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Research

What’s next for IVF

DGX agent

MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here. Forty-eight years ago this July

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7 May 2026

Research

Search: “research”

What’s next for IVF

When Does Gene Regulatory Network Inference Break? A Controlled Diagnostic Study of Causal and Correlational Methods on Single-Cell Data

When Engineering Outruns Intelligence: Rethinking Instruction-Guided Navigation

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise

Why Geometric Continuity Emerges in Deep Neural Networks: Residual Connections and Rotational Symmetry Breaking

3D Human Face Reconstruction with 3DMM face model from RGB image

4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere

A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration

A Closed-Form Adaptive-Landmark Kernel for Certified Point-Cloud and Graph Classification

A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion

A Comprehensive Analysis of Tokenization and Self-Supervised Learning in End-to-End Automatic Speech Recognition applied on French Language

A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning

A note on the unique properties of the Kullback--Leibler divergence for sampling via gradient flows

A Paradigm for Interpreting Metrics and Identifying Critical Errors in Automatic Speech Recognition

A Partition-Based Generating Function for Row-Convex Polyominoes

A Perfectly Truthful Calibration Measure

A Sentence Relation-Based Approach to Sanitizing Malicious Instructions

A Target-Free Harmonization Method for MRI

A User-Centric Analysis of Explainability in AI-Based Medical Image Diagnosis

Accelerating Inference of Discrete Autoregressive Normalizing Flows by Selective Jacobi Decoding

Adaptive Data Compression and Reconstruction for Memory-Bounded EEG Continual Learning

Adaptive Estimation and Optimal Control in Offline Contextual MDPs without Stationarity

Adaptive graph-based algorithms for conditional anomaly detection and semi-supervised learning

AI agents often struggle to plan movements because their internal representations of the physical world can be overly tangled. CDS PhD stude…

AMSnet-q: Unsupervised Circuit Identification and Performance Labeling for AMS Circuits

An ERP Study of Recursive Possessive Parsing in ASD Children and Its Cognitive Neuro Mechanisms

Analysis and Explainability of LLMs Via Evolutionary Methods

Analytic Bridge Diffusions for Controlled Path Generation

Are we Doomed to an AI Race? Why Self-Interest Could Drive Countries Towards a Moratorium on Superintelligence

AsymK-Talker: Real-Time and Long-Horizon Talking Head Generation via Asymmetric Kernel Distillation

Atomic Fact-Checking Increases Clinician Trust in Large Language Model Recommendations for Oncology Decision Support: A Randomized Controlled Trial

Attribution-Guided Masking for Robust Cross-Domain Sentiment Classification

Bandits on graphs and structures

Behavior-dLDS: A decomposed linear dynamical systems model for neural activity partially constrained by behavior

Beyond Scalars: Evaluating and Understanding LLM Reasoning via Geometric Progress and Stability

BiMind: A Dual-Head Reasoning Model with Attention-Geometry Adapter for Incorrect Information Detection

Boundary-Aware Uncertainty Quantification for Wildfire Spread Prediction

Caliper-in-the-Loop: Black-Box Optimization for Hyperledger Fabric Performance Tuning

Can Blockchains Reliably Train Machine Learning Models?

Can Multimodal Large Language Models Understand Pathologic Movements? A Pilot Study on Seizure Semiology

Cascade Token Selection for Transformer Attention Acceleration

CellxPert: Inference-Time MCMC Steering of a Multi-Omics Single-Cell Foundation Model for In-Silico Perturbation

Certified Purity for Cognitive Workflow Executors: From Static Analysis to Cryptographic Attestation

CLAPS: Aleatoric-Epistemic Scaling via Last-Layer Laplace for Conformal Regression

Client-Conditional Federated Learning via Local Training Data Statistics

Co-Generative De Novo Functional Protein Design

Code World Model Preparedness Report

Complex Equation Learner: Rational Symbolic Regression with Gradient Descent in Complex Domain