[HTML][HTML] A survey of large language models for healthcare: from data, technology, and applications to accountability and ethics
The utilization of large language models (LLMs) for Healthcare has generated both
excitement and concern due to their ability to effectively respond to free-text queries with …
excitement and concern due to their ability to effectively respond to free-text queries with …
A survey on semantic processing techniques
Semantic processing is a fundamental research domain in computational linguistics. In the
era of powerful pre-trained language models and large language models, the advancement …
era of powerful pre-trained language models and large language models, the advancement …
A cross-guidance cross-lingual model on generated parallel corpus for classical Chinese machine reading comprehension
Chinese diachronic gap is a key issue in classical Chinese machine reading
comprehension (CCMRC). Preceding work on bridging this gap has been mostly restricted …
comprehension (CCMRC). Preceding work on bridging this gap has been mostly restricted …
Hybrid large language model approach for prompt and sensitive defect management: A comparative analysis of hybrid, non-hybrid, and GraphRAG approaches
This study aims to propose a large language model (LLM)-enhanced defect question-
answering (QA) method that can secure private and sensitive data while yielding high …
answering (QA) method that can secure private and sensitive data while yielding high …
[HTML][HTML] Interoperable information modelling leveraging asset administration shell and large language model for quality control toward zero defect manufacturing
In the era of Industry 4.0, Zero Defect Manufacturing (ZDM) has emerged as a prominent
strategy for quality improvement, emphasizing data-driven approaches for defect prediction …
strategy for quality improvement, emphasizing data-driven approaches for defect prediction …
[HTML][HTML] Global information-aware argument mining based on a top-down multi-turn QA model
Argument mining (AM) aims to automatically generate a graph that represents the argument
structure of a document. Most previous AM models only pay attention to a single argument …
structure of a document. Most previous AM models only pay attention to a single argument …
A T5-based interpretable reading comprehension model with more accurate evidence training
B Guan, X Zhu, S Yuan - Information Processing & Management, 2024 - Elsevier
Pre-trained language models (PLMs) have achieved outstanding performance on Machine
Reading Comprehension (MRC) tasks, but these models' interpretability remains uncertain …
Reading Comprehension (MRC) tasks, but these models' interpretability remains uncertain …
MTMS: Multi-teacher Multi-stage Knowledge Distillation for Reasoning-Based Machine Reading Comprehension
As the field of machine reading comprehension (MRC) continues to evolve, it is unlocking
enormous potential for its practical application. However, the currently well-performing …
enormous potential for its practical application. However, the currently well-performing …
Disentangled retrieval and reasoning for implicit question answering
To date, most of the existing open-domain question answering (QA) methods focus on
explicit questions where the reasoning steps are mentioned explicitly in the question. In this …
explicit questions where the reasoning steps are mentioned explicitly in the question. In this …
[HTML][HTML] Ask and Ye shall be Answered: Bayesian tag-based collaborative recommendation of trustworthy experts over time in community question answering
Several challenging issues have yet to be jointly addressed in the recommendation of
experts for community question answering, including dynamicity, comprehensive profiling …
experts for community question answering, including dynamicity, comprehensive profiling …