Looped GPT-BERT: trading parameters for computation in small language modeling
Read the original at arxiv.org→arXiv:2609.09691v1 Announce Type: new Abstract: When training data are limited, increasing parameter count is not the only way to improve language-model performance. A small parameter set, when repeatedly applied,...
Original headline: "Looped GPT-BERT: Trading Parameters for Computation in Small Language Modeling"
Coverage timeline
- Sep 10, 04:00 UTC arXiv cs.CL lead source Looped GPT-BERT: Trading Parameters for Computation in Small Language Modeling
- Sep 11, 04:00 UTC arXiv cs.CL Data-Efficient Language Modeling: From Frontier Advancement to Principle-Guided Model Improvement