1 citations · 1 across the 12 of their papers we have counts for
13 papers
Bifrost: Empowering Pretrained Language Model with Fallibility Representation for Log-Based Fault Diagnosis
Minghua He, Tong Jia, Lingzhe Zhang +9
Log-based fault diagnosis is crucial for runtime debugging and maintenance. Existing fault diagnosis methods use language models pre-trained on natural language (PLMs) for log repr…
UltraX: Refining Pre-Training Data at Scale with Adaptive Programmatic Editing
Xinlong Zhao, Dongsheng Liu, Hengyu Zhao +9
As available training data approaches its physical limit, gains from Scaling Laws have begun to diminish. Consequently, improving Large Language Models (LLMs) now depends less on d…
Rethinking Data Mixing from the Perspective of Large Language Models
Yuanjian Xu, Tianze Sun, Changwei Xu +7
Data mixing strategy is essential for large language model (LLM) training. Empirical evidence shows that inappropriate strategies can significantly reduce generalization. Although…
MG-HGNN: A Heterogeneous GNN Framework for Indoor Wi-Fi Fingerprint-Based Localization
Yibu Wang, Zhaoxin Zhang, Ning Li +3
Received signal strength indicator (RSSI) is the primary representation of Wi-Fi fingerprints and serves as a crucial tool for indoor localization. However, existing RSSI-based pos…
Generality Is Not Enough: Zero-Label Cross-System Log-Based Anomaly Detection via Knowledge-Level Collaboration
Xinlong Zhao, Tong Jia, Minghua He +1
Log-based anomaly detection is crucial for ensuring software system stability. However, the scarcity of labeled logs limits rapid deployment to new systems. Cross-system transfer h…
ZeroLog: Zero-Label Generalizable Cross-System Log-based Anomaly Detection
Xinlong Zhao, Tong Jia, Minghua He +2
Log-based anomaly detection is an important task in ensuring the stability and reliability of software systems. One of the key problems in this task is the lack of labeled logs. Ex…
FusionLog: Cross-System Log-based Anomaly Detection via Fusion of General and Proprietary Knowledge
Xinlong Zhao, Tong Jia, Minghua He +2
Log-based anomaly detection is critical for ensuring the stability and reliability of web systems. One of the key problems in this task is the lack of sufficient labeled logs, whic…
JVLGS: Joint Vision-Language Gas Leak Segmentation
Xinlong Zhao, Qixiang Pang, Shan Du
Gas leaks pose severe risks to human health and industrial safety. However, accurate and timely monitoring of gas leaks remains a major challenge. Existing vision-based methods usi…
From Few-Label to Zero-Label: An Approach for Cross-System Log-Based Anomaly Detection with Meta-Learning
Xinlong Zhao, Tong Jia, Minghua He +3
Log anomaly detection plays a critical role in ensuring the stability and reliability of software systems. However, existing approaches rely on large amounts of labeled log data, w…
CP-Router: An Uncertainty-Aware Router Between LLM and LRM
Jiayuan Su, Fulin Lin, Zhaopeng Feng +7
Recent advances in Large Reasoning Models (LRMs) have significantly improved long-chain reasoning capabilities over Large Language Models (LLMs). However, LRMs often produce unnece…
Temporal Attention Evolutional Graph Convolutional Network for Multivariate Time Series Forecasting
Xinlong Zhao, Liying Zhang, Tianbo Zou +1
Multivariate time series forecasting enables the prediction of future states by leveraging historical data, thereby facilitating decision-making processes. Each data node in a mult…
Fine-grained spatial-temporal perception for gas leak segmentation
Xinlong Zhao, Shan Du
Gas leaks pose significant risks to human health and the environment. Despite long-standing concerns, there are limited methods that can efficiently and accurately detect and segme…
PerfSeer: An Efficient and Accurate Deep Learning Models Performance Predictor
Xinlong Zhao, Jiande Sun, Jia Zhang +4
Predicting the performance of deep learning (DL) models, such as execution time and resource utilization, is crucial for Neural Architecture Search (NAS), DL cluster schedulers, an…