marktechpost5d
Adaptive Attacks on LLMs: Lessons from the Frontlines of AI Robustness Testing
The field of Artificial Intelligence (AI) is advancing at a rapid rate; specifically, the Large Language Models have become indispensable in modern AI applications. These LLMs have inbuilt safety ...
marktechpost6d
UC Berkeley Researchers Explore the Role of Task Vectors in Vision-Language Models
Vision-and-language models (VLMs) are important tools that use text to handle different computer vision tasks. Tasks like recognizing images, reading text from images (OCR), and detecting objects can ...
marktechpost6d
Retrieval-Augmented Reasoning Enhancement (RARE): A Novel Approach to Factual Reasoning in Medical and Commonsense Domains
Question answering (QA) emerged as a critical task in natural language processing, designed to generate precise answers to complex queries across diverse domains. Within this, medical QA poses unique ...
marktechpost6d
Auto-RAG: An Autonomous Iterative Retrieval Model Centered on the LLM’s Powerful Decision-Making Capabilities
Retrieval Augmented Generation is an efficient solution for knowledge-intensive tasks that improves the quality of outputs and makes it more deterministic with minimal hallucinations. However, RAG ...
marktechpost6d
Researchers at Stanford University Introduce TrAct: A Novel Optimization Technique for Efficient and Accurate First-Layer Training in Vision Models
Vision models are pivotal in enabling machines to interpret and analyze visual data. They are integral to tasks such as image classification, object detection, and segmentation, where raw pixel values ...
marktechpost6d
This AI Paper from UCSD and CMU Introduces EDU-RELAT: A Benchmark for Evaluating Deep Unlearning in Large Language Models
Large language models (LLMs) excel in generating contextually relevant text; however, ensuring compliance with data privacy regulations, such as GDPR, requires a robust ability to unlearn specific ...
marktechpost6d
Composition of Experts: A Modular and Scalable Framework for Efficient Large Language Model Utilization
LLMs have revolutionized artificial intelligence with their remarkable scalability and adaptability. Models like GPT-4 and Claude, built with trillions of parameters, demonstrate exceptional ...
marktechpost5d
Meet DataLab: A Unified Business Intelligence Platform Utilizing LLM-Based Agents and Computational Notebooks
Business intelligence (BI) faces significant challenges in efficiently transforming large data volumes into actionable insights. Current workflows involve multiple complex stages, including data ...
marktechpost6d
Microsoft Introduces Florence-VL: A Multimodal Model Redefining Vision-Language Alignment with Generative Vision Encoding and Depth-Breadth Fusion
Integrating vision and language processing in AI has become a cornerstone for developing systems capable of simultaneously understanding visual and textual data, i.e., multimodal data. This ...
marktechpost6d
Meet GRAPE: A Plug-and-Play Algorithm to Generalize Robot Policies via Preference Alignment
The field of robotic manipulation has witnessed a remarkable transformation with the emergence of vision-language-action (VLA) models. These advanced computational frameworks have demonstrated ...
marktechpost6d
Exploring Adaptivity in AI: A Deep Dive into ALAMA’s Mechanisms
Language Agents (LAs) have recently become the focal point of research and development because of the significant advancement in large language models (LLMs). LLMs have demonstrated significant ...
marktechpost1d
Natural Language Processing
Since the Industrial Revolution, burning fossil fuels and changes in land use, especially deforestation, have driven the rise in atmospheric carbon dioxide (CO2). While terrestrial vegetation and ...