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Llms

If AI is really making us more productive... why does it feel like we are working more, not less...?

The promise of AI was the ultimate system optimisation: Efficiency. On paper, the tools are delivering something similar to what they pro...

Reddit - Artificial Intelligence · 1 min ·
Ai Infrastructure

[P] Built an open source tool to find the location of any street picture

Hey guys, Thank you so much for your love and support regarding Netryx Astra V2 last time. Many people are not that technically savvy to ...

Reddit - Machine Learning · 1 min ·
Llms

[R] GPT-5.4-mini regressed 22pp on vanilla prompting vs GPT-5-mini. Nobody noticed because benchmarks don't test this. Recursive Language Models solved it.

GPT-5.4-mini produces shorter, terser outputs by default. Vanilla accuracy dropped from 69.5% to 47.2% across 12 tasks (1,800 evals). The...

Reddit - Machine Learning · 1 min ·

All Content

[2401.09346] High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization
Machine Learning

[2401.09346] High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization

Abstract page for arXiv paper 2401.09346: High Confidence Level Inference is Almost Free using Parallel Stochastic Optimization

arXiv - Machine Learning · 4 min ·
[2206.02088] LOCO Feature Importance Inference without Data Splitting via Minipatch Ensembles
Machine Learning

[2206.02088] LOCO Feature Importance Inference without Data Splitting via Minipatch Ensembles

Abstract page for arXiv paper 2206.02088: LOCO Feature Importance Inference without Data Splitting via Minipatch Ensembles

arXiv - Machine Learning · 4 min ·
[2603.16177] The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data
Machine Learning

[2603.16177] The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data

Abstract page for arXiv paper 2603.16177: The Finetuner's Fallacy: When to Pretrain with Your Finetuning Data

arXiv - Machine Learning · 4 min ·
[2603.08104] Invisible Safety Threat: Malicious Finetuning for LLM via Steganography
Llms

[2603.08104] Invisible Safety Threat: Malicious Finetuning for LLM via Steganography

Abstract page for arXiv paper 2603.08104: Invisible Safety Threat: Malicious Finetuning for LLM via Steganography

arXiv - Machine Learning · 4 min ·
[2602.05549] Logical Guidance for the Exact Composition of Diffusion Models
Machine Learning

[2602.05549] Logical Guidance for the Exact Composition of Diffusion Models

Abstract page for arXiv paper 2602.05549: Logical Guidance for the Exact Composition of Diffusion Models

arXiv - Machine Learning · 4 min ·
[2512.19735] Improving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting
Llms

[2512.19735] Improving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting

Abstract page for arXiv paper 2512.19735: Improving Fairness of Large Language Model-Based ICU Mortality Prediction via Case-Based Prompting

arXiv - Machine Learning · 4 min ·
[2510.05416] Correlating Cross-Iteration Noise for DP-SGD using Model Curvature
Machine Learning

[2510.05416] Correlating Cross-Iteration Noise for DP-SGD using Model Curvature

Abstract page for arXiv paper 2510.05416: Correlating Cross-Iteration Noise for DP-SGD using Model Curvature

arXiv - Machine Learning · 3 min ·
[2510.04058] Unlearning in Diffusion models under Data Constraints: A Variational Inference Approach
Machine Learning

[2510.04058] Unlearning in Diffusion models under Data Constraints: A Variational Inference Approach

Abstract page for arXiv paper 2510.04058: Unlearning in Diffusion models under Data Constraints: A Variational Inference Approach

arXiv - Machine Learning · 4 min ·
[2509.14617] HDC-X: Efficient Medical Data Classification for Embedded Devices
Machine Learning

[2509.14617] HDC-X: Efficient Medical Data Classification for Embedded Devices

Abstract page for arXiv paper 2509.14617: HDC-X: Efficient Medical Data Classification for Embedded Devices

arXiv - Machine Learning · 3 min ·
[2506.19609] Beyond Static Models: Hypernetworks for Adaptive and Generalizable Forecasting in Complex Parametric Dynamical Systems
Machine Learning

[2506.19609] Beyond Static Models: Hypernetworks for Adaptive and Generalizable Forecasting in Complex Parametric Dynamical Systems

