4 papers
LIBMoE: A Library for comprehensive benchmarking Mixture of Experts in Large Language Models
Nam V. Nguyen, Thong T. Doan, Luong Tran +2
Mixture of experts (MoE) architectures have become a cornerstone for scaling up and are a key component in most large language models such as GPT-OSS, DeepSeek-V3, Llama-4, and Gem…
SemViQA: A Semantic Question Answering System for Vietnamese Information Fact-Checking
Dien X. Tran, Nam V. Nguyen, Thanh T. Tran +4
The rise of misinformation, exacerbated by Large Language Models (LLMs) like GPT and Gemini, demands robust fact-checking solutions, especially for low-resource languages like Viet…
CompeteSMoE -- Statistically Guaranteed Mixture of Experts Training via Competition
Nam V. Nguyen, Huy Nguyen, Quang Pham +3
Sparse mixture of experts (SMoE) offers an appealing solution to scale up the model complexity beyond the mean of increasing the network's depth or width. However, we argue that ef…
CodeMMLU: A Multi-Task Benchmark for Assessing Code Understanding & Reasoning Capabilities of CodeLLMs
Dung Nguyen Manh, Thang Phan Chau, Nam Le Hai +4
Recent advances in Code Large Language Models (CodeLLMs) have primarily focused on open-ended code generation, often overlooking the crucial aspect of code understanding and reason…