21 citations · 44 across the 8 of their papers we have counts for
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cs.CL2023
BeLLM: Backward Dependency Enhanced Large Language Model for Sentence Embeddings
Xianming Li, Jing Li
Sentence embeddings are crucial in measuring semantic similarity. Most recent studies employed large language models (LLMs) to learn sentence embeddings. Existing LLMs mainly adopt…
cs.CL2023★ 20 cited
Label Supervised LLaMA Finetuning
Zongxi Li, Xianming Li, Yuzhang Liu +5
The recent success of Large Language Models (LLMs) has gained significant attention in both academia and industry. Substantial efforts have been made to enhance the zero- and few-s…
cs.CL2023★ 21 cited
AnglE-optimized Text Embeddings
Xianming Li, Jing Li
High-quality text embedding is pivotal in improving semantic textual similarity (STS) tasks, which are crucial components in Large Language Model (LLM) applications. However, a com…