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
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
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 ...
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
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, ...
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 ...
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 ...
marktechpost7d
Microsoft AI Releases AutoGen v0.4: A Comprehensive Update to Enable High-Performance Agentic AI through Asynchronous Messaging and Modular Design
Agentic AI enables autonomous and collaborative problem-solving that mimics human cognition. By facilitating multi-agent cooperation with real-time communication, it holds promise across diverse ...
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 ...
marktechpost7d
Microsoft AI Research Introduces MVoT: A Multimodal Framework for Integrating Visual and Verbal Reasoning in Complex Tasks
The study of artificial intelligence has witnessed transformative developments in reasoning and understanding complex tasks. The most innovative developments are large language models (LLMs) and ...
marktechpost3d
GameFactory: Leveraging Pre-trained Video Models for Creating New Game
Video diffusion models have emerged as powerful tools for video generation and physics simulation, showing promise in developing game engines. These generative game engines function as video ...