Zobrazeno 1 - 10
of 74
pro vyhledávání: '"Hu Linmei"'
Sequential recommender systems are essential for discerning user preferences from historical interactions and facilitating targeted recommendations. Recent innovations employing Large Language Models (LLMs) have advanced the field by encoding item se
Externí odkaz:
http://arxiv.org/abs/2409.01605
Autor:
Yao, Zijun, Qi, Weijian, Pan, Liangming, Cao, Shulin, Hu, Linmei, Liu, Weichuan, Hou, Lei, Li, Juanzi
This paper introduces Self-aware Knowledge Retrieval (SeaKR), a novel adaptive RAG model that extracts self-aware uncertainty of LLMs from their internal states. SeaKR activates retrieval when the LLMs present high self-aware uncertainty for generati
Externí odkaz:
http://arxiv.org/abs/2406.19215
Personality detection aims to detect one's personality traits underlying in social media posts. One challenge of this task is the scarcity of ground-truth personality traits which are collected from self-report questionnaires. Most existing methods l
Externí odkaz:
http://arxiv.org/abs/2403.07581
Program induction (PI) has become a promising paradigm for using knowledge bases (KBs) to help large language models (LLMs) answer complex knowledge-intensive questions. Nonetheless, PI typically relies on a large number of parallel question-program
Externí odkaz:
http://arxiv.org/abs/2402.01619
Autor:
Liu, Jinxin, Cao, Shulin, Shi, Jiaxin, Zhang, Tingjian, Nie, Lunyiu, Hu, Linmei, Hou, Lei, Li, Juanzi
Knowledge Base Question Answering (KBQA) aims to answer natural language questions based on facts in knowledge bases. A typical approach to KBQA is semantic parsing, which translates a question into an executable logical form in a formal language. Re
Externí odkaz:
http://arxiv.org/abs/2401.05777
Autor:
Luo, Ruipu, Zhao, Ziwang, Yang, Min, Dong, Junwei, Li, Da, Lu, Pengcheng, Wang, Tao, Hu, Linmei, Qiu, Minghui, Wei, Zhongyu
Large language models (LLMs), with their remarkable conversational capabilities, have demonstrated impressive performance across various applications and have emerged as formidable AI assistants. In view of this, it raises an intuitive question: Can
Externí odkaz:
http://arxiv.org/abs/2306.07207
The merging of human intelligence and artificial intelligence has long been a subject of interest in both science fiction and academia. In this paper, we introduce a novel concept in Human-AI interaction called Symbiotic Artificial Intelligence with
Externí odkaz:
http://arxiv.org/abs/2305.19278
Dialogue-based language models mark a huge milestone in the field of artificial intelligence, by their impressive ability to interact with users, as well as a series of challenging tasks prompted by customized instructions. However, the prevalent lar
Externí odkaz:
http://arxiv.org/abs/2304.12998
Fake news often involves multimedia information such as text and image to mislead readers, proliferating and expanding its influence. Most existing fake news detection methods apply the co-attention mechanism to fuse multimodal features while ignorin
Externí odkaz:
http://arxiv.org/abs/2212.05699
Pre-trained Language Models (PLMs) which are trained on large text corpus via self-supervised learning method, have yielded promising performance on various tasks in Natural Language Processing (NLP). However, though PLMs with huge parameters can eff
Externí odkaz:
http://arxiv.org/abs/2211.05994