24 citations · 29 across the 9 of their papers we have counts for
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cs.CL2024
AtomR: Atomic Operator-Empowered Large Language Models for Heterogeneous Knowledge Reasoning
Amy Xin, Jinxin Liu, Zijun Yao +4
Despite the outstanding capabilities of large language models (LLMs), knowledge-intensive reasoning still remains a challenging task due to LLMs' limitations in compositional reaso…
cs.CL2024★ 1 cited
Improving Text Embeddings for Smaller Language Models Using Contrastive Fine-tuning
Trapoom Ukarapol, Zhicheng Lee, Amy Xin
While Large Language Models show remarkable performance in natural language understanding, their resource-intensive nature makes them less accessible. In contrast, smaller language…
cs.CL2024★ 4 cited
LLMAEL: Large Language Models are Good Context Augmenters for Entity Linking
Amy Xin, Yunjia Qi, Zijun Yao +5
Specialized entity linking (EL) models are well-trained at mapping mentions to unique knowledge base (KB) entities according to a given context. However, specialized EL models stru…