Papers with feedforward layers
NarrowBERT: Accelerating Masked Language Model Pretraining and Inference (2023.acl-short)
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| Challenge: | Large-scale language model pretraining is expensive as the models and pretraining corpora have become larger over time. |
| Approach: | They propose a modified transformer encoder that increases throughput for masked language model pretraining by more than 2x. |
| Outcome: | The proposed model increases throughput on IMDB and Amazon reviews classification and CoNLL NER tasks by 3.5x with minimal performance degradation. |
The Role of Outgoing Connection Heterogeneity in Feedforward Layers of Large Language Models (2025.emnlp-main)
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| Challenge: | Using a new fine-tuning loss, we show that inner neurons with diverse outgoing connections are more critical to model performance than those with uniform connections. |
| Approach: | They propose a new loss that reduces the outgoing connection entropy in feedforward layers and elucidates the role of outgoing connections in large language models. |
| Outcome: | The proposed method is significantly more effective than removing neurons randomly or based on their magnitude. |