Like humans, large language models (LLMs) often have differing skills and strengths derived from differences in their architectures and training regimens. However, they struggle to combine specialized expertise across different domains, limiting their problem-solving capabilities compared to humans. Specialized models like MetaMath, WizardMath, and QwenMath excel at mathematical reasoning but often underperform on tasks requiring […] The post SYMBOLIC-MOE: Mixture-of-Experts MoE Framework for Adaptive Instance-Level Mixing of Pre-Trained LLM Experts appeared first on MarkTechPost. read more

In this tutorial, we demonstrate how to build an AI-powered PDF interaction system in Google Colab using Gemini Flash 1.5, PyMuPDF, and the Google Generative AI API. By leveraging these tools, we can seamlessly upload a PDF, extract its text, and interactively ask questions, receiving intelligent responses from Google’s latest Gemini Flash 1.5 model. First […] The post A Code Implementation to Build an AI-Powered PDF Interaction System in Google Colab Using Gemini Flash 1.5, PyMuPDF, and Google Generative AI API appeared first on MarkTechPost. read more

Large Language Models (LLMs) have become crucial in customer support, automated content creation, and data retrieval. However, their effectiveness is often hindered by their inability to follow detailed instructions during multiple interactions consistently. This issue is particularly critical in high-stakes environments, such as financial services and customer support systems, where strict adherence to guidelines is […] The post Meet Attentive Reasoning Queries (ARQs): A Structured Approach to Enhancing Large Language Model Instruction Adherence, Decision-Making Accuracy, and Hallucination Prevention in AI-Driven Conversational Systems appeared first on MarkTechPost. read more

Reasoning capabilities have become essential for LLMs, but analyzing these complex processes poses a significant challenge. While LLMs can generate detailed text reasoning output, the lack of process visualization creates barriers to understanding, evaluating, and improving. This limitation manifests in three critical ways: increased cognitive load for users attempting to parse complex reasoning paths; difficulty […] The post Researchers from the University of Cambridge and Monash University Introduce ReasonGraph: A Web-based Platform to Visualize and Analyze LLM Reasoning Processes appeared first on MarkTechPost. read more

Multi-modal Large Language Models (MLLMs) have demonstrated remarkable capabilities across various domains, propelling their evolution into multi-modal agents for human assistance. GUI automation agents for PCs face particularly daunting challenges compared to smartphone counterparts. PC environments present significantly more complex interactive elements with dense, diverse icons and widgets often lacking textual labels, leading to perception […] The post Meet PC-Agent: A Hierarchical Multi-Agent Collaboration Framework for Complex Task Automation on PC appeared first on MarkTechPost. read more

AI-generated videos from text descriptions or images hold immense potential for content creation, media production, and entertainment. Recent advancements in deep learning, particularly in transformer-based architectures and diffusion models, have propelled this progress. However, training these models remains resource-intensive, requiring large datasets, extensive computing power, and significant financial investment. These challenges limit access to cutting-edge […] The post HPC-AI Tech Releases Open-Sora 2.0: An Open-Source SOTA-Level Video Generation Model Trained for Just $200K appeared first on MarkTechPost. read more

​In recent years, the integration of image generation technologies into various platforms has opened new avenues for enhancing user experiences. However, as these multimodal AI systems—capable of processing and generating multiple data forms like text and images—expand, challenges such as “caption hallucination” have emerged. This phenomenon occurs when AI-generated descriptions of images contain inaccuracies or […] The post Patronus AI Introduces the Industry’s First Multimodal LLM-as-a-Judge (MLLM-as-a-Judge): Designed to Evaluate and Optimize AI Systems that Convert Image Inputs into Text Outputs appeared first on MarkTechPost. read more

The rapid evolution of artificial intelligence (AI) has ushered in a new era of large language models (LLMs) capable of understanding and generating human-like text. However, the proprietary nature of many of these models poses challenges for accessibility, collaboration, and transparency within the research community. Additionally, the substantial computational resources required to train such models […] The post Allen Institute for AI (AI2) Releases OLMo 32B: A Fully Open Model to Beat GPT 3.5 and GPT-4o mini on a Suite of Multi-Skill Benchmarks appeared first on MarkTechPost. read more

Traditional language models rely on autoregressive approaches, which generate text sequentially, ensuring high-quality outputs at the expense of slow inference speeds. In contrast, diffusion models, initially developed for image and video generation, have gained attention in text generation due to their potential for parallelized generation and improved controllability. However, existing diffusion models struggle with fixed-length […] The post This AI Paper Introduces BD3-LMs: A Hybrid Approach Combining Autoregressive and Diffusion Models for Scalable and Efficient Text Generation appeared first on MarkTechPost. read more

Enhancing the reasoning abilities of LLMs by optimizing test-time compute is a critical research challenge. Current approaches primarily rely on fine-tuning models with search traces or RL using binary outcome rewards. However, these methods may not fully exploit test-time compute efficiently. Recent research suggests that increasing test-time computing can improve reasoning by generating longer solution […] The post Optimizing Test-Time Compute for LLMs: A Meta-Reinforcement Learning Approach with Cumulative Regret Minimization appeared first on MarkTechPost. read more