Tag: AI reliability
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Enhancing Language Model Reliability in Instruction-Following
Explore how nuance-oriented reliability impacts language model performance and learn about new metrics and tools to improve instruction-following accuracy.
Red Teaming Large Reasoning Models for Trustworthiness
Explore RT-LRM, a benchmark to evaluate the safety, truthfulness, and efficiency of Large Reasoning Models in AI development.
Benchmarking Deflection & Hallucination in Vision-Language AI
Explore new benchmarks assessing deflection and hallucination in large vision-language models to improve AI reliability in multimodal tasks.
IDEA: Interpretable Decision Framework for LLMs Calibration
Discover IDEA, a framework enhancing LLM decision-making with interpretable, editable verbal-to-numeric calibration for accurate AI predictions.
Diagnosing Failures in Long-Horizon AI Agentic Systems
Explore how the HORIZON benchmark diagnoses failures in AI agents during complex long-horizon tasks, improving reliability and performance.