2 citations · 3 across the 7 of their papers we have counts for
7 papers · 1 filter
DiscourseFlip: An Oblique Discourse-Level Opinion Manipulation Attack against Black-box Retrieval-Augmented Generation
Yuyang Gong, Miaokun Chen, Jiawei Liu +5
Retrieval-Augmented Generation (RAG) systems are widely deployed and increasingly influential, but their reliance on external corpora exposes new security risks from poisoned retri…
Interweaving Memories of a Siamese Large Language Model
Xin Song, Zhikai Xue, Guoxiu He +2
Parameter-efficient fine-tuning (PEFT) methods optimize large language models (LLMs) by modifying or introducing a small number of parameters to enhance alignment with downstream t…
Recurrent Alignment with Hard Attention for Hierarchical Text Rating
Chenxi Lin, Jiayu Ren, Guoxiu He +3
While large language models (LLMs) excel at understanding and generating plain text, they are not tailored to handle hierarchical text structures or directly predict task-specific…
A Role-Selected Sharing Network for Joint Machine-Human Chatting Handoff and Service Satisfaction Analysis
Jiawei Liu, Kaisong Song, Yangyang Kang +5
Chatbot is increasingly thriving in different domains, however, because of unexpected discourse complexity and training data sparseness, its potential distrust hatches vital appreh…
Time to Transfer: Predicting and Evaluating Machine-Human Chatting Handoff
Jiawei Liu, Zhe Gao, Yangyang Kang +5
Is chatbot able to completely replace the human agent? The short answer could be - "it depends...". For some challenging cases, e.g., dialogue's topical spectrum spreads beyond the…
Read Beyond the Lines: Understanding the Implied Textual Meaning via a Skim and Intensive Reading Model
Guoxiu He, Zhe Gao, Zhuoren Jiang +4
The nonliteral interpretation of a text is hard to be understood by machine models due to its high context-sensitivity and heavy usage of figurative language. In this study, inspir…