​[[{“value”:” Geometry problem-solving relies heavily on advanced reasoning skills to interpret visual inputs, process questions, and apply mathematical formulas accurately. Although vision-language models (VLMs) have shown progress in multimodal tasks, they still face significant limitations with geometry, particularly in executing unfamiliar mathematical operations, like calculating… Read More »GeoCoder: Enhancing Geometric Reasoning in Vision-Language Models through Modular Code-Finetuning and Retrieval-Augmented Memory Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The efficient training of vision models is still a major challenge in AI because Transformer-based models suffer from computational bottlenecks due to the quadratic complexity of self-attention mechanisms. Also, the ViTs, although extremely promising results on hard vision tasks, require extensive computational and memory… Read More »Researchers at the Ohio State University Introduce Famba-V: A Cross-Layer Token Fusion Technique that Enhances the Training Efficiency of Vision Mamba Models Aswin Ak Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Datasets and pre-trained models come with intrinsic biases. Most methods rely on spotting them by analyzing misclassified samples in a semi-automated human computer validation. Deep neural networks, typically fine-tuned foundational models, are widely used in sectors like healthcare, finance, and criminal justice, where biased… Read More »ConceptDrift: An AI Method to Identify Biases Using a Weight-Space Approach Moving Beyond Traditional Data-Restricted Protocols Nazmi Syed Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Text embedding, a central focus within natural language processing (NLP), transforms text into numerical vectors capturing the essential meaning of words or phrases. These embeddings enable machines to process language tasks like classification, clustering, retrieval, and summarization. By structuring data in vector form, embeddings… Read More »Microsoft Asia Research Introduces SPEED: An AI Framework that Aligns Open-Source Small Models (8B) to Efficiently Generate Large-Scale Synthetic Embedding Data Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Meta has recently released NotebookLlama, an open version of Google’s NotebookLM that empowers researchers and developers with accessible, scalable solutions for interactive data analysis and documentation. NotebookLlama integrates large language models directly into an open-source notebook interface, similar to Jupyter or Google Colab, allowing… Read More »Meta AI Silently Releases NotebookLlama: An Open Version of Google’s NotebookLM Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rise of the information era has brought an overwhelming amount of data in varied formats. Documents, presentations, and images are generated at an astonishing rate across multiple languages and domains. However, retrieving useful information from these diverse sources presents a significant challenge. Conventional… Read More »Meet mcdse-2b-v1: A New Performant, Scalable and Efficient Multilingual Document Retrieval Model Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have demonstrated impressive capabilities in handling knowledge-intensive tasks through their parametric knowledge stored within model parameters. However, the stored knowledge can become inaccurate or outdated, leading to the adoption of retrieval and tool-augmented methods that provide external contextual knowledge. A… Read More »SPARE: Training-Free Representation Engineering for Managing Knowledge Conflicts in Large Language Models Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) have transformed fields ranging from customer service to medical assistance by aligning machine output with human values. Reward models (RMs) play an important role in this alignment, essentially serving as a feedback loop where models are guided to provide human-preferred… Read More »M-RewardBench: A Multilingual Approach to Reward Model Evaluation, Analyzing Accuracy Across High and Low-Resource Languages with Practical Results Asif Razzaq Artificial Intelligence Category – MarkTechPost