2 citations · 3 across the 10 of their papers we have counts for
11 papers · 1 filter
Pruning General Large Language Models into Customized Expert Models
Yirao Zhao, Guizhen Chen, Kenji Kawaguchi +2
Large language models (LLMs) have revolutionized natural language processing, yet their substantial model sizes often require substantial computational resources. To preserve compu…
Analyzing LLMs' Knowledge Boundary Cognition Across Languages Through the Lens of Internal Representations
Chenghao Xiao, Hou Pong Chan, Hao Zhang +4
While understanding the knowledge boundaries of LLMs is crucial to prevent hallucination, research on the knowledge boundaries of LLMs has predominantly focused on English. In this…
Babel: Open Multilingual Large Language Models Serving Over 90% of Global Speakers
Yiran Zhao, Chaoqun Liu, Yue Deng +8
Large language models (LLMs) have revolutionized natural language processing (NLP), yet open-source multilingual LLMs remain scarce, with existing models often limited in language…
LongPO: Long Context Self-Evolution of Large Language Models through Short-to-Long Preference Optimization
Guanzheng Chen, Xin Li, Michael Qizhe Shieh +1
Large Language Models (LLMs) have demonstrated remarkable capabilities through pretraining and alignment. However, superior short-context LLMs may underperform in long-context scen…
SeaExam and SeaBench: Benchmarking LLMs with Local Multilingual Questions in Southeast Asia
Chaoqun Liu, Wenxuan Zhang, Jiahao Ying +3
This study introduces two novel benchmarks, SeaExam and SeaBench, designed to evaluate the capabilities of Large Language Models (LLMs) in Southeast Asian (SEA) application scenari…
FINEREASON: Evaluating and Improving LLMs' Deliberate Reasoning through Reflective Puzzle Solving
Guizhen Chen, Weiwen Xu, Hao Zhang +6
Many challenging reasoning tasks require not just rapid, intuitive responses, but a more deliberate, multi-step approach. Recent progress in large language models (LLMs) highlights…