activity
20192026
most citedTowards Efficient Post-training Quantization of Pre-trained Language Models

21 citations · 116 across the 61 of their papers we have counts for

collaborators
Showing cs.SEShow all

48 papers · 1 filter

cs.SE2026

MicroAgent: Context-Augmented Multi-Agent Framework for Automatic Microservice Decomposition

Zishan Su, Junjie Huang, Shiwen Shan +5

The adoption of Microservice Architecture (MSA) has revolutionized software engineering by enhancing scalability, agility, and maintainability over traditional monolithic applicati…

cs.SE2026

SWE-MeM: Learning Adaptive Memory Management for Long-Horizon Coding Agents

Shuzheng Gao, Wenhao Zeng, Zhaojian Yu +5

Long-horizon software engineering agents often need to manage lengthy and noisy interaction histories under limited context budgets. Existing memory management methods typically re…

cs.SE2026

Cascaded Code Editing: Large-Small Model Collaboration for Effective and Efficient Code Editing

Chaozheng Wang, Zezhou Yang, Shuzheng Gao +7

Code editing constitutes a fundamental practice in software development, wherein developers modify existing codebases according to natural language requirements. Accurate code edit…

cs.SE2026

ComBench: A Repo-level Real-world Benchmark for Compilation Error Repair

Jia Li, Zeyang Zhuang, Zhuangbin Chen +3

Compilation errors pose pervasive and critical challenges in software development, significantly hindering productivity. Therefore, Automated Compilation Error Repair (ACER) techni…

cs.SE2026

ComUICoder: Component-based Reusable UI Code Generation for Complex Websites via Semantic Segmentation and Element-wise Feedback

Jingyu Xiao, Jiantong Qin, Shuoqi Li +5

Multimodal Large Language Models (MLLMs) have demonstrated strong performance on the UI-to-code task, which aims to generate UI code from design mock-ups. However, when applied to…

cs.SE2026

Why Does the LLM Stop Computing: An Empirical Study of User-Reported Failures in Open-Source LLMs

Guangba Yu, Zirui Wang, Yujie Huang +4

The democratization of open-source Large Language Models (LLMs) allows users to fine-tune and deploy models on local infrastructure but exposes them to a First Mile deployment land…