Novel Approach

This research explores novel approaches across diverse fields, aiming to improve existing methods and address limitations in various machine learning and AI applications. Current efforts focus on enhancing model performance and robustness through techniques like active learning, diffusion models, and transformer architectures, often incorporating advanced concepts such as graph isomorphism networks and attention mechanisms. These advancements have significant implications for various domains, including robotics, personalized recommendations, medical image analysis, and cybersecurity, by improving accuracy, efficiency, and interpretability. The overall goal is to create more powerful, reliable, and explainable AI systems.

Papers

October 29, 2024

Saliency-Based diversity and fairness Metric and FaceKeepOriginalAugment: A Novel Approach for Enhancing Fairness and Diversity
Teerath Kumar, Alessandra Mileo, Malika Bendechache
Data Augmentation Procedural Fairness Novel Approach Diversity Awareness Feature Diversity Stereotypical Bias Dataset Diversity Text to Image Association

October 24, 2024

Ali-AUG: Innovative Approaches to Labeled Data Augmentation using One-Step Diffusion Model
Ali Hamza, Aizea Lojo, Adrian Núñez-Marcos, Aitziber Atutxa
Diffusion Model Data Augmentation Novel Approach Soft Augmentation Augmentation Method Diffusion Model Architecture Label Augmentation

October 23, 2024

The Probabilistic Tsetlin Machine: A Novel Approach to Uncertainty Quantification
K. Darshana Abeyrathna, Sara El Mekkaoui, Andreas Hafver, Christian Agrell
Uncertainty Quantification High Uncertainty Anticipation Uncertainty Estimation Bayesian Neural Network Novel Approach Tsetlin Machine

October 21, 2024

October 19, 2024

October 17, 2024

A new approach for fine-tuning sentence transformers for intent classification and out-of-scope detection tasks
Tianyi Zhang, Atta Norouzian, Aanchan Mohan, Frederick Ducatelle
Classification Code Novel Approach Intent Classification Sentence Transformer Scope Detection

October 16, 2024

October 15, 2024

Transformer Layer Injection: A Novel Approach for Efficient Upscaling of Large Language Models
James Vo
Large Language Model Transformer Based Model Novel Approach Transformer Layer Model Scale Effective Depth Up Scaling Arbitrary Upscaling

October 14, 2024

Code-Mixer Ya Nahi: Novel Approaches to Measuring Multilingual LLMs' Code-Mixing Capabilities
Ayushman Gupta, Akhil Bhogal, Kripabandhu Ghosh
Machine Translation Novel Approach Multilingual Large Language Model Language Pair Code Mixed Code Mixing

October 12, 2024

A Novel Approach to Malicious Code Detection Using CNN-BiLSTM and Feature Fusion
Lixia Zhang, Tianxu Liu, Kaihui Shen, Cheng Chen
Novel Approach Feature Fusion Detection Method CNN BiLSTM

October 11, 2024

October 10, 2024

Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models
Wenting Tan, Dongxiao Chen, Jieting Xue, Zihao Wang, Taijie Chen
Complex Reasoning Novel Approach Reasoning Capability Reasoning Ability Reasoning Problem

October 6, 2024

Admissibility Over Winning: A New Approach to Reactive Synthesis in Robotics
Karan Muvvala, Morteza Lahijanian
Robotics Domain Novel Approach Rational Decision Reactive Synthesis

September 26, 2024

Enriched Functional Tree-Based Classifiers: A Novel Approach Leveraging Derivatives and Geometric Features
Fabrizio Maturo, Annamaria Porreca
Random Forest Novel Approach Geometric Feature Tree Based Functional Data Analysis Classification Tree Derivative Process

September 23, 2024

CAMAL: Optimizing LSM-trees via Active Learning
Weiping Yu, Siqiang Luo, Zihao Yu, Gao Cong
Active Learning Novel Approach

September 16, 2024

Householder Pseudo-Rotation: A Novel Approach to Activation Editing in LLMs with Direction-Magnitude Perspective
Van-Cuong Pham, Thien Huu Nguyen
Large Language Model Novel Approach Visual Perspective

Novel Approach

Papers

Saliency-Based diversity and fairness Metric and FaceKeepOriginalAugment: A Novel Approach for Enhancing Fairness and Diversity

Ali-AUG: Innovative Approaches to Labeled Data Augmentation using One-Step Diffusion Model

The Probabilistic Tsetlin Machine: A Novel Approach to Uncertainty Quantification

A New Approach to Solving SMAC Task: Generating Decision Tree Code from Large Language Models

SMILES-Prompting: A Novel Approach to LLM Jailbreak Attacks in Chemical Synthesis

End-to-End Transformer-based Automatic Speech Recognition for Northern Kurdish: A Pioneering Approach

A Novel Approach to Grasping Control of Soft Robotic Grippers based on Digital Twin

A new approach for fine-tuning sentence transformers for intent classification and out-of-scope detection tasks

MIRROR: A Novel Approach for the Automated Evaluation of Open-Ended Question Generation

Transfer Learning on Multi-Dimensional Data: A Novel Approach to Neural Network-Based Surrogate Modeling

Transformer Layer Injection: A Novel Approach for Efficient Upscaling of Large Language Models

Code-Mixer Ya Nahi: Novel Approaches to Measuring Multilingual LLMs' Code-Mixing Capabilities

A Novel Approach to Malicious Code Detection Using CNN-BiLSTM and Feature Fusion

Large Language Models for Medical OSCE Assessment: A Novel Approach to Transcript Analysis

F2A: An Innovative Approach for Prompt Injection by Utilizing Feign Security Detection Agents

Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models

Admissibility Over Winning: A New Approach to Reactive Synthesis in Robotics

Enriched Functional Tree-Based Classifiers: A Novel Approach Leveraging Derivatives and Geometric Features

CAMAL: Optimizing LSM-trees via Active Learning

Householder Pseudo-Rotation: A Novel Approach to Activation Editing in LLMs with Direction-Magnitude Perspective