2 citations · 4 across the 19 of their papers we have counts for
21 papers
Playing social deduction games with reinforcement fine-tuned large language models
Lingzhe Zhang, Yunpeng Zhai, Tong Jia +7
Reinforcement fine-tuning (RFT) is increasingly used in applications where large language models (LLMs) interact with humans and other agents. Here we use social deduction games to…
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…
How Much Parallelism Is "Free"? A Principle of Near-Free Parallelism for Parallel Decoding
Minghua He, Lingzhe Zhang, Yuan Liu +2
Parallel decoding improves generation efficiency by processing multiple decode positions within a single decode forward, but reported speedups conflate algorithmic token utilizatio…
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 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…
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…
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…
RuntimeSlicer: Towards Generalizable Unified Runtime State Representation for Failure Management
Lingzhe Zhang, Tong Jia, Weijie Hong +9
Modern software systems operate at unprecedented scale and complexity, where effective failure management is critical yet increasingly challenging. Metrics, traces, and logs provid…
Hypothesize-Then-Verify: Speculative Root Cause Analysis for Microservices with Pathwise Parallelism
Lingzhe Zhang, Tong Jia, Yunpeng Zhai +5
Microservice systems have become the backbone of cloud-native enterprise applications due to their resource elasticity, loosely coupled architecture, and lightweight deployment. Ye…
Agentic Memory Enhanced Recursive Reasoning for Root Cause Localization in Microservices
Lingzhe Zhang, Tong Jia, Yunpeng Zhai +5
As contemporary microservice systems become increasingly popular and complex-often comprising hundreds or even thousands of fine-grained, interdependent subsystems-they are experie…
VarParser: Unleashing the Neglected Power of Variables for LLM-based Log Parsing
Jinrui Sun, Tong Jia, Minghua He +1
Logs serve as a primary source of information for engineers to diagnose failures in large-scale online service systems. Log parsing, which extracts structured events from massive u…
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…
MicroRemed: Benchmarking LLMs in Microservices Remediation
Lingzhe Zhang, Yunpeng Zhai, Tong Jia +6
Large Language Models (LLMs) integrated with agent-based reasoning frameworks have recently shown strong potential for autonomous decision-making and system-level operations. One p…
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…
LogAction: Consistent Cross-system Anomaly Detection through Logs via Active Domain Adaptation
Chiming Duan, Minghua He, Pei Xiao +11
Log-based anomaly detection is a essential task for ensuring the reliability and performance of software systems. However, the performance of existing anomaly detection methods hea…
United We Stand: Towards End-to-End Log-based Fault Diagnosis via Interactive Multi-Task Learning
Minghua He, Chiming Duan, Pei Xiao +8
Log-based fault diagnosis is essential for maintaining software system availability. However, existing fault diagnosis methods are built using a task-independent manner, which fail…
Walk the Talk: Is Your Log-based Software Reliability Maintenance System Really Reliable?
Minghua He, Tong Jia, Chiming Duan +6
Log-based software reliability maintenance systems are crucial for sustaining stable customer experience. However, existing deep learning-based methods represent a black box for se…
Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thought
Lingzhe Zhang, Tong Jia, Kangjin Wang +4
As contemporary microservice systems become increasingly popular and complex-often comprising hundreds or even thousands of fine-grained, interdependent subsystems-they are facing…
A Survey on Parallel Text Generation: From Parallel Decoding to Diffusion Language Models
Lingzhe Zhang, Liancheng Fang, Chiming Duan +8
As text generation has become a core capability of modern Large Language Models (LLMs), it underpins a wide range of downstream applications. However, most existing LLMs rely on au…
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…