23 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…
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…
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…
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…
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…
Efficient Failure Management for Multi-Agent Systems with Reasoning Trace Representation
Lingzhe Zhang, Tong Jia, Mingyu Wang +9
Large Language Models (LLM)-based Multi-Agent Systems (MASs) have emerged as a new paradigm in software system design, increasingly demonstrating strong reasoning and collaboration…