Academic Articles & Research Papers

Large Language Models and the Elliott Wave Principle: A Multi-Agent Deep Learning Approach to Big Data Analysis in Financial Markets

Traditional technical analysis methods face limitations in accurately predicting trends in today’s complex financial markets. Meanwhile, existing AI-driven approaches, while powerful in processing large datasets, often lack interpretability...

Machine Reading Comprehension for the Tamil Language With Translated SQuAD

Machine Reading Comprehension (MRC) is a challenging task in Natural Language Processing (NLP), crucial for automated customer support, enabling chatbots and virtual assistants to accurately understand and respond to queries. It also enhanc...

Menstrual Health Education Using a Specialized Large Language Model in India: Development and Evaluation Study of MenstLLaMA

Abstract BackgroundThe quality and accessibility of menstrual health education (MHE) in low- and middle-income countries, including India, remain inadequate due to persistent challenges (eg, poverty, social stigma, and gender in...

Gender biases in GPT-4 short biographies.

As has been shown in various studies considering different languages, in professional contexts women tend to be referred to differently than men. While men are typically referred to by their surname (e. g., Fermi), women are more often refe...

Evaluation of the accuracy of ChatGPT-4 and Gemini’s responses to the World Dental Federation’s frequently asked questions on oral health

Abstract Background The field of artificial intelligence (AI) has experienced considerable growth in recent years, with the advent of technologies that are transforming a range of industries, including healthcare and dentistry. Large langua...

Framework for evaluating code generation ability of large language models

Large language models (LLMs) have revolutionized various applications in natural language processing and exhibited proficiency in generating programming code. We propose a framework for evaluating the code generation ability of LLMs and int...

Large Language Models in Healthcare and Medical Domain: A Review

The deployment of large language models (LLMs) within the healthcare sector has sparked both enthusiasm and apprehension. These models exhibit the remarkable ability to provide proficient responses to free-text queries, demonstrating a nuan...

Large Language Models and 3D Vision for Intelligent Robotic Perception and Autonomy

With the rapid advancement of artificial intelligence and robotics, the integration of Large Language Models (LLMs) with 3D vision is emerging as a transformative approach to enhancing robotic sensing technologies. This convergence enables ...

Study on Building Business-oriented Resource On-demand Resolution Model

To address the issue of re-analyzing and repeating development of natural language processing tools and resource ana-lysis plugins when new requirements arise during project development,this paper proposes a business-oriented on-demand reso...

Detecting Fake News in Urdu Language Using Machine Learning, Deep Learning, and Large Language Model-Based Approaches

Fake news is false or misleading information that looks like real news and spreads through traditional and social media. It has a big impact on our social lives, especially in politics. In Pakistan, where Urdu is the main language, finding ...

The fluency-based semantic network of LLMs differs from humans

Modern Large Language Models (LLMs) exhibit complexity and granularity similar to humans in the field of natural language processing, challenging the boundaries between humans and machines in language understanding and creativity. However, ...

A diagnostic hierarchy of epistemic betrayal in large language models

Abstract This paper proposes a hierarchy of epistemic betrayal that distinguishes deceptive behaviors in large language models (LLMs) by the depth at which the infrastructure for epistemic correction is compromised. Drawing on Park et al.’s...

An Analysis of the Training Data Impact for Domain-Adapted Tokenizer Performances—The Case of Serbian Legal Domain Adaptation

Various areas of natural language processing (NLP) have greatly benefited from the development of large language models in recent years. This research addresses the challenge of developing efficient tokenizers for transformer-based domain-s...

Specialized Large Language Model for Standardization of Locomotive Maintenance Data

Standardization is one of the key steps to analyze locomotive overhaul data with a focus on reliability-centered maintenance (RCM). However, traditional manual methods encounter challenges such as small sample sizes, non-standardized data f...

An empirical study of LLaMA3 quantization: from LLMs to MLLMs

Abstract The LLaMA family, a collection of foundation language models ranging from 7B to 65B parameters, has become one of the most powerful open-source large language models (LLMs) and the popular LLM backbone of multi-modal large language...

Human Behavior Analysis: A Comprehensive Survey on Techniques, Applications, Challenges, and Future Directions

Human Behavior Analysis (HBA) has emerged as a critical interdisciplinary field, combining psychology, sociology, artificial intelligence, and data science to model, understand, and predict human behavior across diverse domains. This paper ...

HalluciGuard-eye: knowledge graph-enhanced retrieval-augmented generation for hallucination detection and mitigation in ophthalmic multimodal large language models.

Addressing benchmarking gaps in large language models for health and medicine with dynamic red-teaming.

Simulating a virtual tumor board with large language models: a pilot study in NSCLC patients receiving immunotherapy.

An Exploratory Study: Can Vision-Enabled Large Language Models Interpret Selected Static Urologic Images?