activity
20222025
most citedA Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding

6 citations · 8 across the 5 of their papers we have counts for

collaborators

6 papers

cs.SE2025

LogSage: An LLM-Based Framework for CI/CD Failure Detection and Remediation with Industrial Validation

Weiyuan Xu, Juntao Luo, Tao Huang +7

Continuous Integration and Deployment (CI/CD) pipelines are critical to modern software engineering, yet diagnosing and resolving their failures remains complex and labor-intensive…

cs.LG2025

Win Fast or Lose Slow: Balancing Speed and Accuracy in Latency-Sensitive Decisions of LLMs

Hao Kang, Qingru Zhang, Han Cai +4

Large language models (LLMs) have shown remarkable performance across diverse reasoning and generation tasks, and are increasingly deployed as agents in dynamic environments such a…

cs.CL2023

TLAG: An Informative Trigger and Label-Aware Knowledge Guided Model for Dialogue-based Relation Extraction

Hao An, Dongsheng Chen, Weiyuan Xu +2

Dialogue-based Relation Extraction (DRE) aims to predict the relation type of argument pairs that are mentioned in dialogue. The latest trigger-enhanced methods propose trigger pre…

cs.LG2023

FTM: A Frame-level Timeline Modeling Method for Temporal Graph Representation Learning

Bowen Cao, Qichen Ye, Weiyuan Xu +1

Learning representations for graph-structured data is essential for graph analytical tasks. While remarkable progress has been made on static graphs, researches on temporal graphs…

cs.CL2023★ 2 cited

FiTs: Fine-grained Two-stage Training for Knowledge-aware Question Answering

Qichen Ye, Bowen Cao, Nuo Chen +2

Knowledge-aware question answering (KAQA) requires the model to answer questions over a knowledge base, which is essential for both open-domain QA and domain-specific QA, especiall…

cs.CL2022★ 6 cited

A Dynamic Graph Interactive Framework with Label-Semantic Injection for Spoken Language Understanding

Zhihong Zhu, Weiyuan Xu, Xuxin Cheng +2

Multi-intent detection and slot filling joint models are gaining increasing traction since they are closer to complicated real-world scenarios. However, existing approaches (1) foc…