marktechpost3d
Swarm: A Comprehensive Guide to Lightweight Multi-Agent Orchestration for Scalable and Dynamic Workflows with Code Implementation
Handoffs enable one Agent to pass control to another seamlessly. This allows specialized Agents to handle tasks better suited to their capabilities. # python agent_b ...
marktechpost3d
SHREC: A Physics-Based Machine Learning Approach to Time Series Analysis
Reconstructing unmeasured causal drivers of complex time series from observed response data represents a fundamental challenge across diverse scientific domains. Latent variables, including genetic ...
marktechpost3d
OmniThink: A Cognitive Framework for Enhanced Long-Form Article Generation Through Iterative Reflection and Expansion
LLMs have made significant strides in automated writing, particularly in tasks like open-domain long-form generation and topic-specific reports. Many approaches rely on Retrieval-Augmented Generation ...
marktechpost4d
Stanford Researchers Introduce BIOMEDICA: A Scalable AI Framework for Advancing Biomedical Vision-Language Models with Large-Scale Multimodal Datasets
The development of VLMs in the biomedical domain faces challenges due to the lack of large-scale, annotated, and publicly accessible multimodal datasets across diverse fields. While datasets have been ...
marktechpost3d
Researchers from China Develop Advanced Compression and Learning Techniques to process Long-Context Videos at 100 Times Less Compute
One of the most significant and advanced capabilities of a multimodal large language model is long-context video modeling, which allows models to handle movies, documentaries, and live streams ...
marktechpost3d
Google AI Proposes a Fundamental Framework for Inference-Time Scaling in Diffusion Models
Generative models have revolutionized fields like language, vision, and biology through their ability to learn and sample from complex data distributions. While these models benefit from scaling up ...
marktechpost3d
Researchers from MIT, Google DeepMind, and Oxford Unveil Why Vision-Language Models Do Not Understand Negation and Proposes a Groundbreaking Solution
Vision-language models (VLMs) play a crucial role in multimodal tasks like image retrieval, captioning, and medical diagnostics by aligning visual and linguistic data. However, understanding negation ...
marktechpost3d
This AI Paper Explores Reinforced Learning and Process Reward Models: Advancing LLM Reasoning with Scalable Data and Test-Time Scaling
Scaling the size of large language models (LLMs) and their training data have now opened up emergent capabilities that allow these models to perform highly structured reasoning, logical deductions, ...
marktechpost5d
CrewAI: A Guide to Agentic AI Collaboration and Workflow Optimization with Code Implementation
CrewAI is an innovative platform that transforms how AI agents collaborate to solve complex problems. As an orchestration framework, it empowers users to assemble and manage teams of specialized AI ...
marktechpost4d
Meet OmAgent: A New Python Library for Building Multimodal Language Agents
Understanding long videos, such as 24-hour CCTV footage or full-length films, is a major challenge in video processing. Large Language Models (LLMs) have shown great potential in handling multimodal ...
marktechpost5d
What is?
Enabling artificial intelligence to navigate and retrieve contextually rich, multi-faceted information from the internet is important in enhancing AI functionalities. Traditional search engines are ...
marktechpost6d
Chat with Your Documents Using Retrieval-Augmented Generation (RAG)
Imagine having a personal chatbot that can answer questions directly from your documents—be it PDFs, research papers, or books. With Retrieval-Augmented Generation (RAG), this is not only possible but ...