GPUs, training clusters, MLOps, and deployment
So, yesterday run was a success and I did get an avg rollout length of about 64 tokens as attached in the image! This was with quality_re...
![[2603.10652] Are Video Reasoning Models Ready to Go Outside?](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2603.10652: Are Video Reasoning Models Ready to Go Outside?
Abstract page for arXiv paper 2602.00181: CamReasoner: Reinforcing Camera Movement Understanding via Structured Spatial Reasoning
This paper discusses the geometric coherence issues in global aggregation for Federated Graph Neural Networks (GNNs) and proposes a new f...
The paper explores how AI models can learn to obfuscate deception when trained against white-box deception detectors, introducing a taxon...
This article evaluates a federated learning framework for mood inference using smartphone sensing data across different countries, highli...
This paper presents a novel framework for joint signal enhancement and classification using coupled diffusion models, improving accuracy ...
The paper introduces Fractional-Order Federated Averaging (FOFedAvg), a novel federated learning approach that enhances model training ef...
The paper presents FedPSA, a novel framework for Asynchronous Federated Learning that improves performance by dynamically measuring model...
This paper explores the effectiveness of randomly masking updates in adaptive optimizers for training large language models, introducing ...
This article presents a hybrid framework combining Federated Learning and Split Learning to enhance privacy in clinical decision-making w...
The paper discusses multilingual data curation strategies for training foundation models, revealing that targeted improvements in data qu...
The paper presents MAVRL, a novel approach for learning reward functions from multiple feedback types using amortized variational inferen...
The paper presents COMPOT, a novel framework for compressing Transformer models using Calibration-Optimized Matrix Procrustes Orthogonali...
The paper presents a Decoupled Representation Refinement (DRR) paradigm for Implicit Neural Representations (INRs), enhancing speed and f...
The article reveals the discovery of Claude for Government within the Claude Desktop binary, detailing its deployment and integration wit...
Seton Hall University has launched an Artificial Intelligence Advisory Council to guide ethical AI use and education, aligning with its C...
The article discusses how NetSuite's AI capabilities enhance organizational efficiency and insight through automation and data management...
This article presents findings from testing an INT8 model across five Snapdragon chipsets, revealing significant variations in accuracy, ...
This article discusses a live demo showcasing AI shopping experiences using structured data via the Universal Commerce Protocol (UCP), hi...
The article discusses the implications of local summarization models outperforming cloud-based solutions, raising questions about the fut...
The article discusses the significant disparity between AI demonstrations and actual enterprise usage, highlighting issues like tool acce...
The article discusses the implementation of a self-hosted Claude swarm on cloud infrastructure, focusing on its resilience during system ...
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