204 citations · 283 across the 13 of their papers we have counts for
13 papers
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…
Improving Compositional Generalization in Math Word Problem Solving
Yunshi Lan, Lei Wang, Jing Jiang +1
Compositional generalization refers to a model's capability to generalize to newly composed input data based on the data components observed during training. It has triggered a ser…
MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers
Yihuai Lan, Lei Wang, Qiyuan Zhang +5
Developing automatic Math Word Problem (MWP) solvers has been an interest of NLP researchers since the 1960s. Over the last few years, there are a growing number of datasets and de…
Complex Knowledge Base Question Answering: A Survey
Yunshi Lan, Gaole He, Jinhao Jiang +3
Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Early studies mainly focused on answering simple questions over KBs and achieved grea…
MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving
Zhenwen Liang, Jipeng Zhang, Lei Wang +4
Math word problem (MWP) solving faces a dilemma in number representation learning. In order to avoid the number representation issue and reduce the search space of feasible solutio…
A Survey on Complex Knowledge Base Question Answering: Methods, Challenges and Solutions
Yunshi Lan, Gaole He, Jinhao Jiang +3
Knowledge base question answering (KBQA) aims to answer a question over a knowledge base (KB). Recently, a large number of studies focus on semantically or syntactically complicate…
Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals
Gaole He, Yunshi Lan, Jing Jiang +2
Multi-hop Knowledge Base Question Answering (KBQA) aims to find the answer entities that are multiple hops away in the Knowledge Base (KB) from the entities in the question. A majo…
Multi-level Head-wise Match and Aggregation in Transformer for Textual Sequence Matching
Shuohang Wang, Yunshi Lan, Yi Tay +2
Transformer has been successfully applied to many natural language processing tasks. However, for textual sequence matching, simple matching between the representation of a pair of…