72 citations · 181 across the 44 of their papers we have counts for
8 papers · 2 filters
PolyIE: A Dataset of Information Extraction from Polymer Material Scientific Literature
Jerry Junyang Cheung, Yuchen Zhuang, Yinghao Li +5
Scientific information extraction (SciIE), which aims to automatically extract information from scientific literature, is becoming more important than ever. However, there are no e…
Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models
Ran Xu, Hejie Cui, Yue Yu +6
Clinical natural language processing requires methods that can address domain-specific challenges, such as complex medical terminology and clinical contexts. Recently, large langua…
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search
Yuchen Zhuang, Xiang Chen, Tong Yu +5
Large language models (LLMs) have demonstrated powerful decision-making and planning capabilities in solving complicated real-world problems. LLM-based autonomous agents can intera…
ToolQA: A Dataset for LLM Question Answering with External Tools
Yuchen Zhuang, Yue Yu, Kuan Wang +2
Large Language Models (LLMs) have demonstrated impressive performance in various NLP tasks, but they still suffer from challenges such as hallucination and weak numerical reasoning…
DyGen: Learning from Noisy Labels via Dynamics-Enhanced Generative Modeling
Yuchen Zhuang, Yue Yu, Lingkai Kong +2
Learning from noisy labels is a challenge that arises in many real-world applications where training data can contain incorrect or corrupted labels. When fine-tuning language model…
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias
Yue Yu, Yuchen Zhuang, Jieyu Zhang +5
Large language models (LLMs) have been recently leveraged as training data generators for various natural language processing (NLP) tasks. While previous research has explored diff…
AdaPlanner: Adaptive Planning from Feedback with Language Models
Haotian Sun, Yuchen Zhuang, Lingkai Kong +2
Large language models (LLMs) have recently demonstrated the potential in acting as autonomous agents for sequential decision-making tasks. However, most existing methods either tak…
ReGen: Zero-Shot Text Classification via Training Data Generation with Progressive Dense Retrieval
Yue Yu, Yuchen Zhuang, Rongzhi Zhang +3
With the development of large language models (LLMs), zero-shot learning has attracted much attention for various NLP tasks. Different from prior works that generate training data…