Yan Gao

Orcid: 0000-0001-7922-9788

Affiliations:
  • Flower Labs, Hamburg, Germany
  • University of Cambridge, Department of Computer Science and Technology, Cambridge, UK


According to our database1, Yan Gao authored at least 25 papers between 2018 and 2025.

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

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2025
FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models.
CoRR, June, 2025

Scaling Auditory Cognition via Test-Time Compute in Audio Language Models.
CoRR, March, 2025

DEPT: Decoupled Embeddings for Pre-training Language Models.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Photon: Federated LLM Pre-Training.
CoRR, 2024

The Future of Large Language Model Pre-training is Federated.
CoRR, 2024

FedAnchor: Enhancing Federated Semi-Supervised Learning with Label Contrastive Loss for Unlabeled Clients.
CoRR, 2024

Privacy-Preserving Federated Learning using Flower Framework.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Breaking Physical and Linguistic Borders: Multilingual Federated Prompt Tuning for Low-Resource Languages.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023
A First Look into the Carbon Footprint of Federated Learning.
J. Mach. Learn. Res., 2023

High-throughput Simulation of Federated Learning via Resource-Aware Client Placement.
CoRR, 2023

L-DAWA: Layer-wise Divergence Aware Weight Aggregation in Federated Self-Supervised Visual Representation Learning.
Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023

2022
Federated Learning for Inference at Anytime and Anywhere.
CoRR, 2022

Match to Win: Analysing Sequences Lengths for Efficient Self-Supervised Learning in Speech and Audio.
Proceedings of the IEEE Spoken Language Technology Workshop, 2022

Federated Self-supervised Speech Representations: Are We There Yet?
Proceedings of the 23rd Annual Conference of the International Speech Communication Association, 2022

ZeroFL: Efficient On-Device Training for Federated Learning with Local Sparsity.
Proceedings of the Tenth International Conference on Learning Representations, 2022

End-to-End Speech Recognition from Federated Acoustic Models.
Proceedings of the IEEE International Conference on Acoustics, 2022

Federated Self-supervised Learning for Video Understanding.
Proceedings of the Computer Vision - ECCV 2022, 2022

2021
Can You See It?: Good, So We Can Sense It!
GetMobile Mob. Comput. Commun., 2021

SpeechBrain: A General-Purpose Speech Toolkit.
CoRR, 2021

End-to-End Speech Recognition from Federated Acoustic Models.
CoRR, 2021

On-device Federated Learning with Flower.
CoRR, 2021

Distilling Knowledge from Ensembles of Acoustic Models for Joint CTC-Attention End-to-End Speech Recognition.
Proceedings of the IEEE Automatic Speech Recognition and Understanding Workshop, 2021

2020
IMUTube: Automatic Extraction of Virtual on-body Accelerometry from Video for Human Activity Recognition.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2020

2019
Towards Reliable, Automated General Movement Assessment for Perinatal Stroke Screening in Infants Using Wearable Accelerometers.
Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2019

2018
Robust Cross-View Gait Identification with Evidence: A Discriminant Gait GAN (DiGGAN) Approach on 10000 People.
CoRR, 2018


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