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Mingwei Liu

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#artificial intelligence Review Sep 2026

SWE-Gate: Passing Functional Tests Is Not Enough for Software Engineering Agents

Findings show that functional-only evaluation overestimates agents'ability to satisfy the full requirements of repository-level repair tasks, and introduces SWE-Gate, a repository-level benchmark for software engineering agents that explicitly evaluates review constraint compliance alongside functional correctness.

Xin He, Yan-Lin Wang, Ming-Wei Liu et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Efficient SWE Agent Benchmarking via Trajectory-Aware Evaluation

PTA-IRT is proposed, a Privileged Trajectory-Aware Item Response Theory framework that fuses process and outcome signals and consistently outperforms prior IRT baselines on score and ranking recovery across four SWE benchmarks.

Ke-Feng Duan, De-Wu Zheng, Yan-Lin Wang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Adaptive Critical Token-Aware Retrieval for Repository-Level Code Generation

ACToR identifies critical tokens during generation and triggers targeted retrieval on demand to provide repository context at these decisive positions, and designs a position-aware weighting method for dense retrievers to prioritize context that is more informative for generation.

Ke-Feng Duan, De-Wu Zheng, Yan-Lin Wang et al. · 0 citations
Review Jul 2026

WebDesignIter: Co-Evolving Design Knowledge for Repository-Level Front-End Code Generation

This work proposes WebDesignIter, a framework built around a persistent knowledge graph (WebAppArchKG) that fuses repository structure with design knowledge and keeps both in sync across development cycles, and outperforms every general-purpose coding agent Claude Code, OpenHands, SWE-Agent, Codex CLI on every model co...

Zheng Pei, Mingwei Liu, Zhenxi Chen et al. · 1 citation · ⚡1

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