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Showing 521-540 of 637 claims in topic "safety"

safety
fact
Bearish
academic

Despite alignment training, LLMs remain prone to generating unsafe outputs at deployment time

Machine Learning (Statistics)
7/27/2026
Confidence: 90%Source
safety
Previous
12628
fact
Neutral
academic

Simple real-time monitors based on thresholding are competitive with advanced monitors based on sequential hypothesis testing for safety monitoring

Machine Learning (Statistics)
7/27/2026
Confidence: 80%Source
safety
fact
Bearish
academic

LLMs memorize sensitive training data including personally identifiable information, creating a pressing need for reliable post hoc removal methods

Machine Learning
7/27/2026
Confidence: 90%Source
safety
critique
Bearish
academic

Existing unlearning benchmarks evaluate solely at the output level, leaving open whether unlearning truly erases knowledge or merely obfuscates it

Machine Learning
7/27/2026
Confidence: 85%Source
safety
fact
Bearish
academic

As AI coding agents become more autonomous, persistence creates a new attack surface where misaligned agents can distribute attacks across pull requests

Artificial Intelligence
7/27/2026
Confidence: 85%Source
safety
fact
Bearish
academic

No single monitor is robust to both gradual and non-gradual attacks in iterative coding scenarios

Artificial Intelligence
7/27/2026
Confidence: 80%Source
safety
opinion
Neutral
academic

We can build defined variants of Functional Decision Theory (FDT) that achieve what FDT attempted to, sidestepping theoretical pitfalls

AI Alignment Forum
7/27/2026
Confidence: 75%Source
safety
fact
Bearish
academic

Academic decision theorists largely don't adopt Functional Decision Theory, with adoption countable on one hand missing four fingers

AI Alignment Forum
7/27/2026
Confidence: 80%Source
safety
critique
Bearish
academic

Most existing OOD detection literature assumes balanced datasets and lacks comprehensive assessment across diverse clinical OOD scenarios

Computer Vision
7/27/2026
Confidence: 80%Source
safety
fact
Bullish
academic

A Nonlinear von Mises-Fisher classifier can learn non-linear decision boundaries for improved medical OOD detection

Computer Vision
7/27/2026
Confidence: 75%Source
safety
critique
Bearish
academic

Deep models routinely misclassify out-of-distribution inputs with high confidence in medical diagnostic settings

Computer Vision
7/27/2026
Confidence: 85%Source
safety
critique
Bearish
academic

Existing RAG-based fact-checking systems often assume retrieved evidence is reliable, despite real-world information being conflicting, outdated, or from unreliable sources

Computation and Language
7/27/2026
Confidence: 85%Source
safety
fact
Bullish
academic

Source-critical reasoning through media background checks can assess credibility of evidence sources to support downstream fact verification

Computation and Language
7/27/2026
Confidence: 80%Source
safety
fact
Bullish
academic

Publicly available knowledge stores of web-sourced documents can enable reproducible, low-cost evaluation of media background check generation without relying on costly proprietary search APIs

Computation and Language
7/27/2026
Confidence: 85%Source
safety
fact
Bearish
academic

GPT-4-0314 shows disclosure risk ranging from 0% to 84% depending on adversarial conditioning, indicating systemic PII leakage vulnerability

Artificial Intelligence
7/27/2026
Confidence: 85%Source
safety
fact
Bearish
academic

No standardized runtime mechanism exists to intercept and validate individual AI inference outputs before they trigger live network state changes in autonomous telecommunications

Artificial Intelligence
7/27/2026
Confidence: 85%Source
safety
fact
Bullish
academic

Guard Rail Validation framework can provide graduated validation mechanisms for AI decisions based on criticality levels

Artificial Intelligence
7/27/2026
Confidence: 75%Source
safety
opinion
Neutral
academic

The hard part of AI auditing is not naming a risk but operationalizing it into concrete tests, measurements, and defensible grades

Artificial Intelligence
7/27/2026
Confidence: 90%Source
safety
fact
Bearish
academic

At least 74 AI risk taxonomies exist, and almost all stop at cataloging risks without showing how an audit is executed

Artificial Intelligence
7/27/2026
Confidence: 85%Source
safety
fact
Neutral
academic

Fully autonomous telecommunications networks (Levels 4-5) require AI/ML agents to make real-time decisions without human intervention

Artificial Intelligence
7/27/2026
Confidence: 90%Source
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Last synthesis: 2026-09-20. 8,951 pending.