​[[{“value”:” Parameter-efficient fine-tuning (PEFT) methods, like low-rank adaptation (LoRA), allow large pre-trained foundation models to be adapted to downstream tasks using a small percentage (0.1%-10%) of the original trainable weights. A less explored area of PEFT is extending the pre-training phase without supervised labels—specifically, adapting… Read More »Researchers at Stanford University Propose ExPLoRA: A Highly Effective AI Technique to Improve Transfer Learning of Pre-Trained Vision Transformers (ViTs) Under Domain Shifts Sana Hassan Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Machine Learning (ML) models have shown promising results in various coding tasks, but there remains a gap in effectively benchmarking AI agents’ capabilities in ML engineering. Existing coding benchmarks primarily evaluate isolated coding skills without holistically measuring the ability to perform complex ML tasks,… Read More »OpenAI Researchers Introduce MLE-bench: A New Benchmark for Measuring How Well AI Agents Perform at Machine Learning Engineering Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” An essential bridge connecting human language and structured query languages (SQL) is text-to-SQL. With its help, users can convert their queries in normal language into SQL commands that a database can comprehend and carry out. This technology makes it easier for users to interface… Read More »Google Cloud and Stanford Researchers Propose CHASE-SQL: An AI Framework for Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQL Tanya Malhotra Artificial Intelligence Category – MarkTechPost

​[[{“value”:” LLMs are gaining traction as the workforce across domains is exploring artificial intelligence and automation to plan their operations and make crucial decisions. Generative and Foundational models are thus relied on for multi-step reasoning tasks to achieve planning and execution at par with humans.… Read More »IBM Researchers ACPBench: An AI Benchmark for Evaluating the Reasoning Tasks in the Field of Planning Adeeba Alam Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Large Language Models (LLMs) have gained significant attention in recent years, but improving their performance remains a challenging task. Researchers are striving to enhance already-trained models by creating additional, targeted training data that addresses specific weaknesses. This process, known as instruction tuning and alignment,… Read More »UNC Chapel Hill Researchers Propose DataEnvGym: A Testbed of Teacher Environments for Data Generation Agents Mohammad Asjad Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Multimodal Large Language Models (MLLMs) have made significant progress in various applications using the power of Transformer models and their attention mechanisms. However, these models face a critical challenge of inherent biases in their initial parameters, known as modality priors, which can negatively impact… Read More »CausalMM: A Causal Inference Framework that Applies Structural Causal Modeling to Multimodal Large Language Models (MLLMs) Sajjad Ansari Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Graphical User Interface (GUI) agents are crucial in automating interactions within digital environments, similar to how humans operate software using keyboards, mice, or touchscreens. GUI agents can simplify complex processes such as software testing, web automation, and digital assistance by autonomously navigating and manipulating… Read More »UGround: A Universal GUI Visual Grounding Model Developed with Large-Scale Web-based Synthetic Data Nikhil Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Addressing the Challenges in AI Development The journey to building open source and collaborative AI has faced numerous challenges. One major problem is the centralization of AI model development, which has largely been controlled by a big AI players with vast resources. This concentration… Read More »INTELLECT-1: The First Decentralized 10-Billion-Parameter AI Model Training Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” In the rapidly evolving world of artificial intelligence, one pressing challenge that developers face is orchestrating complex multi-agent systems. These systems, involving multiple AI agents working collaboratively, often present significant difficulties in coordination, control, and scalability. Current solutions tend to be heavy, requiring extensive… Read More »OpenAI Releases Swarm: An Experimental AI Framework for Building, Orchestrating, and Deploying Multi-Agent Systems Asif Razzaq Artificial Intelligence Category – MarkTechPost

​[[{“value”:” Text-to-Audio (TTA) and Text-to-Music (TTM) generation have seen significant advancements in recent years, driven by audio-domain diffusion models. These models have demonstrated superior audio modeling capabilities compared to generative adversarial networks (GANs) and variational autoencoders (VAEs). However, diffusion models face the challenge of long… Read More »Researchers from UCSD and Adobe Introduce Presto!: An AI Approach to Inference Acceleration for Score-based Diffusion Transformers via Reducing both Sampling Steps and Cost Per Step Sajjad Ansari Artificial Intelligence Category – MarkTechPost