​[[{“value”:” Visual and action data are interconnected in robotic tasks, forming a perception-action loop. Robots rely on control parameters for movement, while VFMs excel in processing visual data. However, a modality gap exists between visual and action data arising from the fundamental differences in their… Read More »Differentiable Rendering of Robots (Dr. Robot): A Robot Self-Model Differentiable from Its Visual Appearance to Its Control Parameters Pragati Jhunjhunwala Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large language models (LLMs) like GPT-4, Gemini, and Llama 3 have revolutionized natural language processing through extensive pre-training and supervised fine-tuning (SFT). However, these models come with high computational costs for training and inference. Structured pruning has emerged as a promising method to improve… Read More »Self-Data Distilled Fine-Tuning: A Solution for Pruning and Supervised Fine-tuning Challenges in LLMs Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The problem of over-optimization of likelihood in Direct Alignment Algorithms (DAAs), such as Direct Preference Optimisation (DPO) and Identity Preference Optimisation (IPO), arises when these methods fail to improve model performance despite increasing the likelihood of preferred outcomes. These algorithms, which are alternatives to… Read More »Rethinking Direct Alignment: Balancing Likelihood and Diversity for Better Model Performance Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language models (LLMs) have long been trained to process vast amounts of data to generate responses that align with patterns seen during training. However, researchers are exploring a more profound concept: introspection, the ability of LLMs to reflect on their behavior and gain… Read More »Harnessing Introspection in AI: How Large Language Models Are Learning to Understand and Predict Their Behavior for Greater Accuracy Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Point tracking is paramount in video; from 3d reconstruction to editing tasks, a precise approximation of points is necessary to achieve quality results. Over time, trackers have incorporated transformer and neural network-based designs to track individual and multiple points simultaneously. However, these neural networks… Read More »Meta AI Releases Cotracker3: A Semi-Supervised Tracker that Produces Better Results with Unlabelled Data and Simple Architecture Adeeba Alam Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” The rise of Transformer-based models has significantly advanced the field of natural language processing. However, the training of these models is often computationally intensive, requiring substantial resources and time. This research addresses the issue of improving the training efficiency of Transformer models without compromising… Read More »Nvidia AI Introduces the Normalized Transformer (nGPT): A Hypersphere-based Transformer Achieving 4-20x Faster Training and Improved Stability for LLMs Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Bayesian Optimization, widely used in experimental design and black-box optimization, traditionally relies on regression models for predicting the performance of solutions within fixed search spaces. However, many regression methods are task-specific due to modeling assumptions and input constraints. This issue is especially prevalent in… Read More »Embed-then-Regress: A Versatile Machine Learning Approach for Bayesian Optimization Using String-Based In-Context Regression Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” AI has significantly impacted healthcare, particularly in disease diagnosis and treatment planning. One area gaining attention is the development of Medical Large Vision-Language Models (Med-LVLMs), which combine visual and textual data for advanced diagnostic tools. These models have shown great potential for improving the… Read More »MMed-RAG: A Versatile Multimodal Retrieval-Augmented Generation System Transforming Factual Accuracy in Medical Vision-Language Models Across Multiple Domains Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Dynamical systems are mathematical models that explain how a system evolves due to physical interactions or forces. These systems are fundamental to understanding various phenomena across scientific fields like physics, biology, and engineering. For example, they model fluid dynamics, celestial mechanics, and robotic movements.… Read More »TREAT: A Deep Learning Framework that Achieves High-Precision Modeling for a Wide Range of Dynamical Systems by Injecting Time-Reversal Symmetry as an Inductive Bias Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Long-context Large language models (LLMs) are designed to handle long input sequences, enabling them to process and understand large amounts of information. As the interference computation power is increased the large language models (LLMs) can perform diverse tasks. Particularly for knowledge-intensive tasks that rely… Read More »This AI Paper from Google DeepMind Explores Inference Scaling in Long-Context RAG Divyesh Vitthal Jawkhede Artificial Intelligence Category – MarkTechPost