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README.md

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@@ -167,6 +167,8 @@ Methods for defending against backdoor attacks include:
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| Year | Conf./Jour. | Paper | Code Reporisty | Reproduced Reporisty |
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|------|-------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------|----------------------|
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| 2025 | FSE | [Eliminating Backdoors in Neural Code Models for Secure Code Understanding.](./papers_en/2025-FSE-EliBadCode.pdf) 🚩 | [![Octocat](./figures/github.svg)](https://github.com/wssun/EliBadCode) | |
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| 2025 | ICSE | [Show Me Your Code! Kill Code Poisoning: A Lightweight Method Based on Code Naturalness.](./papers_en/2025-ICSE-KILLBADCODE.pdf) 🚩 | [![Octocat](./figures/github.svg)](https://github.com/wssun/KillBadCode) | |
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| 2024 | TOSEM | [Poison Attack and Poison Detection on Deep Source Code Processing Models.](./papers_en/2024-TOSEM-Poison_Attack_and_Poison_Detection_on_Deep_Source_Code_Processing_Models.pdf) | | |
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| 2024 | CoRR | [Eliminating Backdoors in Neural Code Models via Trigger Inversion.](./papers_en/2024-CoRR-Eliminating_Backdoors_via_Trigger_Inversion.pdf) 🚩 | | |
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| 2024 | CoRR | [Defending Code Language Models against Backdoor Attacks with Deceptive Cross-Entropy Loss.](./papers_en/2024-CoRR-DeCE.pdf) | [![Octocat](./figures/github.svg)](https://github.com/NTDXYG/DeCE) | |

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