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Llms

GPT-4 vs Claude vs Gemini for coding — honest breakdown after 3 months of daily use

I am a solo developer who has been using all three seriously. Here is what I actually think: GPT-4o — Strengths: Large context window, st...

Reddit - Artificial Intelligence · 1 min ·
Open Source Ai

From OpenAI to Nvidia, firms channel billions into AI infrastructure as demand booms

This article is discussing another large investment being made by tech firms into AI projects. I’ve noticed that whilst this is happening...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

easyaligner: Forced alignment with GPU acceleration and flexible text normalization (compatible with all w2v2 models on HF Hub) [P]

https://preview.redd.it/f4d5krhkjyvg1.png?width=1020&format=png&auto=webp&s=11310f377b22abbe3dd110cc7d362ba8aae35f8d I have b...

Reddit - Machine Learning · 1 min ·

All Content

[2602.13290] AGORA: Agentic Green Orchestration Architecture for Beyond 5G Networks
Ai Agents

[2602.13290] AGORA: Agentic Green Orchestration Architecture for Beyond 5G Networks

The AGORA paper presents an innovative architecture for managing Beyond 5G networks, focusing on sustainability by integrating AI-driven ...

arXiv - AI · 4 min ·
[2602.14444] Broken Chains: The Cost of Incomplete Reasoning in LLMs
Llms

[2602.14444] Broken Chains: The Cost of Incomplete Reasoning in LLMs

The paper explores the impact of incomplete reasoning in large language models (LLMs), revealing how different reasoning modalities affec...

arXiv - AI · 4 min ·
[2602.14432] S2D: Selective Spectral Decay for Quantization-Friendly Conditioning of Neural Activations
Machine Learning

[2602.14432] S2D: Selective Spectral Decay for Quantization-Friendly Conditioning of Neural Activations

The paper introduces Selective Spectral Decay (S2D), a method to improve quantization in neural networks by addressing activation outlier...

arXiv - AI · 4 min ·
[2602.13289] Evaluating the Impact of Post-Training Quantization on Reliable VQA with Multimodal LLMs
Llms

[2602.13289] Evaluating the Impact of Post-Training Quantization on Reliable VQA with Multimodal LLMs

This paper evaluates the effects of Post-Training Quantization (PTQ) on the reliability and accuracy of Visual Question Answering (VQA) u...

arXiv - AI · 4 min ·
[2602.13273] MergePipe: A Budget-Aware Parameter Management System for Scalable LLM Merging
Llms

[2602.13273] MergePipe: A Budget-Aware Parameter Management System for Scalable LLM Merging

MergePipe is a novel parameter management system designed to enhance the scalability of large language model (LLM) merging by optimizing ...

arXiv - AI · 4 min ·
[2602.13261] A feedback control optimizer for online and hardware-aware training of Spiking Neural Networks
Machine Learning

[2602.13261] A feedback control optimizer for online and hardware-aware training of Spiking Neural Networks

This article presents a novel feedback control optimizer for training Spiking Neural Networks (SNNs) on mixed-signal devices, addressing ...

arXiv - AI · 4 min ·
[2602.14318] In Transformer We Trust? A Perspective on Transformer Architecture Failure Modes
Machine Learning

[2602.14318] In Transformer We Trust? A Perspective on Transformer Architecture Failure Modes

The paper examines the trustworthiness of transformer architectures in high-stakes applications, analyzing their reliability, interpretab...

arXiv - Machine Learning · 4 min ·
[2602.14301] DeepFusion: Accelerating MoE Training via Federated Knowledge Distillation from Heterogeneous Edge Devices
Llms

[2602.14301] DeepFusion: Accelerating MoE Training via Federated Knowledge Distillation from Heterogeneous Edge Devices

DeepFusion introduces a scalable framework for federated training of Mixture-of-Experts (MoE) models, leveraging knowledge distillation f...

arXiv - AI · 4 min ·
[2602.13246] Global AI Bias Audit for Technical Governance
Llms

[2602.13246] Global AI Bias Audit for Technical Governance

This article discusses a global audit of Large Language Models (LLMs) focusing on geographic and socioeconomic biases in AI governance, h...

arXiv - AI · 4 min ·
[2602.14295] Machine Learning as a Tool (MLAT): A Framework for Integrating Statistical ML Models as Callable Tools within LLM Agent Workflows
Llms

