DDIPE poisons LLM agent skills by embedding malicious logic in documentation examples, achieving 11.6-33.5% bypass rates across frameworks while explicit attacks are blocked, with 2.5% evading detection.
Title resolution pending
4 Pith papers cite this work. Polarity classification is still indexing.
4
Pith papers citing it
citation-role summary
background 1
method 1
citation-polarity summary
years
2026 4representative citing papers
Schema-constrained, quote-grounded LLM extraction plus a second-pass quality score yields 601k auditable 8-K event tags whose precision and market reactions both improve with the score.
Open-source AI model development shows far less collaboration and openness than classic open-source software; users innovate by adapting models rather than improving them.
MESA reduces hallucinations in LVLMs via controlled selective latent intervention that preserves the original token distribution.
citing papers explorer
-
Supply-Chain Poisoning Attacks Against LLM Coding Agent Skill Ecosystems
DDIPE poisons LLM agent skills by embedding malicious logic in documentation examples, achieving 11.6-33.5% bypass rates across frameworks while explicit attacks are blocked, with 2.5% evading detection.
-
Grounded Event Extraction from SEC 8-K Filings with a Fine-Grained Taxonomy
Schema-constrained, quote-grounded LLM extraction plus a second-pass quality score yields 601k auditable 8-K event tags whose precision and market reactions both improve with the score.
-
From OSS to Open Source AI: an Exploratory Study of Collaborative Development Paradigm Divergence
Open-source AI model development shows far less collaboration and openness than classic open-source software; users innovate by adapting models rather than improving them.
-
Mitigating Entangled Steering in Large Vision-Language Models for Hallucination Reduction
MESA reduces hallucinations in LVLMs via controlled selective latent intervention that preserves the original token distribution.