang Qu, Kai Lu +3
Since the point cloud data is inherently irregular and unstructured, point cloud semantic segmentation has always been a challenging task. The graph-based method attempts to model…
MADLLM: Multivariate Anomaly Detection via Pre-trained LLMs
Wei Tao, Xiaoyang Qu, Kai Lu +3
When applying pre-trained large language models (LLMs) to address anomaly detection tasks, the multivariate time series (MTS) modality of anomaly detection does not align with the…