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From the 1 of 6 linked papers with an AI index.

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6 papers

cs.SE2026

Change2Task: From Repository Changes to Executable Coding Agent Tasks and Environments

Haomin Qi, Xingliang Wang, Xuanqi Gao +9

The paper introduces Change2Task, a system that turns merged pull requests from software repositories into verified, executable coding‑agent tasks by reconstructing the code state…

cs.AR2026

VeriRAG: A Retrieval-Augmented Framework for Automated RTL Testability Repair

Haomin Qi, Yuyang Du, Lihao Zhang +3

Large language models (LLMs) have demonstrated immense potential in computer-aided design (CAD), particularly for automated debugging and verification within electronic design auto…

cs.SE2026

TopoEdge: Topology-Grounded Agentic Framework for Edge Networking Code Generation and Repair

Haomin Qi, Bohan Liu, Zihan Dai +1

TopoEdge is a topology-grounded, edge-deployable framework for end-to-end software-defined networking (SDN) configuration generation and repair, motivated by the brittleness of con…

cs.SE2025

GraphCue for SDN Configuration Code Synthesis

Haomin Qi, Fengfei Yu, Chengbo Huang

We present GraphCue, a topology-grounded retrieval and agent-in-the-loop framework for automated SDN configuration. Each case is abstracted into a JSON graph and embedded using a l…

cs.CL2025

Governance-Aware Hybrid Fine-Tuning for Multilingual Large Language Models

Haomin Qi, Chengbo Huang, Zihan Dai +1

We present a governance-aware hybrid fine-tuning framework for multilingual, low-resource adaptation of large language models. The core algorithm combines gradient-aligned low-rank…

cs.CL2025

Hybrid and Unitary PEFT for Resource-Efficient Large Language Models

Haomin Qi, Zihan Dai, Chengbo Huang

Fine-tuning large language models (LLMs) remains a computational bottleneck due to their scale and memory demands. This paper presents a comprehensive evaluation of parameter-effic…