Owl: A large language model for it operations
With the rapid development of IT operations, it has become increasingly crucial to efficiently
manage and analyze large volumes of data for practical applications. The techniques of …
manage and analyze large volumes of data for practical applications. The techniques of …
C-ICL: contrastive in-context learning for information extraction
There has been increasing interest in exploring the capabilities of advanced large language
models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related …
models (LLMs) in the field of information extraction (IE), specifically focusing on tasks related …
Griprank: Bridging the gap between retrieval and generation via the generative knowledge improved passage ranking
Retrieval-enhanced text generation has shown remarkable progress on knowledge-
intensive language tasks, such as open-domain question answering and knowledge …
intensive language tasks, such as open-domain question answering and knowledge …
Leveraging large language models for enhanced nlp task performance through knowledge distillation and optimized training strategies
Y Huang, K Tang, M Chen - arxiv preprint arxiv:2402.09282, 2024 - arxiv.org
Emerging Large Language Models (LLMs) like GPT-4 have revolutionized Natural
Language Processing (NLP), showing potential in traditional tasks such as Named Entity …
Language Processing (NLP), showing potential in traditional tasks such as Named Entity …
m3P: Towards Multimodal Multilingual Translation with Multimodal Prompt
Multilingual translation supports multiple translation directions by projecting all languages in
a shared space, but the translation quality is undermined by the difference between …
a shared space, but the translation quality is undermined by the difference between …
PEPT: Expert Finding Meets Personalized Pre-training
Finding experts is essential in Community Question Answering (CQA) platforms as it
enables the effective routing of questions to potential users who can provide relevant …
enables the effective routing of questions to potential users who can provide relevant …
mABC: multi-Agent Blockchain-Inspired Collaboration for root cause analysis in micro-services architecture
The escalating complexity of micro-services architecture in cloud-native technologies poses
significant challenges for maintaining system stability and efficiency. To conduct root cause …
significant challenges for maintaining system stability and efficiency. To conduct root cause …
VIPTR: A Vision Permutable Extractor for Fast and Efficient Scene Text Recognition
Scene Text Recognition (STR) is a challenging task that involves recognizing text within
images of natural scenes. Although current state-of-the-art models for STR exhibit high …
images of natural scenes. Although current state-of-the-art models for STR exhibit high …
RoNID: new intent discovery with generated-reliable labels and cluster-friendly representations
Abstract New Intent Discovery (NID) strives to identify known and reasonably deduce novel
intent groups in the open-world scenario. But current methods face issues with inaccurate …
intent groups in the open-world scenario. But current methods face issues with inaccurate …
MLAD: A Unified Model for Multi-system Log Anomaly Detection
In spite of the rapid advancements in unsupervised log anomaly detection techniques, the
current mainstream models still necessitate specific training for individual system datasets …
current mainstream models still necessitate specific training for individual system datasets …