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Open access Aug 2025

SynthCoder: Anti-pattern identification and model training for FIM mode code completion

This work introduces SynthCoder, which adopts optimized masking strategies better aligned with developer’s expectation in FIM, and first refine AST-level node masking and add heuristics that better mimic developers’ expectation to construct the training corpora.

Dong-Jun Yu, Xiao Yan, Zhen-Rui Li et al. · 1 citation

Hunk-Constrained DPO: Segment-Level Optimization for Secure and Correct LLM Code Generation

Hunk-Constrained Direct Preference Optimization is introduced, a training framework that unifies security hardening and functional correction in large language models and demonstrates that HPO achieves substantial security improvements—up to 28 percentage points—while preserving or enhancing functional correctness.

Qian-Shuo Huang, Xin Yin, Xin-Rui Li et al. · 0 citations
#small language model Preprint Aug 2026

Vulnerable Code Search: Transferable Attack for Code Language Models

This paper introduces a programming language-agnostic, transferable, adversarial attack that exploits this CLM vulnerability and demonstrates that this attack, even when computed using smaller code embedding models, is highly effective and transferable to larger, closed-source embedding models.

Kaicheng Wang, Li-Yan Huang, Jesse Thomason et al. · 0 citations
#small language model Preprint Sep 2026

Towards Behavior Tree-Guided Vulnerability Detection with Lightweight LLMs

Investigating Behavior Trees (BTs) as an alternative intermediate representation for LLM-based vulnerability detection suggests that BTs can provide a compact and useful structured representation for vulnerability detection with quantized, locally deployable LLMs.

Enna Bašić, A. Giaretta · 0 citations
#artificial intelligence Preprint Sep 2026

JevVibe: Efficient Classification-Guided Secure Code Generation

This work evaluates Jev, a decision model that instead selects directly from a declared set of candidates and returns a probability for each, against six open-weight autoregressive models and a frontier proprietary model, and builds JevVibe, a diagnosis-guided repair agent that uses predicted CWE labels to repair code...

Arshak Rezvani, Sasha Behrouzi, Ahmad Sadeghi · 0 citations
Open access Aug 2026

Selecting and Combining Large Language Models in Scalable Code Clone Detection

Findings indicate that ensembling approaches can be statistically significant and effective on larger datasets, where the best-performing ensemble improved performance by 37% over its individual LLMs on the commercial large-scale code.

M. Chochlov, Gul Aftab Ahmed, J. Patten et al. · 1 citation

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