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Leveraging Linguistic Expertise in NLP: A Deep Dive into RELIES and Its Impact on Large Language Models

Marktechpost

With the significant advancement in the fields of Artificial Intelligence (AI) and Natural Language Processing (NLP), Large Language Models (LLMs) like GPT have gained attention for producing fluent text without explicitly built grammar or semantic modules.

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Integrating Large Language Models with Graph Machine Learning: A Comprehensive Review

Marktechpost

Graph Machine Learning (Graph ML), especially Graph Neural Networks (GNNs), has emerged to effectively model such data, utilizing deep learning’s message-passing mechanism to capture high-order relationships. Foundation Models (FMs) have revolutionized NLP and vision domains in the broader AI spectrum.

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Exploring Parameter-Efficient Fine-Tuning Strategies for Large Language Models

Marktechpost

Large Language Models (LLMs) signify a revolutionary leap in numerous application domains, facilitating impressive accomplishments in diverse tasks. With billions of parameters, these models demand extensive computational resources for operation. Yet, their immense size incurs substantial computational expenses.

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BiomedRAG: Elevating Biomedical Data Analysis with Retrieval-Augmented Generation in Large Language Models

Marktechpost

The emergence of large language models (LLMs) has profoundly influenced the field of biomedicine, providing critical support for synthesizing vast data. These models are instrumental in distilling complex information into understandable and actionable insights. on the GIT and ChemProt datasets, respectively.

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NVIDIA AI Open-Sources ‘NeMo-Aligner’: Transforming Large Language Model Alignment with Efficient Reinforcement Learning

Marktechpost

The large language models (LLMs) research domain emphasizes aligning these models with human preferences to produce helpful, unbiased, and safe responses. A primary challenge in NLP is teaching LLMs to provide responses that align with human preferences, avoiding biases, and generating useful and safe answers.

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EasyQuant: Revolutionizing Large Language Model Quantization with Tencent’s Data-Free Algorithm

Marktechpost

The relentless advancement in natural language processing (NLP) has ushered in an era of large language models (LLMs) capable of performing various complex tasks with unprecedented accuracy. Join our 38k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup.

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Stanford Researchers Innovate in Large Language Model Factuality: Automatic Preference Rankings and NLP Advancements for Error Reduction

Marktechpost

Leveraging recent innovations in NLP, they employ methods to assess factuality through consistency with external knowledge bases and use the direct preference optimization algorithm for fine-tuning. Focusing on open-ended generation settings, it proposes fine-tuning language models for improved factuality without human labeling.