18 citations · 59 across the 42 of their papers we have counts for
47 papers
Language2Drive: Do Vision-Language-Action Models Really Follow the Instructions in Autonomous Driving?
Zihan You, Zehua Fan, Wenqi Lyu +19
Recent Vision-Language-Action (VLA) models increasingly use natural-language instructions to condition autonomous driving behavior. Yet existing closed-loop benchmarks primarily me…
Prime-EVC: One-Step Expressive Emotional Voice Conversion via Emotion-Primed Flow Matching
Yu Pan, Xiaojuan Cai, Liang Zhang +7
Recent diffusion- and conditional flow matching (CFM)-based emotional voice conversion (EVC) systems achieve strong conversion quality. However, they typically rely on multiple sam…
StageWAM: Joint-Embedding Stage Prediction for World-Action Models in Robot Manipulation
Xiao Liu, Yuguang Yang, Xi Wang +6
Generalist robot policies aim to map multimodal observations and linguistic task instructions to actions across diverse tasks. However, existing methods typically represent the fut…
Adaptive-WAM: Quality-Guided Early-Exit Planning from Intermediate Video-Diffusion Features
Sining Ang, Yuguang Yang, Yan Wang
Large video diffusion models provide rich spatiotemporal priors for autonomous driving, but existing world-action models often inherit the cost of iterative future-video generation…
AudioScape-TTA: A Structured Soundscape Benchmark for Fine-Grained Text-to-Audio Evaluation
Jinting Wang, Yuguang Yang, Shengyu Li +4
Text-to-audio (TTA) generation has recently achieved remarkable progress in synthesizing realistic audio from natural language descriptions. However, determining whether generated…
InfraNet: Quality-Aware RGB Guidance for Efficient Infrared Object Detection
Zichao Feng, Haodong Zhu, Jingying Yang +8
Robust object detection under adverse visual conditions remains a long-standing challenge for multi-modal perception systems. Existing fusion-based methods typically require both R…
Teaching Vision-Language-Action Models What to See and Where to Look
Yuguang Yang, Canyu Chen, Zhewen Tan +10
Vision-Language-Action (VLA) models have emerged as a promising paradigm for end-to-end autonomous driving. However, existing VLAs' training relies heavily on text-centric visual q…
CL-CLIP: CLIP-Based Continual Learning Framework with Cost-Volume Category Decoupling for Object Detection
Zihan Liu, Yuguang Yang, Shengjie Su +5
Continual Object Detection (COD) requires a detector to acquire new categories over time while preserving previously learned ones. This goal is closely related to open-vocabulary d…
AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following
Haitao Li, Tian Tan, Yuguang Yang +2
The rapid advancement of instruction-guided audio generation has highlighted the critical need for robust alignment evaluation. Current automated evaluation methods heavily rely on…
SURGE: Surrogate Gradient Adaptation in Binary Neural Networks
Haoyu Huang, Boyu Liu, Linlin Yang +6
The training of Binary Neural Networks (BNNs) is fundamentally based on gradient approximation for non-differentiable binarization operations (e.g., sign function). However, prevai…
CLOVER: Closed-Loop Value Estimation and Ranking for End-to-End Autonomous Driving Planning
Sining Ang, Yuguang Yang, Canyu Chen +1
End-to-end autonomous driving planners are commonly trained by imitating a single logged trajectory, yet evaluated by rule-based planning metrics that measure safety, feasibility,…
TMD-Bench: A Multi-Level Evaluation Paradigm for Music-Dance Co-Generation
Xiaoda Yang, Majun Zhang, Changhao Pan +10
Unified audio-visual generation is rapidly gaining industrial and creative relevance, enabling applications in virtual production and interactive media. However, when moving from g…
Learning domain-invariant features through channel-level sparsification for Out-Of Distribution Generalization
Haoran Pei, Yuguang Yang, Kexin Liu +2
Out-of-Distribution (OOD) generalization has become a primary metric for evaluating image analysis systems. Since deep learning models tend to capture domain-specific context, they…
AMLRIS: Alignment-aware Masked Learning for Referring Image Segmentation
Tongfei Chen, Shuo Yang, Yuguang Yang +7
Referring Image Segmentation (RIS) aims to segment the object in an image uniquely referred to by a natural language expression. However, RIS training often contains hard-to-align…
Devil is in Narrow Policy: Unleashing Exploration in Driving VLA Models
Canyu Chen, Yuguang Yang, Zhewen Tan +10
We identify a fundamental Narrow Policy limitation undermining the performance of autonomous VLA models, where driving Imitation Learning (IL) tends to collapse exploration and lim…
From Representational Complementarity to Dual Systems: Synergizing VLM and Vision-Only Backbones for End-to-End Driving
Sining Ang, Yuguang Yang, Chenxu Dang +8
Vision-Language-Action (VLA) driving augments end-to-end (E2E) planning with language-enabled visual backbones, but how VLM representations differ from vision-only encoders after p…
OpenAI GPT-5 System Card
Aaditya Singh, Adam Fry, Adam Perelman +483
This is the system card published alongside the OpenAI GPT-5 launch, August 2025. GPT-5 is a unified system with a smart and fast model that answers most questions, a deeper reason…
Causally Guided Gaussian Perturbations for Out-Of-Distribution Generalization in Medical Imaging
Haoran Pei, Yuguang Yang, Kexin Liu +1
Out-of-distribution (OOD) generalization remains a central challenge in deploying deep learning models to real-world scenarios, particularly in domains such as biomedical images, w…
WaveMamba: Wavelet-Driven Mamba Fusion for RGB-Infrared Object Detection
Haodong Zhu, Wenhao Dong, Linlin Yang +10
Leveraging the complementary characteristics of visible (RGB) and infrared (IR) imagery offers significant potential for improving object detection. In this paper, we propose WaveM…
Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method
Qingcheng Zhu, Yangyang Ren, Linlin Yang +6
Deploying large language models (LLMs) is challenging due to their massive parameters and high computational costs. Ultra low-bit quantization can significantly reduce storage and…
S2ST-Omni: Hierarchical Language-Aware SpeechLLM Adaptation for Multilingual Speech-to-Speech Translation
Yu Pan, Xiongfei Wu, Yuguang Yang +3
Despite recent advances in speech-to-speech translation (S2ST), it remains difficult to achieve both high translation accuracy and practical flexibility. In this paper, we present…
ClapFM-EVC: High-Fidelity and Flexible Emotional Voice Conversion with Dual Control from Natural Language and Speech
Yu Pan, Yanni Hu, Yuguang Yang +5
Despite great advances, achieving high-fidelity emotional voice conversion (EVC) with flexible and interpretable control remains challenging. This paper introduces ClapFM-EVC, a no…
Prompt as Knowledge Bank: Boost Vision-language model via Structural Representation for zero-shot medical detection
Yuguang Yang, Tongfei Chen, Haoyu Huang +5
Zero-shot medical detection can further improve detection performance without relying on annotated medical images even upon the fine-tuned model, showing great clinical value. Rece…
Fine-grained Preference Optimization Improves Zero-shot Text-to-Speech
Jixun Yao, Yuguang Yang, Yu Pan +5
Integrating human feedback to align text-to-speech (TTS) system outputs with human preferences has proven to be an effective approach for enhancing the robustness of language model…