5 citations · 7 across the 2 of their papers we have counts for
8 papers · 1 filter
R1-T1: Fully Incentivizing Translation Capability in LLMs via Reasoning Learning
Minggui He, Yilun Liu, Shimin Tao +10
Despite recent breakthroughs in reasoning-enhanced large language models (LLMs) like DeepSeek-R1, incorporating inference-time reasoning into machine translation (MT), where human…
Adapting Large Language Models to Log Analysis with Interpretable Domain Knowledge
Yuhe Ji, Yilun Liu, Feiyu Yao +10
Log analysis represents a critical sub-domain within AI applications that facilitates automatic approaches to fault and error management of large-scaled software systems, saving la…
Why Not Transform Chat Large Language Models to Non-English?
Xiang Geng, Ming Zhu, Jiahuan Li +14
The scarcity of non-English data limits the development of non-English large language models (LLMs). Transforming English-centric LLMs to non-English has been identified as an effe…
From Handcrafted Features to LLMs: A Brief Survey for Machine Translation Quality Estimation
Haofei Zhao, Yilun Liu, Shimin Tao +6
Machine Translation Quality Estimation (MTQE) is the task of estimating the quality of machine-translated text in real time without the need for reference translations, which is of…
UCorrect: An Unsupervised Framework for Automatic Speech Recognition Error Correction
Jiaxin Guo, Minghan Wang, Xiaosong Qiao +9
Error correction techniques have been used to refine the output sentences from automatic speech recognition (ASR) models and achieve a lower word error rate (WER). Previous works u…
Using Large Language Model for End-to-End Chinese ASR and NER
Yuang Li, Jiawei Yu, Min Zhang +6
Mapping speech tokens to the same feature space as text tokens has become the paradigm for the integration of speech modality into decoder-only large language models (LLMs). An alt…