collaborators

24 papers

cs.SE2026

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…

cs.CE2026

From Feedback Loops to Policy Updates: Reinforcement Fine-Tuning for LLM-Based Alpha Factor Discovery

Lingzhe Zhang, Tong Jia, Yunpeng Zhai +5

Modern quantitative trading increasingly relies on systematic models to extract predictive signals from large-scale financial data, where alpha factor discovery plays a central rol…

cs.SE2026

Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thought

Lingzhe Zhang, Tong Jia, Kangjin Wang +8

As modern microservice systems grow increasingly complex due to dynamic interactions and evolving runtime environments, they experience failures with rising frequency. Ensuring sys…

cs.SE2026

Towards Robust LLM Post-Training: Automatic Failure Management for Reinforcement Fine-Tuning

Lingzhe Zhang, Tong Jia, Yunpeng Zhai +6

Reinforcement fine-tuning (RFT) has become a core paradigm for post-training large language models, yet its training process remains highly fragile. Existing efforts mainly improve…

cs.SE2026

E2E-REME: Towards End-to-End Microservices Auto-Remediation via Experience-Simulation Reinforcement Fine-Tuning

Lingzhe Zhang, Yunpeng Zhai, Tong Jia +5

Contemporary microservice systems continue to grow in scale and complexity, leading to increasingly frequent and costly failures. While recent LLM-based auto-remediation approaches…

cs.LG2026

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…