GPUs, training clusters, MLOps, and deployment
UMKC announces a new Master of Science in Artificial Intelligence program aimed at addressing workforce demand for AI expertise, set to l...
Hello! Recently I did a project where I initially had around 30 target classes. But at inference, the model had to be able to handle a lo...
What is your opinion on long appendices in conference papers? I am observing that appendix lengths in conference papers (ICML, NeurIPS, e...
![[2603.24595] Model2Kernel: Model-Aware Symbolic Execution For Safe CUDA Kernels](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2603.24595: Model2Kernel: Model-Aware Symbolic Execution For Safe CUDA Kernels
Abstract page for arXiv paper 2603.24828: A Practical Guide Towards Interpreting Time-Series Deep Clinical Predictive Models: A Reproduci...
Abstract page for arXiv paper 2603.25498: EcoThink: A Green Adaptive Inference Framework for Sustainable and Accessible Agents
Abstract page for arXiv paper 2603.25480: Retraining as Approximate Bayesian Inference
Abstract page for arXiv paper 2603.25450: Cross-Model Disagreement as a Label-Free Correctness Signal
Abstract page for arXiv paper 2603.25412: Beyond Content Safety: Real-Time Monitoring for Reasoning Vulnerabilities in Large Language Models
Abstract page for arXiv paper 2603.24709: Training LLMs for Multi-Step Tool Orchestration with Constrained Data Synthesis and Graduated R...
Abstract page for arXiv paper 2603.24648: Energy-Efficient Hierarchical Federated Anomaly Detection for the Internet of Underwater Things...
Abstract page for arXiv paper 2603.25197: The Competence Shadow: Theory and Bounds of AI Assistance in Safety Engineering
Abstract page for arXiv paper 2603.25075: Sparse Visual Thought Circuits in Vision-Language Models
Abstract page for arXiv paper 2603.25035: Mechanistically Interpreting Compression in Vision-Language Models
Abstract page for arXiv paper 2603.24967: The Anatomy of Uncertainty in LLMs
Abstract page for arXiv paper 2603.24929: LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics
Abstract page for arXiv paper 2603.24904: On the Foundations of Trustworthy Artificial Intelligence
Most people just type into ChatGPT like it's Google. Claude with a structured system prompt using XML tags behaves like a completely diff...
Been running local agents with Ollama + LangChain lately and noticed something kind of uncomfortable — you can get a completely correct f...
Wrote up the process of pushing Qwen 3.5 27B (dense, FP8) to 1.1M total tok/s on 96 B200 GPUs with vLLM v0.18.0. DP=8 nearly 4x'd through...
Relatively light at just 2 billion parameters, the model is meant for use with consumer-grade GPUs for those who want to self-host it. It...
Google TurboQuant This is a new compression algorithm. Every time a model answers a question, it stores a massive amount of intermediate ...
If we use Predictive Coding architecture we wouldn't need backpropogation anymore which would work well for a non deterministic system th...
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