5 papers
Equity with Efficiency: An Empirical Study of Tokenizers for Multilingual Large Language Models
Kieron Seven Jun Wei Lee, Muhammad Reza Qorib, Andrew Ivan Soegeng +1
Multilingual large language models (LLMs) depend on subword tokenization to bridge discrete text and continuous neural representation. State-of-the-art multilingual LLMs often use…
Parametric Knowledge is Not All You Need: Toward Honest Large Language Models via Retrieval of Pretraining Data
Christopher Adrian Kusuma, Muhammad Reza Qorib, Hwee Tou Ng
Large language models (LLMs) are highly capable of answering questions, but they are often unaware of their own knowledge boundary, i.e., knowing what they know and what they don't…
OpenSeal: Good, Fast, and Cheap Construction of an Open-Source Southeast Asian LLM via Parallel Data
Tan Sang Nguyen, Muhammad Reza Qorib, Hwee Tou Ng
Large language models (LLMs) have proven to be effective tools for a wide range of natural language processing (NLP) applications. Although many LLMs are multilingual, most remain…
Just What You Desire: Constrained Timeline Summarization with Self-Reflection for Enhanced Relevance
Muhammad Reza Qorib, Qisheng Hu, Hwee Tou Ng
Given news articles about an entity, such as a public figure or organization, timeline summarization (TLS) involves generating a timeline that summarizes the key events about the e…
Efficient and Interpretable Grammatical Error Correction with Mixture of Experts
Muhammad Reza Qorib, Alham Fikri Aji, Hwee Tou Ng
Error type information has been widely used to improve the performance of grammatical error correction (GEC) models, whether for generating corrections, re-ranking them, or combini…