The rapid growth of digital platforms has brought image safety into sharp focus. Harmful imagery—ranging from explicit content to depictions […]
Category: Machine Learning
Researchers from Fudan University and Shanghai AI Lab Introduces DOLPHIN: A Closed-Loop Framework for Automating Scientific Research with Iterative Feedback
Artificial Intelligence (AI) is revolutionizing how discoveries are made. AI is creating a new scientific paradigm with the acceleration of […]
R3GAN: A Simplified and Stable Baseline for Generative Adversarial Networks GANs
GANs are often criticized for being difficult to train, with their architectures relying heavily on empirical tricks. Despite their ability […]
What are Small Language Models (SLMs)?
Large language models (LLMs) like GPT-4, PaLM, Bard, and Copilot have made a huge impact in natural language processing (NLP). […]
RAG-Check: A Novel AI Framework for Hallucination Detection in Multi-Modal Retrieval-Augmented Generation Systems
Large Language Models (LLMs) have revolutionized generative AI, showing remarkable capabilities in producing human-like responses. However, these models face a […]
SepLLM: A Practical AI Approach to Efficient Sparse Attention in Large Language Models
Large Language Models (LLMs) have shown remarkable capabilities across diverse natural language processing tasks, from generating text to contextual reasoning. […]
ToolHop: A Novel Dataset Designed to Evaluate LLMs in Multi-Hop Tool Use Scenarios
Multi-hop queries have always given LLM agents a hard time with their solutions, necessitating multiple reasoning steps and information from […]
This AI Paper Explores Embodiment, Grounding, Causality, and Memory: Foundational Principles for Advancing AGI Systems
Artificial General Intelligence (AGI) seeks to create systems that can perform various tasks, reasoning, and learning with human-like adaptability. Unlike […]
Cache-Augmented Generation: Leveraging Extended Context Windows in Large Language Models for Retrieval-Free Response Generation
Large language models (LLMs) have recently been enhanced through retrieval-augmented generation (RAG), which dynamically integrates external knowledge sources to improve […]
161 years ago, a New Zealand sheep farmer predicted AI doom
The text anticipated several modern AI safety concerns, including the possibility of machine consciousness, self-replication, and humans losing control of […]