3 papers
cs.CL2026
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…
cs.LG2026
On DeepSeekMoE: Statistical Benefits of Shared Experts and Normalized Sigmoid Gating
Huy Nguyen, Thong T. Doan, Quang Pham +3
Mixture of experts (MoE) methods are a key component in most large language model architectures, including the recent series of DeepSeek models. Compared to other MoE implementatio…
cs.SE2025
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…