Papers by Zhuochen Wang

2 papers
Taming System Complexity: Demystifying Software Engineering Agents in Diagnosing Linux Kernel Faults (2026.acl-long)

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Challenge: Existing LLM agents struggle with identifying bugs in the Linux kernel . bugs can affect billions of users, affecting the Linux Foundation's research on the topic .
Approach: They propose a LinuxFLBench benchmark to measure the accuracy of LLM agents on the Linux kernel.
Outcome: The proposed framework improves FL accuracy with minimal costs.
Datasets and Recipes for Video Temporal Grounding via Reinforcement Learning (2025.emnlp-industry)

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Challenge: Existing methods for video temporal grounding suffer from limited temporal awareness and poor generalization.
Approach: They propose a two-stage training framework that integrates supervised fine-tuning with reinforcement learning to improve both the accuracy and robustness of VTG models.
Outcome: The proposed training framework outperforms existing models on multiple benchmarks on open-domain and challenging scenarios.

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