5 papers
Native Multilingual Chain-of-Thought Reasoning in Low-Resource Southeast Asian Languages
Sean Gip Lim, William Chandra Tjhi, Hai Leong Chieu
Large Language Models have achieved substantial progress in reasoning capabilities. Yet in low-resource native settings, many suffer from cross-lingual collapse, reverting to Engli…
Tokenizer-Agnostic Engram Module
Jia Peng Lim, Hai Leong Chieu
Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relies on token-level -gram ha…
Spokes: Optimizing for Diverse Pretraining Data Selection
Clarence Lee, Yejin Choi, Luke Zettlemoyer +2
Diversity plays a critical role in data selection, improving performance under fixed data budgets by reducing redundancy and repetition. However, optimizing for diversity is inhere…
Lessons from Training Grounded LLMs with Verifiable Rewards
Shang Hong Sim, Tej Deep Pala, Vernon Toh +5
Generating grounded and trustworthy responses remains a key challenge for large language models (LLMs). While retrieval-augmented generation (RAG) with citation-based grounding hol…
Measuring and Enhancing Trustworthiness of LLMs in RAG through Grounded Attributions and Learning to Refuse
Maojia Song, Shang Hong Sim, Rishabh Bhardwaj +3
LLMs are an integral component of retrieval-augmented generation (RAG) systems. While many studies focus on evaluating the overall quality of end-to-end RAG systems, there is a gap…