2 citations · 3 across the 5 of their papers we have counts for
6 papers
CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG
Jianghan Shen, Siqi Luo, Xinyu Cheng +6
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for training agentic retrieval-augmented generation (RAG) systems from outcome-only superv…
It's All About In-Context Learning! Teaching Extremely Low-Resource Languages to LLMs
Yue Li, Zhixue Zhao, Carolina Scarton
Extremely low-resource languages, especially those written in rare scripts, as shown in Figure 1, remain largely unsupported by large language models (LLMs). This is due in part to…
SCRum-9: Multilingual Stance Classification over Rumours on Social Media
Yue Li, Jake Vasilakes, Zhixue Zhao +1
We introduce SCRum-9, the largest multilingual Stance Classification dataset for Rumour analysis in 9 languages, containing 7,516 tweets from X. SCRum-9 goes beyond existing stance…
Label Set Optimization via Activation Distribution Kurtosis for Zero-shot Classification with Generative Models
Yue Li, Zhixue Zhao, Carolina Scarton
In-context learning (ICL) performance is highly sensitive to prompt design, yet the impact of class label options (e.g. lexicon or order) in zero-shot classification remains undere…
Don't Waste a Single Annotation: Improving Single-Label Classifiers Through Soft Labels
Ben Wu, Yue Li, Yida Mu +3
In this paper, we address the limitations of the common data annotation and training methods for objective single-label classification tasks. Typically, when annotating such tasks…
Classifying COVID-19 vaccine narratives
Yue Li, Carolina Scarton, Xingyi Song +1
Vaccine hesitancy is widespread, despite the government's information campaigns and the efforts of the World Health Organisation (WHO). Categorising the topics within vaccine-relat…