5 papers
M3PO: Multimodal-Model-Guided Preference Optimization for Visual Instruction Following
Ruirui Gao, Emily Johnson, Bowen Tan +1
Large Vision-Language Models (LVLMs) hold immense potential for complex multimodal instruction following, yet their development is often hindered by the high cost and inconsistency…
Dynamic Epsilon Scheduling: A Multi-Factor Adaptive Perturbation Budget for Adversarial Training
Alan Mitkiy, James Smith, Myungseo wong +3
Adversarial training is among the most effective strategies for defending deep neural networks against adversarial examples. A key limitation of existing adversarial training appro…
Improving the Accuracy and Efficiency of Legal Document Tagging with Large Language Models and Instruction Prompts
Emily Johnson, Xavier Holt, Noah Wilson
Legal multi-label classification is a critical task for organizing and accessing the vast amount of legal documentation. Despite its importance, it faces challenges such as the com…
Hierarchical Vision-Language Alignment for Text-to-Image Generation via Diffusion Models
Emily Johnson, Noah Wilson
Text-to-image generation has witnessed significant advancements with the integration of Large Vision-Language Models (LVLMs), yet challenges remain in aligning complex textual desc…
Enhancing Agricultural Machinery Management through Advanced LLM Integration
Emily Johnson, Noah Wilson
The integration of artificial intelligence into agricultural practices, specifically through Consultation on Intelligent Agricultural Machinery Management (CIAMM), has the potentia…