collaborators

7 papers

cs.SE2026

SpecMind: Cognitively Inspired, Interactive Multi-Turn Framework for Postcondition Inference

Cuong Chi Le, Minh V. T Pham, Tung Vu Duy +4

Specifications are vital for ensuring program correctness, yet writing them manually remains challenging and time-intensive. Recent large language model (LLM)-based methods have sh…

cs.CL2026

SealQA: Raising the Bar for Reasoning in Search-Augmented Language Models

Thinh Pham, Nguyen Nguyen, Pratibha Zunjare +3

We introduce SealQA, a new challenge benchmark for evaluating SEarch-Augmented Language models on fact-seeking questions where web search yields conflicting, noisy, or unhelpful re…

cs.AI2026

ROMA: Recursive Open Meta-Agent Framework for Long-Horizon Multi-Agent Systems

Salaheddin Alzu'bi, Baran Nama, Arda Kaz +6

Current agentic frameworks underperform on long-horizon tasks. As reasoning depth increases, sequential orchestration becomes brittle, context windows impose hard limits that degra…

cs.SE2026

TestWeaver: Execution-aware, Feedback-driven Regression Testing Generation with Large Language Models

Cuong Chi Le, Cuong Duc Van, Tung Duy Vu +4

While recent advances in large language models (LLMs) have shown promise in automating test generation for regression testing, they often suffer from limited reasoning about progra…

cs.LG2025

S-Chain: Structured Visual Chain-of-Thought For Medicine

Khai Le-Duc, Duy M. H. Nguyen, Phuong T. H. Trinh +21

Faithful reasoning in medical vision-language models (VLMs) requires not only accurate predictions but also transparent alignment between textual rationales and visual evidence. Wh…

cs.CV2025

PromptGuard: An Orchestrated Prompting Framework for Principled Synthetic Text Generation for Vulnerable Populations using LLMs with Enhanced Safety, Fairness, and Controllability

Tung Vu, Lam Nguyen, Quynh Dao

The proliferation of Large Language Models (LLMs) in real-world applications poses unprecedented risks of generating harmful, biased, or misleading information to vulnerable popula…