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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 ·
Top 10 AI certifications and courses for 2026
Ai Startups

Top 10 AI certifications and courses for 2026

This article reviews the top 10 AI certifications and courses for 2026, highlighting their significance in a rapidly evolving field and t...

AI Events · 15 min ·
Hub Group Using AI, Machine Learning for Real-Time Visibility of Shipments
Machine Learning

Hub Group Using AI, Machine Learning for Real-Time Visibility of Shipments

Hub Group says it’s using artificial intelligence and machine learning to leverage data from its GPS-equipped container fleet to give cus...

AI Events · 4 min ·

All Content

[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 ·
[2603.25638] Beyond Via: Analysis and Estimation of the Impact of Large Language Models in Academic Papers
Llms

[2603.25638] Beyond Via: Analysis and Estimation of the Impact of Large Language Models in Academic Papers

Abstract page for arXiv paper 2603.25638: Beyond Via: Analysis and Estimation of the Impact of Large Language Models in Academic Papers

arXiv - AI · 3 min ·
[2603.25462] Temporally Decoupled Diffusion Planning for Autonomous Driving
Machine Learning

[2603.25462] Temporally Decoupled Diffusion Planning for Autonomous Driving

Abstract page for arXiv paper 2603.25462: Temporally Decoupled Diffusion Planning for Autonomous Driving

arXiv - AI · 3 min ·
[2603.25629] LanteRn: Latent Visual Structured Reasoning
Machine Learning

[2603.25629] LanteRn: Latent Visual Structured Reasoning

Abstract page for arXiv paper 2603.25629: LanteRn: Latent Visual Structured Reasoning

arXiv - Machine Learning · 3 min ·
[2603.25423] From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunking in the Wild
Machine Learning

[2603.25423] From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunking in the Wild

Abstract page for arXiv paper 2603.25423: From Manipulation to Mistrust: Explaining Diverse Micro-Video Misinformation for Robust Debunki...

arXiv - AI · 4 min ·
[2603.25622] The Geometry of Efficient Nonconvex Sampling
Machine Learning

[2603.25622] The Geometry of Efficient Nonconvex Sampling

Abstract page for arXiv paper 2603.25622: The Geometry of Efficient Nonconvex Sampling

arXiv - Machine Learning · 3 min ·
[2603.25579] The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks
Machine Learning

[2603.25579] The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks

Abstract page for arXiv paper 2603.25579: The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks

arXiv - Machine Learning · 4 min ·
[2603.25573] Hierarchy-Guided Multimodal Representation Learning for Taxonomic Inference
Machine Learning

[2603.25573] Hierarchy-Guided Multimodal Representation Learning for Taxonomic Inference

Abstract page for arXiv paper 2603.25573: Hierarchy-Guided Multimodal Representation Learning for Taxonomic Inference

arXiv - Machine Learning · 4 min ·
[2603.25535] Insights on back marking for the automated identification of animals
Machine Learning

[2603.25535] Insights on back marking for the automated identification of animals

Abstract page for arXiv paper 2603.25535: Insights on back marking for the automated identification of animals

arXiv - Machine Learning · 4 min ·
[2603.25366] Integrating Deep RL and Bayesian Inference for ObjectNav in Mobile Robotics
Machine Learning

[2603.25366] Integrating Deep RL and Bayesian Inference for ObjectNav in Mobile Robotics

Abstract page for arXiv paper 2603.25366: Integrating Deep RL and Bayesian Inference for ObjectNav in Mobile Robotics

arXiv - AI · 3 min ·
[2603.25517] NERO-Net: A Neuroevolutionary Approach for the Design of Adversarially Robust CNNs
Machine Learning

[2603.25517] NERO-Net: A Neuroevolutionary Approach for the Design of Adversarially Robust CNNs

Abstract page for arXiv paper 2603.25517: NERO-Net: A Neuroevolutionary Approach for the Design of Adversarially Robust CNNs

arXiv - AI · 4 min ·
[2603.25509] Conformal Prediction for Nonparametric Instrumental Regression
Machine Learning

[2603.25509] Conformal Prediction for Nonparametric Instrumental Regression

Abstract page for arXiv paper 2603.25509: Conformal Prediction for Nonparametric Instrumental Regression

arXiv - Machine Learning · 3 min ·
[2603.25507] Lightweight GenAI for Network Traffic Synthesis: Fidelity, Augmentation, and Classification
Machine Learning

[2603.25507] Lightweight GenAI for Network Traffic Synthesis: Fidelity, Augmentation, and Classification

Abstract page for arXiv paper 2603.25507: Lightweight GenAI for Network Traffic Synthesis: Fidelity, Augmentation, and Classification

arXiv - AI · 4 min ·
[2603.25322] AD-CARE: A Guideline-grounded, Modality-agnostic LLM Agent for Real-world Alzheimer's Disease Diagnosis with Multi-cohort Assessment, Fairness Analysis, and Reader Study
Llms

[2603.25322] AD-CARE: A Guideline-grounded, Modality-agnostic LLM Agent for Real-world Alzheimer's Disease Diagnosis with Multi-cohort Assessment, Fairness Analysis, and Reader Study

Abstract page for arXiv paper 2603.25322: AD-CARE: A Guideline-grounded, Modality-agnostic LLM Agent for Real-world Alzheimer's Disease D...

arXiv - AI · 4 min ·
[2603.25466] Residual-as-Teacher: Mitigating Bias Propagation in Student--Teacher Estimation
Machine Learning

[2603.25466] Residual-as-Teacher: Mitigating Bias Propagation in Student--Teacher Estimation

Abstract page for arXiv paper 2603.25466: Residual-as-Teacher: Mitigating Bias Propagation in Student--Teacher Estimation

arXiv - Machine Learning · 3 min ·
[2603.25289] Revealing the influence of participant failures on model quality in cross-silo Federated Learning
Machine Learning

[2603.25289] Revealing the influence of participant failures on model quality in cross-silo Federated Learning

Abstract page for arXiv paper 2603.25289: Revealing the influence of participant failures on model quality in cross-silo Federated Learning

arXiv - AI · 4 min ·
[2603.25440] The Symmetric Perceptron: a Teacher-Student Scenario
Machine Learning

[2603.25440] The Symmetric Perceptron: a Teacher-Student Scenario

Abstract page for arXiv paper 2603.25440: The Symmetric Perceptron: a Teacher-Student Scenario

arXiv - Machine Learning · 4 min ·
[2603.25414] Decidable By Construction: Design-Time Verification for Trustworthy AI
Machine Learning

[2603.25414] Decidable By Construction: Design-Time Verification for Trustworthy AI

Abstract page for arXiv paper 2603.25414: Decidable By Construction: Design-Time Verification for Trustworthy AI

arXiv - AI · 4 min ·
[2603.25268] CRAFT: Grounded Multi-Agent Coordination Under Partial Information
Llms

[2603.25268] CRAFT: Grounded Multi-Agent Coordination Under Partial Information

Abstract page for arXiv paper 2603.25268: CRAFT: Grounded Multi-Agent Coordination Under Partial Information

arXiv - AI · 3 min ·
[2603.25403] Shape and Substance: Dual-Layer Side-Channel Attacks on Local Vision-Language Models
Llms

[2603.25403] Shape and Substance: Dual-Layer Side-Channel Attacks on Local Vision-Language Models

Abstract page for arXiv paper 2603.25403: Shape and Substance: Dual-Layer Side-Channel Attacks on Local Vision-Language Models

arXiv - AI · 3 min ·
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