23 citations · 38 across the 31 of their papers we have counts for
7 papers · 1 filter
SCAR: Data Selection via Style Consistency-Aware Response Ranking for Efficient Instruction-Tuning of Large Language Models
Zhuang Li, Yuncheng Hua, Thuy-Trang Vu +3
Recent studies emphasize that manually ensuring a consistent response style and maintaining high data quality in training sets can significantly improve the performance of fine-tun…
Exploring the Potential of Multimodal LLM with Knowledge-Intensive Multimodal ASR
Minghan Wang, Yuxia Wang, Thuy-Trang Vu +2
Recent advancements in multimodal large language models (MLLMs) have made significant progress in integrating information across various modalities, yet real-world applications in…
Mixture-of-Skills: Learning to Optimize Data Usage for Fine-Tuning Large Language Models
Minghao Wu, Thuy-Trang Vu, Lizhen Qu +1
Large language models (LLMs) are typically fine-tuned on diverse and extensive datasets sourced from various origins to develop a comprehensive range of skills, such as writing, re…
Continual Learning for Large Language Models: A Survey
Tongtong Wu, Linhao Luo, Yuan-Fang Li +3
Large language models (LLMs) are not amenable to frequent re-training, due to high training costs arising from their massive scale. However, updates are necessary to endow LLMs wit…
Direct Evaluation of Chain-of-Thought in Multi-hop Reasoning with Knowledge Graphs
Minh-Vuong Nguyen, Linhao Luo, Fatemeh Shiri +4
Large language models (LLMs) demonstrate strong reasoning abilities when prompted to generate chain-of-thought (CoT) explanations alongside answers. However, previous research on e…
Conversational SimulMT: Efficient Simultaneous Translation with Large Language Models
Minghan Wang, Thuy-Trang Vu, Yuxia Wang +2
Simultaneous machine translation (SimulMT) presents a challenging trade-off between translation quality and latency. Recent studies have shown that LLMs can achieve good performanc…
Adapting Large Language Models for Document-Level Machine Translation
Minghao Wu, Thuy-Trang Vu, Lizhen Qu +2
Large language models (LLMs) have significantly advanced various natural language processing (NLP) tasks. Recent research indicates that moderately-sized LLMs often outperform larg…