GLUE

A nine-task benchmark of English sentence and sentence-pair language-understanding tasks (sentiment, entailment, paraphrase, etc.) for evaluating general NLU.

Papers using GLUE (12)

ReCoLoRA: Spectrum-Aware Recursive Consolidation for Continual LLM Fine-Tuning2026Catastrophic Forgetting in LLMs: A Comparative Analysis Across Language Tasks2025 · 1 citesStrategic Over-Parameterization for Generalizable Low-Rank Adaptation2026TLoRA+: A Low-Rank Parameter-Efficient Fine-Tuning Method for Large Language Models2026Disentangling Task Conflicts in Multi-Task LoRA via Orthogonal Gradient Projection2026AdaFRUGAL: Adaptive Memory-Efficient Training with Dynamic Control2026ExplainableGuard: Interpretable Adversarial Defense for Large Language Models Using Chain-of-Thought Reasoning2025Sample-Efficient Differentially Private Fine-Tuning via Gradient Matrix Denoising2025UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter-Efficient Fine-Tuning of Large Models2025Assessing the Macro and Micro Effects of Random Seeds on Fine-Tuning Large Language Models2025The Vulnerability of Language Model Benchmarks: Do They Accurately Reflect True LLM Performance?2024 · 2 cites3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability2024