Large language models for generative information extraction: A survey
Abstract Information Extraction (IE) aims to extract structural knowledge from plain natural
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …
language texts. Recently, generative Large Language Models (LLMs) have demonstrated …
From google gemini to openai q*(q-star): A survey of reshaping the generative artificial intelligence (ai) research landscape
This comprehensive survey explored the evolving landscape of generative Artificial
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Intelligence (AI), with a specific focus on the transformative impacts of Mixture of Experts …
Large language model based long-tail query rewriting in taobao search
W Peng, G Li, Y Jiang, Z Wang, D Ou, X Zeng… - … Proceedings of the …, 2024 - dl.acm.org
In the realm of e-commerce search, the significance of semantic matching cannot be
overstated, as it directly impacts both user experience and company revenue. Along this …
overstated, as it directly impacts both user experience and company revenue. Along this …
Enhancing question answering for enterprise knowledge bases using large language models
Efficient knowledge management plays a pivotal role in augmenting both the operational
efficiency and the innovative capacity of businesses and organizations. By indexing …
efficiency and the innovative capacity of businesses and organizations. By indexing …
User modeling in the era of large language models: Current research and future directions
User modeling (UM) aims to discover patterns or learn representations from user data about
the characteristics of a specific user, such as profile, preference, and personality. The user …
the characteristics of a specific user, such as profile, preference, and personality. The user …
NoteLLM: A Retrievable Large Language Model for Note Recommendation
People enjoy sharing" notes" including their experiences within online communities.
Therefore, recommending notes aligned with user interests has become a crucial task …
Therefore, recommending notes aligned with user interests has become a crucial task …
Sinkt: A structure-aware inductive knowledge tracing model with large language model
Knowledge Tracing (KT) aims to determine whether students will respond correctly to the
next question, which is a crucial task in intelligent tutoring systems (ITS). In educational KT …
next question, which is a crucial task in intelligent tutoring systems (ITS). In educational KT …
[PDF][PDF] A Step Towards Adaptive Online Learning: Exploring the Role of GPT as Virtual Teaching Assistants in Online Education
X Liu, M Pankiewicz, T Gupta… - Manuscript under …, 2024 - learninganalytics.upenn.edu
As student learning transitions to being increasingly 24/7, online courses struggle to provide
support for learners on the same schedule. Human TAs are bound by time constraints and …
support for learners on the same schedule. Human TAs are bound by time constraints and …
Bridging the information gap between domain-specific model and general llm for personalized recommendation
Personalized recommendation is widely applicable in various domains like e-commerce and
social media. Few recent research efforts have attempted to design general large language …
social media. Few recent research efforts have attempted to design general large language …
Randomized Geometric Algebra Methods for Convex Neural Networks
Y Wang, S Kim, P Chu, I Subramaniam… - arXiv preprint arXiv …, 2024 - arxiv.org
We introduce randomized algorithms to Clifford's Geometric Algebra, generalizing
randomized linear algebra to hypercomplex vector spaces. This novel approach has many …
randomized linear algebra to hypercomplex vector spaces. This novel approach has many …