Large language models (LLMs) have gained significant traction in reasoning tasks, including mathematics, logic, planning, and coding. However, a critical challenge emerges when applying these models to real-world scenarios. While current implementations typically operate under the assumption that all necessary information is provided upfront in well-specified tasks, reality often presents incomplete or ambiguous situations. Users […] The post Google DeepMind Research Introduces QuestBench: Evaluating LLMs’ Ability to Identify Missing Information in Reasoning Tasks appeared first on MarkTechPost. read more

Designing and evaluating web interfaces is one of the most critical tasks in today’s digital-first world. Every change in layout, element positioning, or navigation logic can influence how users interact with websites. This becomes even more crucial for platforms that rely on extensive user engagement, such as e-commerce or content streaming services. One of the […] The post AgentA/B: A Scalable AI System Using LLM Agents that Simulate Real User Behavior to Transform Traditional A/B Testing on Live Web Platforms appeared first on MarkTechPost. read more

Autoregressive (AR) models have made significant advances in language generation and are increasingly explored for image synthesis. However, scaling AR models to high-resolution images remains a persistent challenge. Unlike text, where relatively few tokens are required, high-resolution images necessitate thousands of tokens, leading to quadratic growth in computational cost. As a result, most AR-based multimodal […] The post Meta AI Introduces Token-Shuffle: A Simple AI Approach to Reducing Image Tokens in Transformers appeared first on MarkTechPost. read more

At technology conferences worldwide and on social media, generative AI applications demonstrate impressive capabilities: composing marketing emails, creating data visualizations, or writing functioning code. Yet behind these polished demonstrations lies a stark reality. What works in controlled environments often fails when confronted with the demands of production systems. Industry surveys reveal the scale of this […] The post From GenAI Demos to Production: Why Structured Workflows Are Essential appeared first on MarkTechPost. read more

Recent advancements in multimodal AI have highlighted a persistent challenge: achieving strong specialized reasoning capabilities while preserving generalization across diverse tasks. “Slow-thinking” models such as OpenAI-o1 and Gemini-Thinking have made strides in deliberate analytical reasoning but often exhibit compromised performance on general visual understanding tasks, with increased tendencies toward visual hallucinations. As the field progresses […] The post Skywork AI Advances Multimodal Reasoning: Introducing Skywork R1V2 with Hybrid Reinforcement Learning appeared first on MarkTechPost. read more

Transformers have revolutionized sequence modeling by introducing an architecture that handles long-range dependencies efficiently without relying on recurrence. Their ability to process input tokens simultaneously, while utilizing self-attention mechanisms, enables them to achieve impressive performance in natural language tasks. However, despite their dominance, some of the essential features found in recurrent neural networks, particularly the […] The post Mila & Universite de Montreal Researchers Introduce the Forgetting Transformer (FoX) to Boost Long-Context Language Modeling without Sacrificing Efficiency appeared first on MarkTechPost. read more

In this tutorial, we explore five levels of Agentic Architectures, from the simplest language model calls to a fully autonomous code-generating system. This tutorial is designed to run seamlessly on Google Colab. Starting with a basic “simple processor” that simply echoes the model’s output, you will progressively build routing logic, integrate external tools, orchestrate multi-step […] The post A Comprehensive Tutorial on the Five Levels of Agentic AI Architectures: From Basic Prompt Responses to Fully Autonomous Code Generation and Execution appeared first on MarkTechPost. read more

Integrating long-context capabilities with visual understanding significantly enhances the potential of VLMs, particularly in domains such as robotics, autonomous driving, and healthcare. Expanding the context size enables VLMs to process extended video and text sequences, thereby enhancing temporal resolution and performance in complex tasks, such as video comprehension. However, one major limitation is the quadratic […] The post Microsoft Research Introduces MMInference to Accelerate Pre-filling for Long-Context Vision-Language Models appeared first on MarkTechPost. read more

Mathematical reasoning has long presented a formidable challenge for AI, demanding not only an understanding of abstract concepts but also the ability to perform multi-step logical deductions with precision. Traditional language models, while adept at generating fluent text, often struggle when tasked with solving complex mathematical problems that require both deep domain knowledge and structured […] The post NVIDIA AI Releases OpenMath-Nemotron-32B and 14B-Kaggle: Advanced AI Models for Mathematical Reasoning that Secured First Place in the AIMO-2 Competition and Set New Benchmark Records appeared first on MarkTechPost. read more

In recent years, contrastive language-image models such as CLIP have established themselves as a default choice for learning vision representations, particularly in multimodal applications like Visual Question Answering (VQA) and document understanding. These models leverage large-scale image-text pairs to incorporate semantic grounding via language supervision. However, this reliance on text introduces both conceptual and practical […] The post Meta AI Releases Web-SSL: A Scalable and Language-Free Approach to Visual Representation Learning appeared first on MarkTechPost. read more