Abstract page for arXiv paper 2506.19609: Beyond Static Models: Hypernetworks for Adaptive and Generalizable Forecasting in Complex Param...

arXiv - Machine Learning · 4 min ·
[2501.16562] C-HDNet: Hyperdimensional Computing for Causal Effect Estimation from Observational Data Under Network Interference
Machine Learning

[2501.16562] C-HDNet: Hyperdimensional Computing for Causal Effect Estimation from Observational Data Under Network Interference

Abstract page for arXiv paper 2501.16562: C-HDNet: Hyperdimensional Computing for Causal Effect Estimation from Observational Data Under ...

arXiv - Machine Learning · 4 min ·
[2402.15127] Asymptotically and Minimax Optimal Regret Bounds for Multi-Armed Bandits with Abstention
Ai Infrastructure

[2402.15127] Asymptotically and Minimax Optimal Regret Bounds for Multi-Armed Bandits with Abstention

Abstract page for arXiv paper 2402.15127: Asymptotically and Minimax Optimal Regret Bounds for Multi-Armed Bandits with Abstention

arXiv - Machine Learning · 4 min ·
[2308.05629] Inhibitor Transformers and Gated RNNs for Torus Efficient Fully Homomorphic Encryption
Machine Learning

[2308.05629] Inhibitor Transformers and Gated RNNs for Torus Efficient Fully Homomorphic Encryption

Abstract page for arXiv paper 2308.05629: Inhibitor Transformers and Gated RNNs for Torus Efficient Fully Homomorphic Encryption

arXiv - Machine Learning · 4 min ·
[2603.22053] AnimalCLAP: Taxonomy-Aware Language-Audio Pretraining for Species Recognition and Trait Inference
Machine Learning

[2603.22053] AnimalCLAP: Taxonomy-Aware Language-Audio Pretraining for Species Recognition and Trait Inference

Abstract page for arXiv paper 2603.22053: AnimalCLAP: Taxonomy-Aware Language-Audio Pretraining for Species Recognition and Trait Inference

arXiv - Machine Learning · 3 min ·
[2603.22050] MAGPI: Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data
Machine Learning

[2603.22050] MAGPI: Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data

Abstract page for arXiv paper 2603.22050: MAGPI: Multifidelity-Augmented Gaussian Process Inputs for Surrogate Modeling from Scarce Data

arXiv - Machine Learning · 4 min ·
[2603.21928] The Golden Subspace: Where Efficiency Meets Generalization in Continual Test-Time Adaptation
Machine Learning

[2603.21928] The Golden Subspace: Where Efficiency Meets Generalization in Continual Test-Time Adaptation

Abstract page for arXiv paper 2603.21928: The Golden Subspace: Where Efficiency Meets Generalization in Continual Test-Time Adaptation

arXiv - Machine Learning · 4 min ·
[2603.21911] A Latent Representation Learning Framework for Hyperspectral Image Emulation in Remote Sensing
Machine Learning

[2603.21911] A Latent Representation Learning Framework for Hyperspectral Image Emulation in Remote Sensing

Abstract page for arXiv paper 2603.21911: A Latent Representation Learning Framework for Hyperspectral Image Emulation in Remote Sensing

arXiv - Machine Learning · 3 min ·
[2603.21752] Identifiability and amortized inference limitations in Kuramoto models
Machine Learning

[2603.21752] Identifiability and amortized inference limitations in Kuramoto models

Abstract page for arXiv paper 2603.21752: Identifiability and amortized inference limitations in Kuramoto models

arXiv - Machine Learning · 3 min ·
[2603.21647] FedCVU: Federated Learning for Cross-View Video Understanding
Ai Safety

[2603.21647] FedCVU: Federated Learning for Cross-View Video Understanding

Abstract page for arXiv paper 2603.21647: FedCVU: Federated Learning for Cross-View Video Understanding

arXiv - Machine Learning · 3 min ·
[2603.21568] Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach
Machine Learning

[2603.21568] Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylov-Arnoldi Approach

Abstract page for arXiv paper 2603.21568: Stability and Bifurcation Analysis of Nonlinear PDEs via Random Projection-based PINNs: A Krylo...

arXiv - Machine Learning · 4 min ·
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Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision Robotics & Embodied AI

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