11 citations · 29 across the 7 of their papers we have counts for
11 papers
Task-Specific Data Selection for Instruction Tuning via Monosemantic Neuronal Activations
Da Ma, Gonghu Shang, Zhi Chen +6
Instruction tuning improves the ability of large language models (LLMs) to follow diverse human instructions, but achieving strong performance on specific target tasks remains chal…
Compressing KV Cache for Long-Context LLM Inference with Inter-Layer Attention Similarity
Da Ma, Lu Chen, Situo Zhang +8
The rapid expansion of context window sizes in Large Language Models~(LLMs) has enabled them to tackle increasingly complex tasks involving lengthy documents. However, this progres…
Few-Shot NLU with Vector Projection Distance and Abstract Triangular CRF
Su Zhu, Lu Chen, Ruisheng Cao +3
Data sparsity problem is a key challenge of Natural Language Understanding (NLU), especially for a new target domain. By training an NLU model in source domains and applying the mo…
LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relations
Ruisheng Cao, Lu Chen, Zhi Chen +3
This work aims to tackle the challenging heterogeneous graph encoding problem in the text-to-SQL task. Previous methods are typically node-centric and merely utilize different weig…
Decoupled Dialogue Modeling and Semantic Parsing for Multi-Turn Text-to-SQL
Zhi Chen, Lu Chen, Hanqi Li +4
Recently, Text-to-SQL for multi-turn dialogue has attracted great interest. Here, the user input of the current turn is parsed into the corresponding SQL query of the appropriate d…
ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parser
Zhi Chen, Lu Chen, Yanbin Zhao +4
Given a database schema, Text-to-SQL aims to translate a natural language question into the corresponding SQL query. Under the setup of cross-domain, traditional semantic parsing m…
CREDIT: Coarse-to-Fine Sequence Generation for Dialogue State Tracking
Zhi Chen, Lu Chen, Zihan Xu +3
In dialogue systems, a dialogue state tracker aims to accurately find a compact representation of the current dialogue status, based on the entire dialogue history. While previous…
Dual Learning for Dialogue State Tracking
Zhi Chen, Lu Chen, Yanbin Zhao +2
In task-oriented multi-turn dialogue systems, dialogue state refers to a compact representation of the user goal in the context of dialogue history. Dialogue state tracking (DST) i…
Structured Hierarchical Dialogue Policy with Graph Neural Networks
Zhi Chen, Xiaoyuan Liu, Lu Chen +1
Dialogue policy training for composite tasks, such as restaurant reservation in multiple places, is a practically important and challenging problem. Recently, hierarchical deep rei…
Deep Reinforcement Learning for On-line Dialogue State Tracking
Zhi Chen, Lu Chen, Xiang Zhou +1
Dialogue state tracking (DST) is a crucial module in dialogue management. It is usually cast as a supervised training problem, which is not convenient for on-line optimization. In…
Semi-Supervised Text Simplification with Back-Translation and Asymmetric Denoising Autoencoders
Yanbin Zhao, Lu Chen, Zhi Chen +1
Text simplification (TS) rephrases long sentences into simplified variants while preserving inherent semantics. Traditional sequence-to-sequence models heavily rely on the quantity…