LLMs have demonstrated impressive capabilities in answering medical questions accurately, even outperforming average human scores in some medical examinations. However, […]
Category: Language Model
XAI-DROP: Enhancing Graph Neural Networks GNNs Training with Explainability-Driven Dropping Strategies
Graph Neural Networks GNNs have become a powerful tool for analyzing graph-structured data, with applications ranging from social networks and […]
This AI Paper from Tencent AI Lab and Shanghai Jiao Tong University Explores Overthinking in o1-Like Models for Smarter Computation
Large language models (LLMs) have become pivotal tools in tackling complex reasoning and problem-solving tasks. Among them, o1-like models, inspired […]
FedVCK: A Data-Centric Approach to Address Non-IID Challenges in Federated Medical Image Analysis
Federated learning has emerged as an approach for collaborative training among medical institutions while preserving data privacy. However, the non-IID […]
Hugging Face Just Released SmolAgents: A Smol Library that Enables to Run Powerful AI Agents in a Few Lines of Code
Creating intelligent agents has traditionally been a complex task, often requiring significant technical expertise and time. Developers encounter challenges like […]
Meet the Pirates of the RAG: Adaptively Attacking LLMs to Leak Knowledge Bases
Retrieval-augmented generation (RAG) enhances the output of Large Language Models (LLMs) using external knowledge bases. These systems work by retrieving […]
Meet HuatuoGPT-o1: A Medical LLM Designed for Advanced Medical Reasoning
Medical artificial intelligence (AI) is full of promise but comes with its own set of challenges. Unlike straightforward mathematical problems, […]
Researchers from MIT, Sakana AI, OpenAI and Swiss AI Lab IDSIA Propose a New Algorithm Called Automated Search for Artificial Life (ASAL) to Automate the Discovery of Artificial Life Using Vision-Language Foundation Models
Artificial Life (ALife) research explores the emergence of lifelike behaviors through computational simulations, providing a unique framework to study “life […]
AutoSculpt: A Pattern-based Automated Pruning Framework Designed to Enhance Efficiency and Accuracy by Leveraging Graph Learning and Deep Reinforcement Learning
Deploying Deep Neural Networks (DNNs) on edge devices, such as smartphones and autonomous vehicles, remains a significant challenge due to […]
B-STAR: A Self-Taught AI Reasoning Framework for LLMs
A direct correlation exists between an LLM’s training corpus quality and its capabilities. Consequently, researchers have invested a great deal […]