204 citations · 283 across the 13 of their papers we have counts for
6 papers · 1 filter
Prompting Large Language Models with Chain-of-Thought for Few-Shot Knowledge Base Question Generation
Yuanyuan Liang, Jianing Wang, Hanlun Zhu +3
The task of Question Generation over Knowledge Bases (KBQG) aims to convert a logical form into a natural language question. For the sake of expensive cost of large-scale question…
DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning
Kangyang Luo, Shuai Wang, Yexuan Fu +3
Federated Learning (FL) is a privacy-constrained decentralized machine learning paradigm in which clients enable collaborative training without compromising private data. However,…
History Semantic Graph Enhanced Conversational KBQA with Temporal Information Modeling
Hao Sun, Yang Li, Liwei Deng +6
Context information modeling is an important task in conversational KBQA. However, existing methods usually assume the independence of utterances and model them in isolation. In th…
Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models
Lei Wang, Wanyu Xu, Yihuai Lan +4
Large language models (LLMs) have recently been shown to deliver impressive performance in various NLP tasks. To tackle multi-step reasoning tasks, few-shot chain-of-thought (CoT)…
Read, Diagnose and Chat: Towards Explainable and Interactive LLMs-Augmented Depression Detection in Social Media
Wei Qin, Zetong Chen, Lei Wang +3
This paper proposes a new depression detection system based on LLMs that is both interpretable and interactive. It not only provides a diagnosis, but also diagnostic evidence and p…
GradMA: A Gradient-Memory-based Accelerated Federated Learning with Alleviated Catastrophic Forgetting
Kangyang Luo, Xiang Li, Yunshi Lan +1
Federated Learning (FL) has emerged as a de facto machine learning area and received rapid increasing research interests from the community. However, catastrophic forgetting caused…