44 citations · 167 across the 19 of their papers we have counts for
20 papers
HERO: Human-profile Enhanced Retrieval Optimization Framework for Long-term Agent Memory
Yuanhua Lin, Yile Li, Zhiyuan Zhao +2
Long-term memory is crucial for personalized responses and long-horizon agent interactions. Existing methods often rely on LLMs to compress or rewrite dialogue histories and use th…
A Survey on Out-of-Distribution Detection in NLP
Hao Lang, Yinhe Zheng, Yixuan Li +3
Out-of-distribution (OOD) detection is essential for the reliable and safe deployment of machine learning systems in the real world. Great progress has been made over the past year…
CGoDial: A Large-Scale Benchmark for Chinese Goal-oriented Dialog Evaluation
Yinpei Dai, Wanwei He, Bowen Li +5
Practical dialog systems need to deal with various knowledge sources, noisy user expressions, and the shortage of annotated data. To better solve the above problems, we propose CGo…
Estimating Soft Labels for Out-of-Domain Intent Detection
Hao Lang, Yinhe Zheng, Jian Sun +3
Out-of-Domain (OOD) intent detection is important for practical dialog systems. To alleviate the issue of lacking OOD training samples, some works propose synthesizing pseudo OOD s…
SPACE-3: Unified Dialog Model Pre-training for Task-Oriented Dialog Understanding and Generation
Wanwei He, Yinpei Dai, Min Yang +4
Recently, pre-training methods have shown remarkable success in task-oriented dialog (TOD) systems. However, most existing pre-trained models for TOD focus on either dialog underst…
A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions
Bowen Qin, Binyuan Hui, Lihan Wang +9
Text-to-SQL parsing is an essential and challenging task. The goal of text-to-SQL parsing is to convert a natural language (NL) question to its corresponding structured query langu…
Layout-Aware Information Extraction for Document-Grounded Dialogue: Dataset, Method and Demonstration
Zhenyu Zhang, Bowen Yu, Haiyang Yu +6
Building document-grounded dialogue systems have received growing interest as documents convey a wealth of human knowledge and commonly exist in enterprises. Wherein, how to compre…
Duplex Conversation: Towards Human-like Interaction in Spoken Dialogue Systems
Ting-En Lin, Yuchuan Wu, Fei Huang +3
In this paper, we present Duplex Conversation, a multi-turn, multimodal spoken dialogue system that enables telephone-based agents to interact with customers like a human. We use t…
Proton: Probing Schema Linking Information from Pre-trained Language Models for Text-to-SQL Parsing
Lihan Wang, Bowen Qin, Binyuan Hui +7
The importance of building text-to-SQL parsers which can be applied to new databases has long been acknowledged, and a critical step to achieve this goal is schema linking, i.e., p…
A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots
Sai Zhang, Yuwei Hu, Yuchuan Wu +5
A slot value might be provided segment by segment over multiple-turn interactions in a dialog, especially for some important information such as phone numbers and names. It is a co…
SSQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parsers
Binyuan Hui, Ruiying Geng, Lihan Wang +4
The task of converting a natural language question into an executable SQL query, known as text-to-SQL, is an important branch of semantic parsing. The state-of-the-art graph-based…
GALAXY: A Generative Pre-trained Model for Task-Oriented Dialog with Semi-Supervised Learning and Explicit Policy Injection
Wanwei He, Yinpei Dai, Yinhe Zheng +9
Pre-trained models have proved to be powerful in enhancing task-oriented dialog systems. However, current pre-training methods mainly focus on enhancing dialog understanding and ge…
Linking-Enhanced Pre-Training for Table Semantic Parsing
Bowen Qin, Lihan Wang, Binyuan Hui +5
Recently pre-training models have significantly improved the performance of various NLP tasks by leveraging large-scale text corpora to improve the contextual representation abilit…
Path-Enhanced Multi-Relational Question Answering with Knowledge Graph Embeddings
Guanglin Niu, Yang Li, Chengguang Tang +6
The multi-relational Knowledge Base Question Answering (KBQA) system performs multi-hop reasoning over the knowledge graph (KG) to achieve the answer. Recent approaches attempt to…
DialogueCSE: Dialogue-based Contrastive Learning of Sentence Embeddings
Che Liu, Rui Wang, Jinghua Liu +3
Learning sentence embeddings from dialogues has drawn increasing attention due to its low annotation cost and high domain adaptability. Conventional approaches employ the siamese-n…
MMChat: Multi-Modal Chat Dataset on Social Media
Yinhe Zheng, Guanyi Chen, Xin Liu +1
Incorporating multi-modal contexts in conversation is important for developing more engaging dialogue systems. In this work, we explore this direction by introducing MMChat: a larg…
Preview, Attend and Review: Schema-Aware Curriculum Learning for Multi-Domain Dialog State Tracking
Yinpei Dai, Hangyu Li, Yongbin Li +4
Existing dialog state tracking (DST) models are trained with dialog data in a random order, neglecting rich structural information in a dataset. In this paper, we propose to use cu…
Relational Learning with Gated and Attentive Neighbor Aggregator for Few-Shot Knowledge Graph Completion
Guanglin Niu, Yang Li, Chengguang Tang +7
Aiming at expanding few-shot relations' coverage in knowledge graphs (KGs), few-shot knowledge graph completion (FKGC) has recently gained more research interests. Some existing mo…
Improving Text-to-SQL with Schema Dependency Learning
Binyuan Hui, Xiang Shi, Ruiying Geng +4
Text-to-SQL aims to map natural language questions to SQL queries. The sketch-based method combined with execution-guided (EG) decoding strategy has shown a strong performance on t…
Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsing
Binyuan Hui, Ruiying Geng, Qiyu Ren +7
Semantic parsing has long been a fundamental problem in natural language processing. Recently, cross-domain context-dependent semantic parsing has become a new focus of research. C…