A survey on lora of large language models
Y Mao, Y Ge, Y Fan, W Xu, Y Mi, Z Hu… - Frontiers of Computer …, 2025 - Springer
Abstract Low-Rank Adaptation (LoRA), which updates the dense neural network layers with
pluggable low-rank matrices, is one of the best performed parameter efficient fine-tuning …
pluggable low-rank matrices, is one of the best performed parameter efficient fine-tuning …
[HTML][HTML] LLMs in e-commerce: a comparative analysis of GPT and LLaMA models in product review evaluation
E-commerce has witnessed remarkable growth, especially following the easing of COVID-19
restrictions. Many people, who were initially hesitant about online shop**, have now …
restrictions. Many people, who were initially hesitant about online shop**, have now …
[HTML][HTML] Knowledge extraction for additive manufacturing process via named entity recognition with LLMs
This paper proposes a novel NER framework, leveraging the advanced capabilities of Large
Language Models (LLMs), to address the limitations of manually defined taxonomy. Our …
Language Models (LLMs), to address the limitations of manually defined taxonomy. Our …
Looking right is sometimes right: Investigating the capabilities of decoder-only llms for sequence labeling
Pre-trained language models based on masked language modeling (MLM) excel in natural
language understanding (NLU) tasks. While fine-tuned MLM-based encoders consistently …
language understanding (NLU) tasks. While fine-tuned MLM-based encoders consistently …
Tc-llama 2: fine-tuning LLM for technology and commercialization applications
This paper introduces TC-Llama 2, a novel application of large language models (LLMs) in
the technology-commercialization field. Traditional methods in this field, reliant on statistical …
the technology-commercialization field. Traditional methods in this field, reliant on statistical …
Toponym resolution leveraging lightweight and open-source large language models and geo-knowledge
Toponym resolution is crucial for extracting geographic information from natural language
texts, such as social media posts and news articles. Despite the advancements in current …
texts, such as social media posts and news articles. Despite the advancements in current …
Preserving generalization of language models in few-shot continual relation extraction
Few-shot Continual Relations Extraction (FCRE) is an emerging and dynamic area of study
where models can sequentially integrate knowledge from new relations with limited labeled …
where models can sequentially integrate knowledge from new relations with limited labeled …
Ceptner: contrastive learning enhanced prototypical network for two-stage few-shot named entity recognition
E Zha, D Zeng, M Lin, Y Shen - Knowledge-Based Systems, 2024 - Elsevier
Abstract Few-shot Named Entity Recognition (NER) systems aim to classify unseen named
entity types with limited labeled examples. Significant progress has been made in the use of …
entity types with limited labeled examples. Significant progress has been made in the use of …
Political-llm: Large language models in political science
In recent years, large language models (LLMs) have been widely adopted in political
science tasks such as election prediction, sentiment analysis, policy impact assessment, and …
science tasks such as election prediction, sentiment analysis, policy impact assessment, and …
OmEGa (Ω): Ontology-based information extraction framework for constructing task-centric knowledge graph from manufacturing documents with large language …
Manufacturing industry relies heavily on technical documents that encapsulate specialized
knowledge essential for optimizing production and maintenance processes. However …
knowledge essential for optimizing production and maintenance processes. However …