Papers by Li Erran Li
On the Analysis and Distillation of Emergent Outlier Properties in Pre-trained Language Models (2025.naacl-long)
Copied to clipboard
| Challenge: | Existing studies show that a small subset of dimensions within language Transformers’ representation spaces emerge as "outliers" during pretraining. |
| Approach: | They propose a method that prioritizes critical outlier dimensions in distillation using a weighted MSE loss. |
| Outcome: | The proposed method outperforms state-of-the-art distillation methods and generalizes well across Encoder-only BERT, Decoder-only GPT-2, and Encodeer-Decoder T5 architectures. |
Retrieval, Analogy, and Composition: A framework for Compositional Generalization in Image Captioning (2021.findings-emnlp)
Copied to clipboard
| Challenge: | Existing approaches fail to generalize well to concepts that are not observed during training. |
| Approach: | They propose a framework that revolves around probing several similar image caption training instances and performing analogical reasoning over relevant entities in retrieved prototypes. |
| Outcome: | The proposed framework improves on the widely used image captioning benchmarks and on composition-related evaluation metrics. |