​[[{“value”:” Parameter-efficient fine-tuning (PEFT) methods have become essential in machine learning. They allow large models to adapt to new tasks without extensive computational resources. By fine-tuning only a small subset of parameters while keeping most of the model frozen, PEFT methods aim to make the… Read More »LoRA-Pro: A Groundbreaking Machine Learning Approach to Bridging the Performance Gap Between Low-Rank Adaptation and Full Fine-Tuning Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Recent advancements in LLM capabilities have increased their usability by enabling them to do a broader range of general activities autonomously. The existing methods for expressing and running LM programs could be more efficient, although they are widely used. There are two main obstacles… Read More »SGLang: A Structured Generation Language for Efficient Execution of Complex Language Model Programs Dhanshree Shripad Shenwai Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Causal effect estimation is crucial for understanding the impact of interventions in various domains, such as healthcare, social sciences, and economics. This area of research focuses on determining how changes in one variable cause changes in another, which is essential for informed decision-making. Traditional… Read More »What if the Next Medical Breakthrough is Hidden in Plain Text? Meet NATURAL: A Pipeline for Causal Estimation from Unstructured Text Data in Hours, Not Years Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Competition significantly shapes human societies, influencing economics, social structures, and technology. Traditional research on competition, relying on empirical studies, is limited by data accessibility and lacks micro-level insights. Agent-based modeling (ABM) emerged to overcome these limitations, progressing from rule-based to machine learning-based agents. However,… Read More »CompeteAI: An Artificial Intelligence AI Framework that Understands the Competition Dynamics of Large Language Model-based Agents Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Evaluating model performance is essential in the significantly advancing fields of Artificial Intelligence and Machine Learning, especially with the introduction of Large Language Models (LLMs). This review procedure helps understand these models’ capabilities and create dependable systems based on them. However, what is referred… Read More »The Impact of Questionable Research Practices on the Evaluation of Machine Learning (ML) Models Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Autonomous web navigation focuses on developing AI agents capable of performing complex online tasks. These tasks range from data retrieval and form submissions to more intricate activities like finding the cheapest flights or booking accommodations. By leveraging large language models (LLMs) and other AI… Read More »Emergence AI Proposes Agent-E: A Web Agent Achieving 73.2% Success Rate with a 20% Improvement in Autonomous Web Navigation Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Generative Artificial Intelligence (GenAI), particularly large language models (LLMs) like ChatGPT, has revolutionized the field of natural language processing (NLP). These models can produce coherent and contextually relevant text, enhancing applications in customer service, virtual assistance, and content creation. Their ability to generate human-like… Read More »RogueGPT: Unveiling the Ethical Risks of Customizing ChatGPT Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Aligning models with human preferences poses significant challenges in AI research, particularly in high-dimensional and sequential decision-making tasks. Traditional Reinforcement Learning from Human Feedback (RLHF) methods require learning a reward function from human feedback and then optimizing this reward using RL algorithms. This two-phase… Read More »Researchers at Stanford Introduce Contrastive Preference Learning (CPL): A Novel Machine Learning Framework for RLHF Using the Regret Preference Model Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The landscape of artificial intelligence has seen significant advancements with the introduction of state-of-the-art language models. Among the leading models are Llama 3.1, GPT-4o, and Claude 3.5. Each model brings unique capabilities and improvements, reflecting the ongoing evolution of AI technology. Let’s analyze these… Read More »Llama 3.1 vs GPT-4o vs Claude 3.5: A Comprehensive Comparison of Leading AI Models Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) can improve their final answers by dedicating additional computer power to intermediate thought generation during inference. System 2 strategies are used in this procedure to mimic intentional and conscious reasoning. Many more System 2 strategies, such as Rephrase and Respond,… Read More »Optimizing Artificial Intelligence Performance by Distilling System 2 Reasoning into Efficient System 1 Responses Tanya Malhotra Artificial Intelligence Category – MarkTechPost