collaborators

5 papers

cs.SE2026

ChainSWE: Benchmarking Coding Agents on Multi-Bug Software Maintenance

Qirui Jin, Lingching Tung, Kenan Li +12

Language model (LM) agents are increasingly deployed to maintain codebases over extended periods, fixing streams of related defects while carrying context from one fix to the next.…

cs.AI2026

Signature-Guided Capacity Occupancy for Dense Expert Merging

Lingching Tung, Chi-Jui Kim, Beicheng Xu +2

Dense expert merging combines domain-specialized language models into one single checkpoint, typically by admitting task-vector support in weight space. However, this admission is…

cs.AI2026

AutoSci: A Memory-Centric Agentic System for the Full Scientific Research Lifecycle

Weitong Qian, Beicheng Xu, Zhongao Xie +16

Scientific research has traditionally been human-intensive, requiring researchers to coordinate literature, ideas, experiments, manuscripts, and review responses across long projec…

cs.DB2026

MFTune: An Efficient Multi-fidelity Framework for Spark SQL Configuration Tuning

Beicheng Xu, Lingching Tung, Yuchen Wang +2

Apache Spark SQL is a cornerstone of modern big data analytics.However,optimizing Spark SQL performance is challenging due to its vast configuration space and the prohibitive cost…

cs.LG2026

Tree-Structured Synergy of Large Language Models and Bayesian Optimization for Efficient CASH

Beicheng Xu, Weitong Qian, Lingching Tung +2

To lower the expertise barrier in machine learning, the AutoML community has focused on the CASH problem, which jointly automates algorithm selection and hyperparameter tuning. Whi…