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From the 1 of 10 linked papers with an AI index.

collaborators

10 papers

cs.AI2026

Adaptive Arena-based Contestable Argumentative Network-of-Experts for Open-Ended Care Plan Coordination

Truong Thanh Hung Nguyen, Hoang-Loc Cao, Phuc Ho +3

Care plan coordination demands synthesizing heterogeneous clinical, functional, and psychosocial information across multiple professional disciplines, where monolithic LLM pipeline…

cs.AI2026

CoPlan: A Trustworthy Co-Intelligence Interface for Care Planning through Role-Based Contestable Argument Graphs

Hung Truong Thanh Nguyen, Hélène Fournier, Piper Jackson +4

AI-supported care planning can help clinicians, patients, caregivers, and care teams coordinate complex decisions across clinical, functional, psychosocial, and environmental needs…

cs.AI2026

Self-Evolving Human-Centered Framework for Explainable Depression Symptom Annotation

Hoang-Loc Cao, Van Pham, Truong Thanh Hung Nguyen +4

The paper proposes a self‑evolving, expert‑in‑the‑loop framework that uses large language models to generate and refine depression symptom annotations aligned with DSM‑5‑TR criteri…

cs.PF2026

Does Mixture-of-Experts Actually Help Inference on Consumer and Edge Hardware? An Empirical Study

Alfarizy Alfarizy, Hung Truong Thanh Nguyen, René Richard +2

Mixture-of-Experts (MoE) language models are often described as ideal for resource-constrained inference. Each token activates only a small subset of experts, so the per-token comp…

cs.AI2026

Consensus-based Agentic Large Language Model Framework for Harmonized Tariff Schedule Code Classification

Truong Thanh Hung Nguyen, Khanh Van Quynh Nguyen, Hoang-Loc Cao +5

Accurate Harmonized Tariff Schedule (HTS) code classification is essential for customs clearance, duty assessment, trade statistics, and regulatory compliance in maritime logistics…

cs.MM2026

Contestable Multi-Agent Debate with Arena-based Argumentative Computation for Multimedia Verification

Truong Thanh Hung Nguyen, Vo Thanh Khang Nguyen, Hoang-Loc Cao +3

Multimedia verification requires not only accurate conclusions but also transparent and contestable reasoning. We propose a contestable multi-agent framework that integrates multim…