← Search

Yuxin Liang

2 accepted papers

2024

Never Lost in the Middle: Mastering Long-Context Question Answering with Position-Agnostic Decompositional Training

ACL 2024long

While large language models (LLMs) are equipped with longer text input capabilities than before, they are struggling to seek correct information in long contexts. The “lost in the middle” problem challenges most LLMs, referring to the dramatic decline in accuracy when correct information is located…

2022

Exploring the Impact of Negative Samples of Contrastive Learning: A Case Study of Sentence Embedding

ACL 2022findings

Contrastive learning is emerging as a powerful technique for extracting knowledge from unlabeled data. This technique requires a balanced mixture of two ingredients: positive (similar) and negative (dissimilar) samples. This is typically achieved by maintaining a queue of negative samples during tra…