​[[{“value”:” Home Table of Contents Understanding Tasks in Diffusers: Part 1 Configuring Your Development Environment Setup and Imports Unconditional Image Generation Text-to-Image Generation Specifying Parameters Image-to-Image Generation Stable Diffusion XL (SDXL) Model A Closer Look at Pipeline Parameters Summary Citation Information Understanding Tasks in Diffusers:… Read More »Understanding Tasks in Diffusers: Part 1 Aritra Roy Gosthipaty and Ritwik Raha PyImageSearch

​[[{“value”:” Researchers from Google DeepMind have collaborated with Mila, and McGill University defined appropriate reward functions to address the challenge of efficiently training reinforcement learning (RL) agents. The reinforcement learning method uses a rewarding system for achieving desired behaviors and punishing undesired ones. Hence, designing… Read More »Meet VLM-CaR (Code as Reward): A New Machine Learning Framework Empowering Reinforcement Learning with Vision-Language Models Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” A crucial challenge at the core of the advancements in large language models (LLMs) is ensuring that their outputs align with human ethical standards and intentions. Despite their sophistication, these models can generate content that can be technically accurate but may not align with… Read More »Researchers from AWS AI Labs and USC Propose DeAL: A Machine Learning Framework that Allows the User to Customize Reward Functions and Enables Decoding-Time Alignment of LLMs Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Integrating external tools into language models (LMs) marks a pivotal advancement towards creating versatile digital assistants. This integration enhances the models’ functionality and propels them closer to the vision of general-purpose AI. This ambition encounters a significant challenge: the rapid evolution of tools and… Read More »Researchers from Meta AI and UCSD Present TOOLVERIFIER: A Generation and Self-Verification Method for Enhancing the Performance of Tool Calls for LLMs Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The well-known Artificial Intelligence (AI)-based chatbot, i.e., ChatGPT, which has been built on top of GPT’s transformer architecture, uses the technique of Reinforcement Learning from Human Feedback (RLHF). RLHF is an increasingly important method for utilizing the potential of pre-trained Large Language Models (LLMs)… Read More »Researchers from NVIDIA and the University of Maryland Propose ODIN: A Reward Disentangling Technique that Mitigates Hacking in Reinforcement Learning from Human Feedback (RLHF) Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The alignment of Large Language Models (LLMs) with human preferences has become a crucial area of research. As these models gain complexity and capability, ensuring their actions and outputs align with human values and intentions is paramount. The conventional route to this alignment has… Read More »Can Machine Learning Models Be Fine-Tuned More Efficiently? This AI Paper from Cohere for AI Reveals How REINFORCE Beats PPO in Reinforcement Learning from Human Feedback Adnan Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The challenges in developing instruction-following agents in grounded environments include sample efficiency and generalizability. These agents must learn effectively from a few demonstrations while performing successfully in new environments with novel instructions post-training. Techniques like reinforcement learning and imitation learning are commonly used but… Read More »Can Machine Learning Teach Robots to Understand Us Better? This Microsoft Research Introduces Language Feedback Models for Advanced Imitation Learning Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the fast-evolving world of technology, language models play a crucial role in various applications, from answering questions to generating text. However, one challenge these models face is their size, which can limit their capabilities and applications. Developers and researchers always seek efficient yet… Read More »Meet MiniCPM: An End-Side LLM with only 2.4B Parameters Excluding Embeddings Niharika Singh Artificial Intelligence Category – MarkTechPost