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cs.AI2025
Approximating Human Preferences Using a Multi-Judge Learned System
Eitán Sprejer, Fernando Avalos, Augusto Bernardi +3
Aligning LLM-based judges with human preferences is a significant challenge, as they are difficult to calibrate and often suffer from rubric sensitivity, bias, and instability. Ove…
cs.AI2024
Noise Injection Reveals Hidden Capabilities of Sandbagging Language Models
Cameron Tice, Philipp Alexander Kreer, Nathan Helm-Burger +7
Capability evaluations play a crucial role in assessing and regulating frontier AI systems. The effectiveness of these evaluations faces a significant challenge: strategic underper…