[2602.14295] Machine Learning as a Tool (MLAT): A Framework for Integrating Statistical ML Models as Callable Tools within LLM Agent Workflows

The paper introduces Machine Learning as a Tool (MLAT), a framework for integrating statistical ML models as callable tools within LLM wo...

arXiv - AI · 4 min ·
[2602.14293] KernelBlaster: Continual Cross-Task CUDA Optimization via Memory-Augmented In-Context Reinforcement Learning
Llms

[2602.14293] KernelBlaster: Continual Cross-Task CUDA Optimization via Memory-Augmented In-Context Reinforcement Learning

KernelBlaster introduces a novel framework for optimizing CUDA code across GPU architectures using Memory-Augmented In-Context Reinforcem...

arXiv - AI · 4 min ·
[2602.13244] Responsible AI in Business
Machine Learning

[2602.13244] Responsible AI in Business

The paper discusses the concept of Responsible AI in business, focusing on its implementation in small and medium-sized enterprises. It c...

arXiv - AI · 4 min ·
[2602.13241] Real-World Design and Deployment of an Embedded GenAI-powered 9-1-1 Calltaking Training System: Experiences and Lessons Learned
Machine Learning

[2602.13241] Real-World Design and Deployment of an Embedded GenAI-powered 9-1-1 Calltaking Training System: Experiences and Lessons Learned

This article discusses the design and deployment of a GenAI-powered training system for 9-1-1 call-takers, highlighting the challenges fa...

arXiv - AI · 4 min ·
[2602.14275] Reverse N-Wise Output-Oriented Testing for AI/ML and Quantum Computing Systems
Machine Learning

[2602.14275] Reverse N-Wise Output-Oriented Testing for AI/ML and Quantum Computing Systems

The paper introduces Reverse N-Wise Output-Oriented Testing, a novel approach for testing AI/ML and quantum computing systems, addressing...

arXiv - AI · 4 min ·
[2602.13231] An Explainable Failure Prediction Framework for Neural Networks in Radio Access Networks
Machine Learning

[2602.13231] An Explainable Failure Prediction Framework for Neural Networks in Radio Access Networks

This paper presents a framework for explainable failure prediction in neural networks used in radio access networks, enhancing model tran...

arXiv - Machine Learning · 4 min ·
[2602.13227] An Agentic AI Control Plane for 6G Network Slice Orchestration, Monitoring, and Trading
Ai Agents

[2602.13227] An Agentic AI Control Plane for 6G Network Slice Orchestration, Monitoring, and Trading

This paper presents an innovative AI control plane for 6G network slice orchestration, emphasizing agentic autonomy and market-aware capa...

arXiv - AI · 4 min ·
[2602.14274] Integrating Unstructured Text into Causal Inference: Empirical Evidence from Real Data
Llms

[2602.14274] Integrating Unstructured Text into Causal Inference: Empirical Evidence from Real Data

This paper presents a framework for integrating unstructured text into causal inference, demonstrating its effectiveness against traditio...

arXiv - AI · 3 min ·
[2602.13211] An Overlay Multicast Routing Method Based on Network Situational Aware-ness and Hierarchical Multi-Agent Reinforcement Learning
Ai Infrastructure

[2602.13211] An Overlay Multicast Routing Method Based on Network Situational Aware-ness and Hierarchical Multi-Agent Reinforcement Learning

This article presents MA-DHRL-OM, a novel overlay multicast routing method utilizing multi-agent deep hierarchical reinforcement learning...

arXiv - AI · 3 min ·
[2602.13207] A Safety-Constrained Reinforcement Learning Framework for Reliable Wireless Autonomy
Ai Infrastructure

[2602.13207] A Safety-Constrained Reinforcement Learning Framework for Reliable Wireless Autonomy

This article presents a safety-constrained reinforcement learning framework aimed at enhancing the reliability of wireless autonomy, part...

arXiv - AI · 4 min ·
[2602.14233] Evaluating LLMs in Finance Requires Explicit Bias Consideration
Llms

[2602.14233] Evaluating LLMs in Finance Requires Explicit Bias Consideration

This paper discusses the need for explicit bias consideration in evaluating Large Language Models (LLMs) used in finance, identifying fiv...

arXiv - AI · 3 min ·
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Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

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