Search Results for author:
Found 12 papers, 6 papers with code
CASIA at SemEval-2022 Task 11: Chinese Named Entity Recognition for Complex and Ambiguous Entities
This paper describes our approach to develop a complex named entity recognition system in SemEval 2022 Task 11: MultiCoNER Multilingual Complex Named Entity Recognition, Track 9 - Chinese.
CASIA@SMM4H’22: A Uniform Health Information Mining System for Multilingual Social Media Texts
This paper presents a description of our system in SMM4H-2022, where we participated in task 1a, task 4, and task 6 to task 10.
DiffPAD: Denoising Diffusion-based Adversarial Patch Decontamination
In the ever-evolving adversarial machine learning landscape, developing effective defenses against patch attacks has become a critical challenge, necessitating reliable solutions to safeguard real-world AI systems.
Advancing Open-Set Domain Generalization Using Evidential Bi-Level Hardest Domain Scheduler
In this paper, we observe that an adaptive domain scheduler benefits more in OSDG compared with prefixed sequential and random domain schedulers.
Referring Atomic Video Action Recognition
Since these existing methods underperform on RAVAR, we introduce RefAtomNet -- a novel cross-stream attention-driven method specialized for the unique challenges of RAVAR: the need to interpret a textual referring expression for the targeted individual, utilize this reference to guide the spatial localization and harvest the prediction of the atomic actions for the referring person.
AutoRAG-HP: Automatic Online Hyper-Parameter Tuning for Retrieval-Augmented Generation
Recent advancements in Large Language Models have transformed ML/AI development, necessitating a reevaluation of AutoML principles for the Retrieval-Augmented Generation (RAG) systems.
EffiQA: Efficient Question-Answering with Strategic Multi-Model Collaboration on Knowledge Graphs
Finally, the exploration results are fed to LLMs for self-reflection to further improve the global planning and efficient KG exploration.
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
The FeTA Challenge 2022 was able to successfully evaluate and advance generalizability of multi-class fetal brain tissue segmentation algorithms for MRI and it continues to benchmark new algorithms.
SegRap2023: A Benchmark of Organs-at-Risk and Gross Tumor Volume Segmentation for Radiotherapy Planning of Nasopharyngeal Carcinoma
The precise delineation of Gross Tumor Volumes (GTVs) and Organs-At-Risk (OARs) is crucial in radiation treatment, directly impacting patient prognosis.
Component attention network for multimodal dance improvisation recognition
Motion analysis of improvised dance can be challenging due to its unique dynamics.
UM-CAM: Uncertainty-weighted Multi-resolution Class Activation Maps for Weakly-supervised Fetal Brain Segmentation
To this end, we propose a novel weakly-supervised method with image-level labels based on semantic features and context information exploration.
Semantic Segmentation of Panoramic Images Using a Synthetic Dataset
In addition, it has been shown that by using panoramic images with a 180 degree FoV as training data the model has better performance.
