3 papers
cs.CL2025
EpiCoDe: Boosting Model Performance Beyond Training with Extrapolation and Contrastive Decoding
Mingxu Tao, Jie Hu, Mingchuan Yang +3
The remarkable performance of Large language models (LLMs) relies heavily on the availability of abundant high-quality training data. However, the high cost of acquiring annotated…
cs.CL2025
ALOHA: Empowering Multilingual Agent for University Orientation with Hierarchical Retrieval
Mingxu Tao, Bowen Tang, Mingxuan Ma +5
The rise of Large Language Models~(LLMs) revolutionizes information retrieval, allowing users to obtain required answers through complex instructions within conversations. However,…
cs.CL2025
MiLiC-Eval: Benchmarking Multilingual LLMs for China's Minority Languages
Chen Zhang, Mingxu Tao, Zhiyuan Liao +1
Large language models (LLMs) excel in high-resource languages but struggle with low-resource languages (LRLs), particularly those spoken by minority communities in China, such as T…