Yadan Luo

Senior Lecturer & DECRA at University of Queensland. PI of UQMM Lab. Researching generalization challenges in 2D/3D autonomous driving and beyond🤖.

[Yadan Luo @Yadan_Luo]

Check out my latest article: 🎉 [CVPR 2026] 6 Papers accepted from UQMM Lab: Test-Time Outdoor 3DV, E2E Driving & VLA Agents https://t.co/0lVwzlYqxq via @LinkedIn

[Yadan Luo @Yadan_Luo]

A practical LaTeX writing guide is available to help PhD students quickly self-check common submission mistakes and reduce repetitive work.
✅ Prompt LLMs for auto-checking
✅ Fast, easy, and effective!
🚪 Portal: https://t.co/VuFDoGqf3B
Welcome to read, share, and contribute! 🙏

[Zixin Wang @ZixinWang_AU]

Excited to share that our latest paper on training-free adaptation for CLIP-style VLMs has been accepted to #ICCV2025! We propose Token Condensation as Adaptation, which improves performance with up to 48.9% lower compute — no training, no tuning!
Check it out 👇

[Bhaskar Mitra | ভাস্কর মিত্র @UnderdogGeek]

⏰ Upcoming SIGIR-AP 2025 Deadlines!
Abstract due: July 1
Paper due: July 8

Soliciting research, resource, reproducibility, perspective, and industry papers. Had a paper rejected at SIGIR'25? Resubmit as SIGIR-RR or regular submission!

More info: https://t.co/QpJtYHE99T

[Yadan Luo @Yadan_Luo]

@DrZhenghaoChen 🤓

[Yadan Luo @Yadan_Luo]

🔍 [3/3] Color-Oriented Redundancy Reduction in Dataset Distillation
📍 Join us at the poster: West Ballroom A-D #7309
🗓️ Thu, Dec 12 | 11 a.m. PST — 2 p.m. PST
Official page: https://t.co/1lurWgpUMb

[Yadan Luo @Yadan_Luo]

Also happy to present 2 more data-centric works on retrieval and dataset distillation! 🌟
🔍 [2/3] Exploiting Descriptive Completeness Prior for Cross-Modal Hashing with Incomplete Labels
📍East Exhibit Hall A-C #1400
🗓️ Wed, Dec 11 | 11 a.m. — 2 p.m. PST
https://t.co/Ukm5s6nEXe

[Yadan Luo @Yadan_Luo]

Recoding and paper can be found here: https://t.co/B6izf598AP

[Yadan Luo @Yadan_Luo]

Excited to share our @NeurIPSConf work on unsupervised prompt expansion and stop by to meet our first author! 🚀
🔍 [1/3] DiPEx: Dispersing Prompt Expansion for Class-Agnostic Object Detection (by Jason Lim)
📍 Poster: East Exhibit Hall A-C #1300
🗓️ Fri, Dec 13 | 11 a.m.-2 p.m

[Yadan Luo @Yadan_Luo]

[3/3] Our solution? DiPEx, a self-supervised prompting solution for VLMs like GroundingDiNO progressively learns to expand a set of distinct, non-overlapping hyperspherical prompts to enhance recall rates. It shows +20% AR gain over existing prompting and SAM on COCO and LVIS! 🔥

[Michael Black @Michael_J_Black]

Young scientists regularly ask me for career advice. Academia or industry? Big company or startup? US or Europe?  Good scientists in AI disciplines are fortunate to have many choices. But choosing can be stressful. I always give the same advice. 1/10

[ACM Multimedia @ACMMM24]

The #ACMMM24 website is now live! ACM MM is happening in Melbourne, Australia from 28 October to 1 November 2024. If you would like to attend, present or exhibit at the world's premier conference in multimedia, submit an expression of interest today: https://t.co/6nwySFb5xp

[Australian Institute for Machine Learning @TheAIML]

#InMemoryOfDrYifanLiu #GoneTooSoon

[Qi Wu @QiWu_AIML]

Yifan was not only a gifted researcher but also a wonderful friend. Her passion for knowledge was truly inspiring. She will be deeply missed. My heartfelt condolences go out to her family and loved ones. 💔 #InMemoryOfYIfan

[Yadan Luo @Yadan_Luo]

[UQ Data Science Seminar] Wed, 17/05/2023 - 13:00 https://t.co/nQQAdOShxL

[Yadan Luo @Yadan_Luo]

[UQ Data Science Seminar] Wed, 10/05/2023 - 13:00 - Building Experiment Tracking at Scale with Weights & Biases - https://t.co/4HCc8BqAAI

[Yadan Luo @Yadan_Luo]

[UQ Data Science Seminar] Wed, 03/05/2023 - 10:00 - SEINE: SEgment-based Indexing for NEural Information Retrieval - https://t.co/AB8GS9DxUY

[Yadan Luo @Yadan_Luo]

[UQ Data Science Seminar] Wed, 22/03/2023 - 13:00 - The Human Quotient for Better AI Systems - https://t.co/p89ibd0ICz

[Yadan Luo @Yadan_Luo]

[UQ Data Science Seminar] Wed, 15/03/2023 - 13:00 - Multi-Domain Few-Shot Image Classification - https://t.co/21rR5f96x5