1 citations · 1 across the 11 of their papers we have counts for
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Hyperband-based Bayesian Optimization for Black-box Prompt Selection
Lennart Schneider, Martin Wistuba, Aaron Klein +3
Optimal prompt selection is crucial for maximizing large language model (LLM) performance on downstream tasks, especially in black-box settings where models are only accessible via…
Warmstarting for Scaling Language Models
Neeratyoy Mallik, Maciej Janowski, Johannes Hog +4
Scaling model sizes to scale performance has worked remarkably well for the current large language models paradigm. The research and empirical findings of various scaling studies l…
Compressing Large Language Models with Automated Sub-Network Search
Rhea Sanjay Sukthanker, Benedikt Staffler, Frank Hutter +1
Large Language Models (LLMs) demonstrate exceptional reasoning abilities, enabling strong generalization across diverse tasks such as commonsense reasoning and instruction followin…
Structural Pruning of Pre-trained Language Models via Neural Architecture Search
Aaron Klein, Jacek Golebiowski, Xingchen Ma +2
Pre-trained language models (PLM), for example BERT or RoBERTa, mark the state-of-the-art for natural language understanding task when fine-tuned on labeled data. However, their la…