I am Yiran Qiao, a PhD student in Computer Science at Case Western Reserve University, where I am fortunate to be advised by Prof. Jing Ma. Prior to that, I received my M.S. in Electrical and Computer Engineering from The Ohio State University and my B.Eng. in Electrical Engineering from Xi’an Jiaotong University.
My research centers on diffusion models and flow matching, along with their applications to world models and 3D generation. I am also interested in causal inference and adversarial attacks and defenses.
🔥 News
- 2026.08: 🎉 Our paper NS-Copilot is accepted to EMNLP 2026 Findings!
- 2026.06: 🎉 Our paper DefenseSplat is accepted to ECCV 2026!
- 2026.05: 🎉 Our paper SAIF is accepted to ECML PKDD 2026!
- 2026.04: 🎉 Our paper YesBut-v2 is accepted to TPAMI!
- 2025.09: 🎉 Our paper Segment then Splat is accepted to NeurIPS 2025!
- 2024.12: 🎉 Our paper GLEAN is accepted to AAAI 2025!
- 2024.09: 🎉 Our paper YesBut is accepted to NeurIPS 2024 (Oral)!
📝 Selected Publications

Valerant: An Automatic NaVigAbLE Game Map GeneratoR via Action-CoNditioned World Model ExploraTion
Yiran Qiao, Feng Wang, Jing Ma
- VALERANT builds a navigable 3D game map from a single image by rolling out candidate actions through an action-conditioned world model, reconstructing each rollout with SLAM, and committing the step that scores best.

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion
Yiran Qiao, Yiren Lu, Yunlai Zhou, Disheng Liu, Linlin Hou, Rui Yang, Yu Yin, Jing Ma
- We introduce DiLAST: 2D Diffusion-based Latent Awakening for 3D Style Transfer. It guides a 3D generator’s structured latents with a pretrained 2D diffusion teacher, transferring styles well outside the generator’s training distribution and plugging into existing backbones unchanged.

AdvSplat: Adversarial Attacks on Feed-Forward Gaussian Splatting Models
Yiran Qiao, Yiren Lu, Yunlai Zhou, Rui Yang, Linlin Hou, Yu Yin, Jing Ma
- AdvSplat gives the first systematic account of adversarial attacks on feed-forward 3DGS, with two query-efficient black-box algorithms that parameterize imperceptible pixel perturbations in the frequency domain and disrupt reconstruction without access to model internals.

DefenseSplat: Enhancing the Robustness of 3D Gaussian Splatting via Frequency-Aware Filtering
Yiran Qiao, Yiren Lu, Yunlai Zhou, Rui Yang, Linlin Hou, Yu Yin, Jing Ma
- DefenseSplat filters poisoned input views in the wavelet domain and regularizes Gaussian scale during training, restoring 3DGS fidelity under attack without adversarial training or clean ground truth.
💼 Internship Experience
Supervisor: Prof. Xiong Wu
Topic: Distributed Energy Storage in Smart Grids
📖 Education
🎖 Awards
🤝 Service
Conference Reviewer: NeurIPS 2025, ICLR 2026, ICML 2026, CVPR 2026, NeurIPS 2026, ICLR 2027
Teaching Assistant: CSDS 452 Causality and Machine Learning, CSDS 435 Data Mining, CSDS 433 Database Systems

