2 citations · 3 across the 6 of their papers we have counts for
5 papers · 1 filter
Coherence-Aware Distributional Evaluation of Open-Ended Text Generation
Jinnuo Liu, Junhao Zhu, Weifeng Jiang +2
Existing open-ended generation metrics measure likelihood, lexical diversity, or distributional similarity in generic representation space, yet can miss fundamental dimensions of q…
Privacy-Preserving Federated Embedding Learning for Localized Retrieval-Augmented Generation
Qianren Mao, Qili Zhang, Hanwen Hao +11
Retrieval-Augmented Generation (RAG) has recently emerged as a promising solution for enhancing the accuracy and credibility of Large Language Models (LLMs), particularly in Questi…
XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generation
Qili Zhang, Qianren Mao, Yangyifei Luo +15
Retrieval-augmented generation (RAG) synergizes the retrieval of pertinent data with the generative capabilities of Large Language Models (LLMs), ensuring that the generated output…
Lightweight Contenders: Navigating Semi-Supervised Text Mining through Peer Collaboration and Self Transcendence
Qianren Mao, Weifeng Jiang, Junnan Liu +5
The semi-supervised learning (SSL) strategy in lightweight models requires reducing annotated samples and facilitating cost-effective inference. However, the constraint on model pa…
DisCo: Distilled Student Models Co-training for Semi-supervised Text Mining
Weifeng Jiang, Qianren Mao, Chenghua Lin +4
Many text mining models are constructed by fine-tuning a large deep pre-trained language model (PLM) in downstream tasks. However, a significant challenge nowadays is maintaining p…