Tag: AI reliability
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Can We Trust AI in Scientific Peer Review?
Explore the reliability and challenges of AI referees in scientific peer review and how to ensure trustworthy evaluations.
Analyzing Reasoning Shortcuts in Neurosymbolic Learning
Explore constraint-based methods to detect and fix reasoning shortcuts in neurosymbolic AI, improving learning accuracy and system reliability.
Eliminating Sandbagging in LLMs with Weak Supervision
Discover how combining weak supervision and reinforcement learning stops sandbagging in LLMs, boosting AI performance in math, science, and coding tasks.
Do Hallucination Neurons in LLMs Generalize Across Domains?
Explore how hallucination neurons in large language models perform across domains and why domain-specific calibration is crucial for AI accuracy.
Detecting Precision Risks in Large Language Models
Discover how PrecisionDiff identifies hidden precision-induced output errors in large language models to improve reliability and deployment safety.