Author

Tien N. Nguyen

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Book Open access Aug 2026

Post-hoc Attention Steering of Large Language Models for Robust Code Understanding under Obfuscation

This work proposes CodeSteer, a novel attention steering approach that reallocates model attention toward semantically relevant program elements, including backward slices for output prediction and control-flow paths for execution reasoning in large language models.

Xiao-Kai Rong, Aashish Yadavally, Tien N. Nguyen · Proceedings of the 41st IEEE... · 0 citations

Open access Aug 2026

On Behavioral Alignment of Model-Code and Human-Code Understandability via Behavioral Proxies

It is demonstrated that semantic self-consistency is a reliable and extensible measure to be used as a behavioral proxy for quantifying model code understandability, with broad implications in both software engineering research and practice.

Xiao-Kai Rong, Aashish Yadavally, Hridya Dhulipala et al. · Proceedings of the ACM on So... · 0 citations

#artificial intelligence Preprint Sep 2026

Can LLMs Reason About Runtime Behavior? A Repository-Level Dynamic Benchmark

SWE-Flux is introduced, a repository-level benchmark for dynamic execution reasoning containing 480 execution-grounded instances across 12 real Python repositories, with gold answers automatically harvested from instrumented test executions rather than written manually or judged by LLMs.

Hamed Taherkhani, Mohammad Abdollahi, Melika Sepidband et al. · 0 citations

#artificial intelligence Preprint Sep 2026

Beyond Single-Negative Preference: Multi-Negative DPO for LLM-Centric Historical Entity Linking

Multi-negative direct preference optimisation (MDPO), a reference-based pairwise objective that compares the correct entity with all valid rejected candidates associated with each mention, demonstrates that incorporating all within-instance negative candidates is a simple and effective improvement for LLM-based histori...

Tien N. Nguyen, Emanuela Boros, Ahmed Hamdi et al. · 0 citations

Preprint Aug 2026

W-RAG: Source-Aware Retrieval for Enterprise Document Generation from Heterogeneous Knowledge Bases

W-RAG is proposed, a source-aware retrieval framework that performs ontology-guided retrieval, local ranking within each knowledge base, and source-level weighting to regulate evidence composition to improve document coverage and generation quality.

Hridya Dhulipala, Rajesh Ombase, Michael Wang et al. · 0 citations

Preprint Jul 2026

Teaching Code LLMs to Reason with Intermediate Formal Specifications

This paper introduces SpecCoder, a verification-guided CodeLLM training framework that learns from validated reference programs, behavior-changing mutants, and multi-turn specification-refinement traces, and improves checkpoint-specification quality over base CodeLLMs, and introduces HumanExec, a benchmark built from r...

Minh Le-Anh, Cuong Chi Le, Tien N. Nguyen · 0 citations