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autosculpt:-a-pattern-based-automated-pruning-framework-designed-to-enhance-efficiency-and-accuracy-by-leveraging-graph-learning-and-deep-reinforcement-learning

AutoSculpt: A Pattern-based Automated Pruning Framework Designed to Enhance Efficiency and Accuracy by Leveraging Graph Learning and Deep Reinforcement Learning

Source: MarkTechPost Deploying Deep Neural Networks (DNNs) on edge devices, such as smartphones and autonomous vehicles, remains a...
Dec 30, 2024
b-star:-a-self-taught-ai-reasoning-framework-for-llms

B-STAR: A Self-Taught AI Reasoning Framework for LLMs

Source: MarkTechPost A direct correlation exists between an LLM’s training corpus quality and its capabilities. Consequently, researchers have...
Dec 30, 2024
advancing-parallel-programming-with-hpc-instruct:-optimizing-code-llms-for-high-performance-computing

Advancing Parallel Programming with HPC-INSTRUCT: Optimizing Code LLMs for High-Performance Computing

Source: MarkTechPost LLMs have revolutionized software development by automating coding tasks and bridging the natural language and programming...
Dec 29, 2024
this-ai-paper-proposes-tale:-an-ai-framework-that-reduces-token-redundancy-in-chain-of-thought-(cot)-reasoning-by-incorporating-token-budget-awareness

This AI Paper Proposes TALE: An AI Framework that Reduces Token Redundancy in Chain-of-Thought (CoT) Reasoning by Incorporating Token Budget Awareness

Source: MarkTechPost Large Language Models (LLMs) have shown significant potential in reasoning tasks, using methods like Chain-of-Thought (CoT)...
Dec 29, 2024
researchers-from-tsinghua-university-propose-remoe:-a-fully-differentiable-moe-architecture-with-relu-routing

Researchers from Tsinghua University Propose ReMoE: A Fully Differentiable MoE Architecture with ReLU Routing

Source: MarkTechPost The development of Transformer models has significantly advanced artificial intelligence, delivering remarkable performance across diverse tasks....
Dec 29, 2024
neuraloperator:-a-new-python-library-for-learning-neural-operators-in-pytorch

NeuralOperator: A New Python Library for Learning Neural Operators in PyTorch

Source: MarkTechPost Operator learning is a transformative approach in scientific computing. It focuses on developing models that map...
Dec 29, 2024
aixplain-introduces-a-multi-ai-agent-autonomous-framework-for-optimizing-agentic-ai-systems-across-diverse-industries-and-applications

aiXplain Introduces a Multi-AI Agent Autonomous Framework for Optimizing Agentic AI Systems Across Diverse Industries and Applications

Source: MarkTechPost Agentic AI systems have revolutionized industries by enabling complex workflows through specialized agents working in collaboration....
Dec 29, 2024
hypernetwork-fields:-efficient-gradient-driven-training-for-scalable-neural-network-optimization

Hypernetwork Fields: Efficient Gradient-Driven Training for Scalable Neural Network Optimization

Source: MarkTechPost Hypernetworks have gained attention for their ability to efficiently adapt large models or train generative models...
Dec 28, 2024
this-ai-paper-explores-how-formal-systems-could-revolutionize-math-llms

This AI Paper Explores How Formal Systems Could Revolutionize Math LLMs

Source: MarkTechPost Formal mathematical reasoning represents a significant frontier in artificial intelligence, addressing fundamental logic, computation, and problem-solving...
Dec 28, 2024
collective-monte-carlo-tree-search-(comcts):-a-new-learning-to-reason-method-for-multimodal-large-language-models

Collective Monte Carlo Tree Search (CoMCTS): A New Learning-to-Reason Method for Multimodal Large Language Models

Source: MarkTechPost In today’s world, Multimodal large language models (MLLMs) are advanced systems that process and understand multiple...
Dec 28, 2024
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