Introduces LoRA-Curve parameterization to link independent LoRA optima via low-loss valleys, yielding higher predictive mutual information on reasoning and classification tasks with Qwen2.5 7B.
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models.Advances in Neural In- formation Processing Systems, 37:67758–67794, December 2024
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CaliDist calibrates LLMs by scaling confidence according to how much predictions change under semantic distractors, cutting average ECE from 23% to 7% on seven NLU benchmarks across six models.
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On the Construction and Implications of Low-Loss Valleys in LoRA-based Bayesian Inference
Introduces LoRA-Curve parameterization to link independent LoRA optima via low-loss valleys, yielding higher predictive mutual information on reasoning and classification tasks with Qwen2.5 7B.
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CaliDist: Calibrating Large Language Models via Behavioral Robustness to Distraction
CaliDist calibrates LLMs by scaling confidence according to how much predictions change under semantic distractors, cutting average ECE from 23% to 7% on seven NLU benchmarks across six models.