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Microsoft takes on AI rivals with three new foundational models | TechCrunch
Machine Learning

Microsoft takes on AI rivals with three new foundational models | TechCrunch

MAI released models that can transcribe voice into text as well as generate audio and images after the group's formation six months ago.

TechCrunch - AI · 4 min ·
Machine Learning

[D] Make. Big. Batch. Size.

It's something between vent and learning. I tried training RWKV v6 model by my own code on my RTX 4050. I trained over 50k steps on batch...

Reddit - Machine Learning · 1 min ·
Machine Learning

AI Tools That Can’t Prove What They Did Will Hit a Wall

Most AI products are still judged like answer machines. People ask whether the model is smart, fast, creative, cheap, or good at sounding...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2510.12453] Time-Correlated Video Bridge Matching
Machine Learning

[2510.12453] Time-Correlated Video Bridge Matching

Abstract page for arXiv paper 2510.12453: Time-Correlated Video Bridge Matching

arXiv - Machine Learning · 3 min ·
[2510.06790] Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness
Llms

[2510.06790] Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness

Abstract page for arXiv paper 2510.06790: Get RICH or Die Scaling: Profitably Trading Inference Compute for Robustness

arXiv - Machine Learning · 4 min ·
[2510.04900] Benchmarking M-LTSF: Frequency and Noise-Based Evaluation of Multivariate Long Time Series Forecasting Models
Machine Learning

[2510.04900] Benchmarking M-LTSF: Frequency and Noise-Based Evaluation of Multivariate Long Time Series Forecasting Models

Abstract page for arXiv paper 2510.04900: Benchmarking M-LTSF: Frequency and Noise-Based Evaluation of Multivariate Long Time Series Fore...

arXiv - Machine Learning · 4 min ·
[2603.25716] Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models
Machine Learning

[2603.25716] Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models

Abstract page for arXiv paper 2603.25716: Out of Sight but Not Out of Mind: Hybrid Memory for Dynamic Video World Models

arXiv - AI · 4 min ·
[2509.15199] CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness
Machine Learning

[2509.15199] CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness

Abstract page for arXiv paper 2509.15199: CausalPre: Scalable and Effective Data Pre-Processing for Causal Fairness

arXiv - Machine Learning · 4 min ·
[2508.09223] Hierarchical Adaptive networks with Task vectors for Test-Time Adaptation
Machine Learning

[2508.09223] Hierarchical Adaptive networks with Task vectors for Test-Time Adaptation

Abstract page for arXiv paper 2508.09223: Hierarchical Adaptive networks with Task vectors for Test-Time Adaptation

arXiv - AI · 4 min ·
[2509.08617] Towards Interpretable Deep Neural Networks for Tabular Data
Machine Learning

[2509.08617] Towards Interpretable Deep Neural Networks for Tabular Data

Abstract page for arXiv paper 2509.08617: Towards Interpretable Deep Neural Networks for Tabular Data

arXiv - Machine Learning · 3 min ·
[2603.25697] The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase
Llms

[2603.25697] The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase

Abstract page for arXiv paper 2603.25697: The Kitchen Loop: User-Spec-Driven Development for a Self-Evolving Codebase

arXiv - AI · 3 min ·
[2507.19737] Predicting Human Mobility during Extreme Events via LLM-Enhanced Cross-City Learning
Llms

[2507.19737] Predicting Human Mobility during Extreme Events via LLM-Enhanced Cross-City Learning

Abstract page for arXiv paper 2507.19737: Predicting Human Mobility during Extreme Events via LLM-Enhanced Cross-City Learning

arXiv - AI · 4 min ·
[2505.23004] QLIP: A Dynamic Quadtree Vision Prior Enhances MLLM Performance Without Retraining
Llms

[2505.23004] QLIP: A Dynamic Quadtree Vision Prior Enhances MLLM Performance Without Retraining

Abstract page for arXiv paper 2505.23004: QLIP: A Dynamic Quadtree Vision Prior Enhances MLLM Performance Without Retraining

arXiv - Machine Learning · 4 min ·
[2603.25646] A Mentalistic Interface for Probing Folk-Psychological Attribution to Non-Humanoid Robots
Llms

[2603.25646] A Mentalistic Interface for Probing Folk-Psychological Attribution to Non-Humanoid Robots

Abstract page for arXiv paper 2603.25646: A Mentalistic Interface for Probing Folk-Psychological Attribution to Non-Humanoid Robots

arXiv - AI · 3 min ·
[2411.17501] The Limits of Inference Scaling Through Resampling
Machine Learning

[2411.17501] The Limits of Inference Scaling Through Resampling

Abstract page for arXiv paper 2411.17501: The Limits of Inference Scaling Through Resampling

arXiv - AI · 4 min ·
[2603.25613] Demographic Fairness in Multimodal LLMs: A Benchmark of Gender and Ethnicity Bias in Face Verification
Llms

[2603.25613] Demographic Fairness in Multimodal LLMs: A Benchmark of Gender and Ethnicity Bias in Face Verification

Abstract page for arXiv paper 2603.25613: Demographic Fairness in Multimodal LLMs: A Benchmark of Gender and Ethnicity Bias in Face Verif...

arXiv - AI · 4 min ·
[2410.21764] Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning
Machine Learning

[2410.21764] Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning

Abstract page for arXiv paper 2410.21764: Adaptive Online Mirror Descent for Tchebycheff Scalarization in Multi-Objective Learning

arXiv - AI · 4 min ·
[2603.25607] DeepFAN, a transformer-based deep learning model for human-artificial intelligence collaborative assessment of incidental pulmonary nodules in CT scans: a multi-reader, multi-case trial
Machine Learning

[2603.25607] DeepFAN, a transformer-based deep learning model for human-artificial intelligence collaborative assessment of incidental pulmonary nodules in CT scans: a multi-reader, multi-case trial

Abstract page for arXiv paper 2603.25607: DeepFAN, a transformer-based deep learning model for human-artificial intelligence collaborativ...

arXiv - AI · 4 min ·
[2408.05696] SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction
Llms

[2408.05696] SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction

Abstract page for arXiv paper 2408.05696: SMILES-Mamba: Chemical Mamba Foundation Models for Drug ADMET Prediction

arXiv - Machine Learning · 4 min ·
[2403.04545] Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets
Machine Learning

[2403.04545] Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization in Overparameterized ResNets

Abstract page for arXiv paper 2403.04545: Branch Scaling Manifests as Implicit Architectural Regularization for Improving Generalization ...

arXiv - Machine Learning · 3 min ·
[2401.12546] On Building Myopic MPC Policies using Supervised Learning
Machine Learning

[2401.12546] On Building Myopic MPC Policies using Supervised Learning

Abstract page for arXiv paper 2401.12546: On Building Myopic MPC Policies using Supervised Learning

arXiv - Machine Learning · 4 min ·
[2603.25740] Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving
Machine Learning

[2603.25740] Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving

Abstract page for arXiv paper 2603.25740: Drive My Way: Preference Alignment of Vision-Language-Action Model for Personalized Driving

arXiv - AI · 4 min ·
[2603.25722] No Hard Negatives Required: Concept Centric Learning Leads to Compositionality without Degrading Zero-shot Capabilities of Contrastive Models
Machine Learning

[2603.25722] No Hard Negatives Required: Concept Centric Learning Leads to Compositionality without Degrading Zero-shot Capabilities of Contrastive Models

Abstract page for arXiv paper 2603.25722: No Hard Negatives Required: Concept Centric Learning Leads to Compositionality without Degradin...

arXiv - Machine Learning · 4 min ·
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