80 citations · 121 across the 25 of their papers we have counts for
8 papers · 1 filter
MathPile: A Billion-Token-Scale Pretraining Corpus for Math
Zengzhi Wang, Xuefeng Li, Rui Xia +1
High-quality, large-scale corpora are the cornerstone of building foundation models. In this work, we introduce MathPile, a diverse and high-quality math-centric corpus comprising…
In-Context Learning for Knowledge Base Question Answering for Unmanned Systems based on Large Language Models
Yunlong Chen, Yaming Zhang, Jianfei Yu +2
Knowledge Base Question Answering (KBQA) aims to answer factoid questions based on knowledge bases. However, generating the most appropriate knowledge base query code based on Natu…
A New Dialogue Response Generation Agent for Large Language Models by Asking Questions to Detect User's Intentions
Siwei Wu, Xiangqing Shen, Rui Xia
Large Language Models (LLMs), such as ChatGPT, have recently been applied to various NLP tasks due to its open-domain generation capabilities. However, there are two issues with ap…
Ask Again, Then Fail: Large Language Models' Vacillations in Judgment
Qiming Xie, Zengzhi Wang, Yi Feng +1
We observe that current conversational language models often waver in their judgments when faced with follow-up questions, even if the original judgment was correct. This wavering…
MEMD-ABSA: A Multi-Element Multi-Domain Dataset for Aspect-Based Sentiment Analysis
Hongjie Cai, Nan Song, Zengzhi Wang +7
Aspect-based sentiment analysis is a long-standing research interest in the field of opinion mining, and in recent years, researchers have gradually shifted their focus from simple…
Commonsense Knowledge Graph Completion Via Contrastive Pretraining and Node Clustering
Siwei Wu, Xiangqing Shen, Rui Xia
The nodes in the commonsense knowledge graph (CSKG) are normally represented by free-form short text (e.g., word or phrase). Different nodes may represent the same concept. This le…