10 citations · 21 across the 16 of their papers we have counts for
19 papers
Cowork-Gym: Synthesizing Interactive Work Environments at Scale
Anni Zou, Cheng Chen, Jiaji Deng +18
Cowork agents navigate dependencies across tools and files while adapting to changing user requirements and edits to shared workspaces. Scaling such environments requires maintaini…
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…
RLCSD: Reinforcement Learning with Contrastive On-Policy Self-Distillation
Leyi Pan, Shuchang Tao, Yunpeng Zhai +5
On-policy self-distillation (OPSD) provides dense, token-level supervision for reasoning models by aligning a model's own distribution with that under privileged context, typically…
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…
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…
CuES: A Curiosity-driven and Environment-grounded Synthesis Framework for Agentic RL
Shinji Mai, Yunpeng Zhai, Ziqian Chen +5
Large language model based agents are increasingly deployed in complex, tool augmented environments. While reinforcement learning provides a principled mechanism for such agents to…
d-TreeRPO: Towards More Reliable Policy Optimization for Diffusion Language Models
Leyi Pan, Shuchang Tao, Yunpeng Zhai +8
Reinforcement learning (RL) is pivotal for enhancing the reasoning capabilities of diffusion large language models (dLLMs). However, existing dLLM policy optimization methods suffe…
AgentEvolver: Towards Efficient Self-Evolving Agent System
Yunpeng Zhai, Shuchang Tao, Cheng Chen +10
Autonomous agents powered by large language models (LLMs) have the potential to significantly enhance human productivity by reasoning, using tools, and executing complex tasks in d…
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…
Auto-Rubric: Learning From Implicit Weights to Explicit Rubrics for Reward Modeling
Lipeng Xie, Sen Huang, Zhuo Zhang +9
Conventional reward modeling relies on gradient descent over neural weights, creating opaque, data-hungry "black boxes." We propose a paradigm shift from implicit to explicit rewar…
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…
Omni-SafetyBench: A Benchmark for Safety Evaluation of Audio-Visual Large Language Models
Leyi Pan, Zheyu Fu, Yunpeng Zhai +9
Omni-modal Large Language Models (OLLMs) that integrate visual, auditory, and textual processing face severe safety risks. They exhibit fragile defenses against audio-visual joint…
Provoking Multi-modal Few-Shot LVLM via Exploration-Exploitation In-Context Learning
Cheng Chen, Yunpeng Zhai, Yifan Zhao +3
In-context learning (ICL), a predominant trend in instruction learning, aims at enhancing the performance of large language models by providing clear task guidance and examples, im…
Contrastive Learning for Continuous Touch-Based Authentication
Mengyu Qiao, Yunpeng Zhai, Yang Wang
Smart mobile devices have become indispensable in modern daily life, where sensitive information is frequently processed, stored, and transmitted-posing critical demands for robust…
AgentFM: Role-Aware Failure Management for Distributed Databases with LLM-Driven Multi-Agents
Lingzhe Zhang, Yunpeng Zhai, Tong Jia +3
Distributed databases are critical infrastructures for today's large-scale software systems, making effective failure management essential to ensure software availability. However,…
ThinkFL: Self-Refining Failure Localization for Microservice Systems via Reinforcement Fine-Tuning
Lingzhe Zhang, Yunpeng Zhai, Tong Jia +6
As modern microservice systems grow increasingly popular and complex-often consisting of hundreds or even thousands of fine-grained, interdependent components-they are becoming mor…