Yixuan Qiao

According to our database1, Yixuan Qiao authored at least 22 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2025
Optimal Brain Iterative Merging: Mitigating Interference in LLM Merging.
CoRR, February, 2025

A multi-modal fusion model with enhanced feature representation for chronic kidney disease progression prediction.
Briefings Bioinform., January, 2025

2024
Revisiting Open World Object Detection.
IEEE Trans. Circuits Syst. Video Technol., May, 2024

2023
Biological knowledge graph-guided investigation of immune therapy response in cancer with graph neural network.
Briefings Bioinform., March, 2023

2022
PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stage Ranking.
CoRR, 2022

CandidateDrug4Cancer: An Open Molecular Graph Learning Benchmark on Drug Discovery for Cancer.
CoRR, 2022

Multi-modality artificial intelligence in digital pathology.
Briefings Bioinform., 2022

Implementation of one-time editable blockchain chameleon hash function construction scheme.
Proceedings of the IEEE International Conference on Trust, 2022

HCL: Improving Graph Representation with Hierarchical Contrastive Learning.
Proceedings of the Semantic Web - ISWC 2022, 2022

PA Ph&Tech at SemEval-2022 Task 11: NER Task with Ensemble Embedding from Reinforcement Learning.
Proceedings of the 16th International Workshop on Semantic Evaluation, SemEval@NAACL 2022, 2022

SFE-AI at SemEval-2022 Task 11: Low-Resource Named Entity Recognition using Large Pre-trained Language Models.
Proceedings of the 16th International Workshop on Semantic Evaluation, SemEval@NAACL 2022, 2022

2021
Superpixel-Based Building Damage Detection from Post-earthquake Very High Resolution Imagery Using Deep Neural Networks.
CoRR, 2021

Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks.
CoRR, 2021

Winner Team Mia at TextVQA Challenge 2021: Vision-and-Language Representation Learning with Pre-trained Sequence-to-Sequence Model.
CoRR, 2021

An effective self-supervised framework for learning expressive molecular global representations to drug discovery.
Briefings Bioinform., 2021

PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stageRankingtrack: DL.
Proceedings of the Thirtieth Text REtrieval Conference, 2021

Pairwise Half-graph Discrimination: A Simple Graph-level Self-supervised Strategy for Pre-training Graph Neural Networks.
Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

2020
Learn molecular representations from large-scale unlabeled molecules for drug discovery.
CoRR, 2020

PASH at TREC 2020 Deep Learning Track: Dense Matching for Nested Ranking.
Proceedings of the Twenty-Ninth Text REtrieval Conference, 2020

A Multiple Models Ensembling Method in TREC Deep Learning.
Proceedings of the Twenty-Ninth Text REtrieval Conference, 2020

2019
Collaborative Evidential Clustering.
Proceedings of the Fuzzy Techniques: Theory and Applications, 2019

2018
An Expert System for Diagnosis and Treatment of Hypertension Based on Ontology.
Proceedings of the Bio-inspired Computing: Theories and Applications, 2018


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