Hive

abdelzaher1 (4)in #ai • 12 days ago
Nvidia AI Introduces the Normalized Transformer (nGPT): A Hypersphere-based Transformer Achieving 4-20x Faster Training and Improved Stability for LLMs
Researchers from NVIDIA propose a novel architecture called the Normalized Transformer (nGPT), which incorporates representation learning on the hypersphere. In this approach…
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abdelzaher1 (4)in #ai • 13 days ago
Understanding Local Rank and Information Compression in Deep Neural Networks
The proposed framework is centered around the definition and analysis of local rank, which is defined as the expected rank of the Jacobian of the pre-activation function with…
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abdelzaher1 (4)in #ai • 14 days ago
Researchers at Stanford University Propose Locality Alignment: A New Post-Training Stage for Vision Transformers ViTs
Researchers from Stanford University propose a novel solution called Locality Alignment, which involves a post-training stage for Vision Transformers. This process aims to…
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abdelzaher1 (4)in #cats • 15 days ago
Only thing that can save me now
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abdelzaher1 (4)in #ai • 16 days ago
How Large Language Models (LLMs) can Perform Multiple, Computationally Distinct In-Context Learning (ICL) Tasks Simultaneously
In a recent study from the University of Wisconsin-Madison, the University of Michigan, and Microsoft Research, the occurrence of task superposition across different LLM kinds…
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abdelzaher1 (4)in #ai • 18 days ago
IoT-LLM: An AI Framework that Integrates IoT Sensor Data with LLMs to Enhance their Perception and Reasoning Abilities in the Physical World
Rule-based systems, traditional machine learning models, and basic AI-driven methods are conventional models for processing IoT data. Processing dense numerical data and complex…
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abdelzaher1 (4)in #ai • 19 days ago
Differentiable Adaptive Merging (DAM): A Novel AI Approach to Model Integration
Researchers from Arcee AI and Liquid AI propose a novel merging technique called Differentiable Adaptive Merging (DAM). DAM aims to tackle the complexities of merging language…
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abdelzaher1 (4)in #ai • 20 days ago
Google AI Research Examines Random Circuit Sampling (RCS) for Evaluating Quantum Computer Performance in the Presence of Noise
Google researchers address the challenge of evaluating quantum computer performance in the noisy intermediate-scale quantum (NISQ) era, where quantum processors are highly…
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abdelzaher1 (4)in #ai • 21 days ago
Google AI Introduces Gemma-APS: A Collection of Gemma Models for Text-to-Propositions Segmentation
Google AI Releases Gemma-APS, a collection of Gemma models for text-to-propositions segmentation. The models are distilled from fine-tuned Gemini Pro models applied to…
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abdelzaher1 (4)in #ai • 22 days ago
MEGA-Bench: A Comprehensive AI Benchmark that Scales Multimodal Evaluation to Over 500 Real-World Tasks at a Manageable Inference Cost
A team of researchers from the MEGA-Bench Team introduces MEGA-Bench, an innovative and comprehensive benchmark that scales multimodal evaluation to encompass more than 500…
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abdelzaher1 (4)in #ai • 23 days ago
Simular Research Introduces Agent S: An Open-Source AI Framework Designed to Interact Autonomously with Computers through a Graphical User Interface
Simular Research introduces Agent S, an open agentic framework designed to use computers like a human, specifically through autonomous interaction with GUIs. This framework aims…
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abdelzaher1 (4)in #ai • 25 days ago
Researchers from UCLA and Stanford Introduce MRAG-Bench: An AI Benchmark Specifically Designed for Vision-Centric Evaluation for Retrieval-Augmented Multimodal Models
Researchers from UCLA and Stanford introduced MRAG-Bench, a vision-centric benchmark designed to evaluate the effectiveness of LVLMs in scenarios where visual information…
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abdelzaher1 (4)in #ai • 26 days ago
OpenR: An Open-Source AI Framework Enhancing Reasoning in Large Language Models
Researchers from University College London, the University of Liverpool, Shanghai Jiao Tong University, The Hong Kong University of Science and Technology (Guangzhou), and…
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abdelzaher1 (4)in #ai • 27 days ago
Researchers from Moore Threads AI Introduce TurboRAG: A Novel AI Approach to Boost RAG Inference Speed
Researchers from Moore Threads AI introduce TurboRAG, a novel approach to optimize the inference paradigm of RAG systems by pre-computing and storing the KV caches of documents…
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abdelzaher1 (4)in #ai • 27 days ago
Exposing Vulnerabilities in Automatic LLM Benchmarks: The Need for Stronger Anti-Cheating Mechanisms
Evaluating open-ended text generation is challenging because a single correct output is needed. Human evaluation is reliable but costly and time-consuming, so LLMs are often used…
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abdelzaher1 (4)in #ai • 29 days ago
Researchers at Stanford University Propose ExPLoRA: A Highly Effective AI Technique to Improve Transfer Learning of Pre-Trained Vision Transformers (ViTs) Under Domain Shifts
Vision foundation models (VFMs) like DinoV2 and masked autoencoders (MAE) have shown excellent performance in tasks such as classification and semantic segmentation through…
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abdelzaher1 (4)in #ai • last month
INTELLECT-1: The First Decentralized 10-Billion-Parameter AI Model Training
Prime Intellect AI launches INTELLECT-1, the first decentralized training run of a 10-billion-parameter model, inviting anyone to contribute compute and participate. This…
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abdelzaher1 (4)in #ai • last month
OpenAI Releases Swarm: An Experimental AI Framework for Building, Orchestrating, and Deploying Multi-Agent Systems
OpenAI introduces the Swarm Framework as a solution to simplify the complexities inherent in multi-agent orchestration. Swarm is an experimental framework that focuses on making…
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abdelzaher1 (4)in #ai • last month
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
Existing attempts to address the challenges in Text-to-Audio (TTA) and Text-to-Music (TTM) generation have primarily focused on autoregressive (AR) techniques and diffusion…
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abdelzaher1 (4)in #ai • last month
Google AI Researchers Propose Astute RAG: A Novel RAG Approach to Deal with the Imperfect Retrieval Augmentation and Knowledge Conflicts of LLMs
When RAG systems retrieve external data, there is always the risk of pulling in irrelevant, outdated, or malicious information. A major challenge associated with RAG is the issue…
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