Papers with security vulnerabilities

3 papers
A dataset for identifying actionable feedback in collaborative software development (P18-2)

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Challenge: a dataset of code reviews for the Google Chromium project analyzed linguistic features of code review feedback that elicited responsive actions from coworkers.
Approach: They analyze code reviews for Google Chromium and extract linguistic features that elicit responsive responses from coworkers.
Outcome: The proposed dataset shows that using NLP can be useful in code reviews . it also shows that it can be used to improve code reviews in a collaborative environment .
Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods (2021.emnlp-main)

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Challenge: Knowledge Graph Embeddings (KGE) are widely used for relational learning on large scale Knowledge . however, little is known about the security vulnerabilities that might disrupt their intended behaviour.
Approach: They propose to use model-agnostic instance attribution methods to select adversarial deletions and a heuristic method to replace one of the two entities in each influential triple to generate adversarials.
Outcome: The proposed methods outperform the state-of-the-art data poisoning attacks on KGE models and improve the MRR degradation by up to 62% over the baselines.
Rotation Control Unlearning: Quantifying and Controlling Continuous Unlearning for LLM with The Cognitive Rotation Space (2026.findings-acl)

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Challenge: Existing methods to remove undesirable data from Large Language Models suffer from cumulative catastrophic utility loss under continuous unlearning requests.
Approach: They propose a method that leverages the rotational salience weight of RCU to quantify and control the unlearning degree in the continuous unlearning process.
Outcome: The proposed method achieves SOTA performance without a retained dataset.

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