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Merge pull request #2 from reds-lab/update-pubs
add july 2025 pubs
2 parents 1f4cfe4 + aa5b833 commit 393b97b

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-29
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-----BEGIN OPENSSH PRIVATE KEY-----
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b3BlbnNzaC1rZXktdjEAAAAACmFlczI1Ni1jdHIAAAAGYmNyeXB0AAAAGAAAABDJ5G2z2f
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d+pp5gEMhHrWvaAAAAGAAAAAEAAAAzAAAAC3NzaC1lZDI1NTE5AAAAIATQ1rJBeSc7UCyB
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DQl8TJbPptxfS2kOubrA2mpAUYUVAAAAoNQW3f9GKEY4elP6p6j8APe+w1ZYkwSwAjdcFA
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cqbKjnj+SgTnOUrMEYL77XEmn69JPlDL6r+fgpz/eWdwdcsM9HNLDmSTqTqfAHsW2v3CNP
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oYuMZdYDgteKS6LQYkV7pgHZ7fQy+vKlsV5CC3XWMYzFZ9qHFyfglvFHgrrhx+qNPcxOlr
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xeDT/TqoHU+wzWFDfQ1CA4SWw5aO3HUA8BRFE=
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-----END OPENSSH PRIVATE KEY-----
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ssh-ed25519 AAAAC3NzaC1lZDI1NTE5AAAAIATQ1rJBeSc7UCyBDQl8TJbPptxfS2kOubrA2mpAUYUV ruoxijia@vt.edu

src/assets/content/People/People.ts

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@@ -54,28 +54,6 @@ export const peopleData: PeopleGroup[] = [
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{
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title: "PhD Students",
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people: [
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{
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profileImage: yiZengImage,
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name: "Yi Zeng",
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details: "Yi's research focuses on ensuring AI benefits humanity through advancements in AI safety, AI security, and responsible AI.",
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links: {
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// website: "https://yizeng.com",
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// github: "https://github.com/yizeng",
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// googleScholar: "https://scholar.google.com/citations?user=jkl012",
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// linkedin: "https://www.linkedin.com/in/yi-zeng",
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// twitter: "https://twitter.com/yizeng"
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}
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},
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{
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profileImage: siChenImage,
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name: "Si Chen",
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details: "Si's research focuses on enhancing trustworthiness and privacy of AI by developing defenses against, and analyzing attacks on, AI models.",
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links: {
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website: "https://sichen21.netlify.app/",
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linkedin: "https://www.linkedin.com/in/si-chen-1805001a1/",
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twitter: "https://twitter.com/si_chen0921"
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}
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},
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{
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profileImage: myeongseobKoImage,
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name: "Myeongseob Ko",
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details: "Tran's research focuses on understanding the vulnerabilities of AI models and advancing the robustness of AI systems against adversarial threats.",
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links: {}
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},
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]
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},
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{
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title: "MS Students",
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people: [
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{
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profileImage: mahavirDabasImage,
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name: "Mahavir Dabas",
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{
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title: "Past Alumni",
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people: [
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{
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profileImage: yiZengImage,
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name: "Yi Zeng",
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details: "Ph.D. student, 2021-2025. (Next: TikTok)",
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links: {googleScholar: "https://scholar.google.com/citations?user=slUNmHQAAAAJ&hl=en"}
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},
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{
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profileImage: siChenImage,
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name: "Si Chen",
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details: "Ph.D. student, 2020-2025. (Next: Salesforce)",
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links: {googleScholar: "https://scholar.google.com/citations?hl=en&user=pJvSiBgAAAAJ"}
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},
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{
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profileImage: minzhouPanImage,
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name: "Minzhou Pan",

src/assets/content/Publications/2025pubs.ts

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const publications = [
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{
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"title": "AutoScale: Scale-Aware Data Mixing for Pre-Training LLMs",
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"authors": "Feiyang Kang, Yifan Sun, Bingbing Wen, Si Chen, Dawn Song, Rafid Mahmood, Ruoxi Jia",
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"conference": "Conference on Language Modeling (COLM), 2025",
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"arxiv": "https://arxiv.org/abs/2407.20177",
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"highlights": []
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},
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{
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"title": "Data-Centric Human Preference with Rationales for Direct Preference Alignment",
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"authors": "Hoang Anh Just, Ming Jin, Anit Kumar Sahu, Huy Phan, Ruoxi Jia",
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"conference": "Conference on Language Modeling (COLM), 2025",
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"arxiv": "https://arxiv.org/abs/2407.14477",
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"highlights": []
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},
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{
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"title": "LLM Can be a Dangerous Persuader: Empirical Study of Persuasion Safety in Large Language Models",
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"authors": "Minqian Liu, Zhiyang Xu, Xinyi Zhang, Heajun An, Sarvech Qadir, Qi Zhang, Pamela J. Wisniewski, Jin-Hee Cho, Sang Won Lee, Ruoxi Jia, Lifu Huang",
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"conference": "Conference on Language Modeling (COLM), 2025",
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"arxiv": "https://arxiv.org/abs/2504.10430",
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"highlights": []
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},
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{
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"title": "NaviDet: Efficient Input-level Backdoor Detection on Text-to-Image Synthesis via Neuron Activation Variation",
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"authors": "Shengfang Zhai, Jiajun Li, Yue Liu, Huanran Chen, Zhihua Tian, Wenjie Qu, Qingni Shen, Ruoxi Jia, Yinpeng Dong, Jiaheng Zhang",
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"conference": "International Conference on Computer Vision (ICCV), 2025",
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"arxiv": "https://arxiv.org/abs/2503.06453",
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"highlights": []
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},
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{
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"title": "Model Residuals as Shields: A Two-Level Formulation to Defend Smart Grids From Poisoning Attacks",
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"authors": "Tung-Wei Lin, Padmaksha Roy, Yi Zeng, Ming Jin, Ruoxi Jia, Chen-Ching Liu, Alberto Sangiovanni-Vincentelli",
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"conference": "IEEE Internet of Things Journal, 2025",
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"arxiv": "https://waynelin567.github.io/files/res.pdf",
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"highlights": []
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},
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{
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"title": "Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning",
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"authors": "Mahavir Dabas, Si Chen, Charles Fleming, Ming Jin, Ruoxi Jia",
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"conference": "International Conference on Machine Learning (ICML), 2025",
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"arxiv": "",
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"arxiv": "https://arxiv.org/abs/2507.04250",
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"highlights": []
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},
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{

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