Topic
Adversarial Attacks
Discover key takeaways from 3 podcast episodes about this topic.
Large Language Models (LLMs)Retrieval Augmented Generation (RAG)Adversarial Attacks
Jan 27, 2026Cascading Adversarial Bias from Injection to Distillation in Language Models
RAG systems, designed to enhance LLM accuracy and personalization, are vulnerable to 'Phantom' trigger attacks where a single poisoned document can manipulate outputs to deny service, express bias, exfiltrate data, or generate harmful content.
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Google TechTalks
Language ModelsAdversarial AttacksData Poisoning
Jan 27, 2026Cascading Adversarial Bias from Injection to Distillation in Language Models
Adversarial bias injected into large language models (LLMs) during instruction tuning can cascade and amplify in distilled student models, even with minimal poisoning, bypassing current detection methods.
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Google TechTalks
Generative AIWatermarkingDeepfakes
Jan 27, 2026Watermarking in Generative AI: Opportunities and Threats
This talk details the critical role of watermarking in combating generative AI misuse, from deepfakes and scams to intellectual property theft, by enabling detection and attribution across text and images.
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Google TechTalks