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cs.CL2026
Beyond LoRA vs. Full Fine-Tuning: Gradient-Guided Optimizer Routing for LLM Adaptation
Haozhan Tang, Xiuqi Zhu, Xinyin Zhang +3
Recent literature on fine-tuning Large Language Models highlights a fundamental debate. While Full Fine-Tuning (FFT) provides greater representational plasticity, Low-Rank Adaptati…
cs.CL2026
Automated Concept Discovery for LLM-as-a-Judge Preference Analysis
James Wedgwood, Chhavi Yadav, Virginia Smith
Large Language Models (LLMs) are increasingly used as scalable evaluators of model outputs, but their preference judgments exhibit systematic biases and can diverge from human eval…