Publications (24)
THAT: Token-wise High-frequency Augmentation Transformer for Hyperspectral Pansharpening
Hongkun Jin, Hongcheng Jiang, Zejun Zhang +4
Transformer-based methods have demonstrated strong potential in hyperspectral pansharpening by modeling long-range dependencies. However, their effectiveness is often limited by re…
Component attention network for multimodal dance improvisation recognition
Jia Fu, Jiarui Tan, Wenjie Yin +2
Dance improvisation is an active research topic in the arts. Motion analysis of improvised dance can be challenging due to its unique dynamics. Data-driven dance motion analysis, i…
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
Kelly Payette, Céline Steger, Roxane Licandro +64
Segmentation is a critical step in analyzing the developing human fetal brain. There have been vast improvements in automatic segmentation methods in the past several years, and th…
A LN2-based cryogenic system prototype for future PandaX experiment
Xinbei Jiang, Li Zhao, Shaobo Wang +3
This paper describes results on R&D of an economical and efficient cryogenic system prototype for future liquid xenon detector. The test module of the prototype has a "cold head" a…
RLEP: Reinforcement Learning with Experience Replay for LLM Reasoning
Hongzhi Zhang, Jia Fu, Jingyuan Zhang +4
Reinforcement learning (RL) for large language models is an energy-intensive endeavor: training can be unstable, and the policy may gradually drift away from its pretrained weights…
Referring Atomic Video Action Recognition
Kunyu Peng, Jia Fu, Kailun Yang +8
We introduce a new task called Referring Atomic Video Action Recognition (RAVAR), aimed at identifying atomic actions of a particular person based on a textual description and the…
AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation
Jia Fu, Xiaoting Qin, Fangkai Yang +7
Recent advancements in Large Language Models have transformed ML/AI development, necessitating a reevaluation of AutoML principles for the Retrieval-Augmented Generation (RAG) syst…
Klear-AgentForge: Forging Agentic Intelligence through Posttraining Scaling
Qi Wang, Hongzhi Zhang, Jia Fu +12
Despite the proliferation of powerful agentic models, the lack of critical post-training details hinders the development of strong counterparts in the open-source community. In thi…
SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma
Xiangde Luo, Jia Fu, Yunxin Zhong +39
Radiation therapy is a primary and effective NasoPharyngeal Carcinoma (NPC) treatment strategy. The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is c…
Go Beyond Earth: Understanding Human Actions and Scenes in Microgravity Environments
Di Wen, Lei Qi, Kunyu Peng +9
Despite substantial progress in video understanding, most existing datasets are limited to Earth's gravitational conditions. However, microgravity alters human motion, interactions…
UM-CAM: Uncertainty-weighted Multi-resolution Class Activation Maps for Weakly-supervised Fetal Brain Segmentation
Jia Fu, Tao Lu, Shaoting Zhang +1
Accurate segmentation of the fetal brain from Magnetic Resonance Image (MRI) is important for prenatal assessment of fetal development. Although deep learning has shown the potenti…
RefAtomNet++: Advancing Referring Atomic Video Action Recognition using Semantic Retrieval based Multi-Trajectory Mamba
Kunyu Peng, Di Wen, Jia Fu +9
Referring Atomic Video Action Recognition (RAVAR) aims to recognize fine-grained, atomic-level actions of a specific person of interest conditioned on natural language descriptions…
Klear-CodeTest: Scalable Test Case Generation for Code Reinforcement Learning
Jia Fu, Xinyu Yang, Hongzhi Zhang +5
Precise, correct feedback is crucial for effectively training large language models (LLMs) in code reinforcement learning. However, synthesizing high-quality test cases remains a p…
Advances in Automated Fetal Brain MRI Segmentation and Biometry: Insights from the FeTA 2024 Challenge
Vladyslav Zalevskyi, Thomas Sanchez, Misha Kaandorp +67
Accurate fetal brain tissue segmentation and biometric analysis are essential for studying brain development in utero. The FeTA Challenge 2024 advanced automated fetal brain MRI an…
DeepSynth-Eval: Objectively Evaluating Information Consolidation in Deep Survey Writing
Hongzhi Zhang, Yuanze Hu, Tinghai Zhang +9
The evolution of Large Language Models (LLMs) towards autonomous agents has catalyzed progress in Deep Research. While retrieval capabilities are well-benchmarked, the post-retriev…
CLISC: Bridging clip and sam by enhanced cam for unsupervised brain tumor segmentation
Xiaochuan Ma, Jia Fu, Wenjun Liao +2
Brain tumor segmentation is important for diagnosis of the tumor, and current deep-learning methods rely on a large set of annotated images for training, with high annotation costs…
Diffusion-based Cumulative Adversarial Purification for Vision Language Models
Jia Fu, Yongtao Wu, Yihang Chen +5
Vision Language Models (VLMs) have shown remarkable capabilities in multimodal understanding, yet their susceptibility to adversarial perturbations poses a significant threat to th…
First Identification of New X-Ray Spectra of Mo39+, Mo40+, W43+, W44+ and W45+ on EAST
Fudi Wang, Dian Lu, Mingfeng Gu +27
New high-resolution x-ray spectra of Mo39+, Mo40+, W43+, W44+ and W45+ have been carefully confirmed for the first time by use of the x-ray imaging crystal spectrometer (XCS) in Ex…
Semantic Segmentation of Panoramic Images Using a Synthetic Dataset
Yuanyou Xu, Kaiwei Wang, Kailun Yang +2
Panoramic images have advantages in information capacity and scene stability due to their large field of view (FoV). In this paper, we propose a method to synthesize a new dataset…
EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphs
Zixuan Dong, Baoyun Peng, Yufei Wang +4
While large language models (LLMs) have shown remarkable capabilities in natural language processing, they struggle with complex, multi-step reasoning tasks involving knowledge gra…
SegRap2025: A Benchmark of Gross Tumor Volume and Lymph Node Clinical Target Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma
Jia Fu, Litingyu Wang, He Li +27
Accurate delineation of Gross Tumor Volume (GTV), Lymph Node Clinical Target Volume (LN CTV), and Organ-at-Risk (OAR) from Computed Tomography (CT) scans is essential for precise r…
DiffPAD: Denoising Diffusion-based Adversarial Patch Decontamination
Jia Fu, Xiao Zhang, Sepideh Pashami +2
In the ever-evolving adversarial machine learning landscape, developing effective defenses against patch attacks has become a critical challenge, necessitating reliable solutions t…
EReLiFM: Evidential Reliability-Aware Residual Flow Meta-Learning for Open-Set Domain Generalization under Noisy Labels
Kunyu Peng, Di Wen, Kailun Yang +9
Open-Set Domain Generalization (OSDG) aims to enable deep learning models to recognize unseen categories in new domains, which is crucial for real-world applications. Label noise h…
Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler
Kunyu Peng, Di Wen, Kailun Yang +6
In Open-Set Domain Generalization (OSDG), the model is exposed to both new variations of data appearance (domains) and open-set conditions, where both known and novel categories ar…