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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 3

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 2

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

publications

FPEdit: Robust LLM Fingerprinting through Localized Parameter Editing

Published in arXiv preprint, 2025

We introduce FPEdit, a novel framework that leverages knowledge editing to inject semantically coherent natural language fingerprints through sparse, targeted modifications to model weights, achieving 95-100% fingerprint retention under both full-parameter fine-tuning and parameter-efficient adaptation.

Recommended citation: Wang, S., Liu, C., Wang, Y., & Xu, L. (2025). "FPEdit: Robust LLM Fingerprinting through Localized Parameter Editing." arXiv preprint arXiv:2508.02092. https://arxiv.org/pdf/2508.02092

DiG: Differential Grounding for Enhancing Fine-Grained Perception in Multimodal Large Language Model

Published in CVPR 2026, 2025

We introduce DiG (Differential Grounding), a novel proxy task framework where MLLMs learn fine-grained perception by identifying and localizing all differences between similar image pairs, significantly improving performance across diverse visual perception benchmarks.

Recommended citation: Tao, Z., Wang, S., Hua, Y., Cao, H., & Xu, L. (2026). "DiG: Differential Grounding for Enhancing Fine-Grained Perception in Multimodal Large Language Model." Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). https://arxiv.org/pdf/2512.12633

talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

This is a description of a teaching experience. You can use markdown like any other post.

Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.