How to Use Backdoor Criterion to Select Control Variables

Mathematical Reasoning in AI: New Solutions from Shanghai AI Laboratory Understanding the Challenges Mathematical reasoning is a complex area for artificial intelligence (AI). While large language models (LLMs) have improved, they often struggle with tasks that…

Large Vision-Language Models (LVLMs) bridge visual perception and language processing. Huawei researchers address the challenge of hallucinations in LVLMs, proposing innovative strategies and interventions. Refinements in data processing and model architecture enhance accuracy and reliability, reducing…

The text discusses the challenges and limitations of AI technology, highlighting various incidents where AI systems made significant errors or had unintended consequences, such as Google’s Gemini refusing to generate images of white people, Microsoft’s Bing…

Enhancing Business with Conversational AI Enhancing Business with Conversational AI Introduction to Function Calling in Conversational AI Function calling is a powerful feature that enables large language models (LLMs) to connect natural language inputs with real-world…

SEC Chairman Gary Gensler emphasizes the importance of regulating AI in order to prevent a financial crisis. He expresses concerns about the potential for overreliance on AI tools by financial institutions, which could lead to a…

Researchers have developed a method called SweetDreamer to address the issue of geometric inconsistency in converting 2D images to 3D objects for text-to-3D generation. This method aligns 2D geometric priors with well-defined 3D shapes to ensure…

Practical Solutions for AI in Graph Comprehension and Reasoning Overview Developing and evaluating Large Language Models (LLMs) to understand and reason about graph-structured data is crucial for various applications, including social network analysis, drug discovery, recommendation…

University of Geneva researchers have developed Graph Neural Networks (GNN) to predict healthcare-associated infections, outperforming traditional models in early detection of multidrug-resistant Enterobacteriaceae colonization with over 88% accuracy. The GNN model utilizes patient and healthcare worker…

Researchers from Meta have introduced Retrieval-Augmented Dual Instruction Tuning (RA-DIT), a lightweight fine-tuning methodology to equip large language models (LLMs) with efficient retrieval capabilities. RA-DIT operates through two stages, optimizing the LLM’s use of retrieved information…

The InfoBatch framework, developed by researchers at the National University of Singapore and Alibaba, introduces an innovative solution to the challenge of balancing training costs with model performance in machine learning. By dynamically pruning less informative…

ProtHyena, developed by researchers at Tokyo Institute of Technology, is a protein language model that addresses attention-based model limitations. Utilizing the Hyena operator, it efficiently processes long protein sequences and outperforms traditional models on various biological…

Introduction to Foundation Models Foundation models are advanced AI systems trained on large amounts of unlabeled data. They can perform complex tasks by responding to specific prompts. Researchers are now looking to expand these models beyond…

Despite some progress in the SAG-AFTRA strike negotiations, unresolved issues remain, including the use of AI in recreating performers’ likeness and revenue sharing with streaming platforms. The strike has continued for 109 days, with uncertainty surrounding…

DeepMind researchers unveiled “FunSearch,” using Large Language Models to generate new mathematical and computer science solutions. FunSearch combines a pre-trained LLM to create code-based solutions, verified by an automated evaluator, refining them iteratively. It has successfully…

Practical Solutions and Value of Generalizable Reward Model (GRM) Improving Large Language Models (LLMs) Performance Pretrained large models can align with human values and avoid harmful behaviors using alignment methods such as supervised fine-tuning (SFT) and…