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Tian Dong

6 papers hereh-index 5163 citations19 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author4

Across the 6 of 6 papers where every author was matched, so the position is known.

fields
  • cs.CR4
  • cs.LG2
same name
  • Tian Dong — 13 papers, h 10
  • Tian Dong — 8 papers, h 4
  • Tian Dong — 3 papers, h 2
  • Tian Dong — 3 papers, h 3
  • Tian Dong — 1 paper, h 3
  • Tian Dong — 1 paper, h 10

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedThe Philosopher's Stone: Trojaning Plugins of Large Language Models

3 citations · 6 across the 5 of their papers we have counts for

collaborators
Showing cs.CRShow all

4 papers · 1 filter

cs.CR2026

EmbTracker: Traceable Black-box Watermarking for Federated Language Models

Haodong Zhao, Jinming Hu, Yijie Bai +6

Federated Language Model (FedLM) allows a collaborative learning without sharing raw data, yet it introduces a critical vulnerability, as every untrustworthy client may leak the re…

cs.CR2025

Depth Gives a False Sense of Privacy: LLM Internal States Inversion

Tian Dong, Yan Meng, Shaofeng Li +3

Large Language Models (LLMs) are increasingly integrated into daily routines, yet they raise significant privacy and safety concerns. Recent research proposes collaborative inferen…

cs.CR2024★ 2 cited

Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning

Hongsheng Hu, Shuo Wang, Tian Dong +1

Machine unlearning has become a promising solution for fulfilling the "right to be forgotten", under which individuals can request the deletion of their data from machine learning…

cs.CR2023★ 3 cited

The Philosopher's Stone: Trojaning Plugins of Large Language Models

Tian Dong, Minhui Xue, Guoxing Chen +5

Open-source Large Language Models (LLMs) have recently gained popularity because of their comparable performance to proprietary LLMs. To efficiently fulfill domain-specialized task…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.