Skip to content
TILens What matters today in tech v0.3.2
Theme

Topic - Edition

AI Research

877 items on 23 Oct 2026
AI Research AI Python

Don’t Let Messy Data Bend Your Curves

Robust Estimation Series: Building Accurate Curves with Polynomials and Splines With Spurious Data The post Don’t Let Messy Data Bend Your Curves appeared first on Towards Data Science.

Source: Towards Data Science Aamir Hussain Chughtai, PhD
AI Research AI

Automated screening of privacy risks in medical AI

arXiv:2610.30229v1 Announce Type: new Abstract: Medical artificial intelligence (AI) models are often shared without their training data, assuming this protects the patients who contributed them. However, a model can…

Source: arXiv cs.LG Konstantinos Vrettos, Eleftherios Tzanis, Haridimos Kondylakis, Evangelia E. Vassalou, Florence X. Doo, Michail E. Klontzas
AI Research AI

FreeEvolve: Learning to Evolve Beyond Fixed Loops

arXiv:2610.09197v2 Announce Type: replace-cross Abstract: Agent evolvers automate the design of the prompts, skills and workflows around language model agents, yet the optimization process they follow is still designed…

Source: arXiv cs.LG Lecheng Kong, Like Hui, Nikos Kanakaris, Prithwish Jana, Sahika Genc, Narayanan Sadagopan
AI Research AI

Random Remasking Scales Masked Diffusion Inference

arXiv:2610.30744v1 Announce Type: new Abstract: Masked diffusion models (MDMs) generate sequences by progressively unmasking tokens, but errors introduced during decoding are typically irreversible. Recent work has…

Source: arXiv cs.LG Zhaoyi Zhou, Frank Wu, Andrea Zanette
AI Research AI

Graph Memory Transformer (GMT)

arXiv:2604.23862v4 Announce Type: replace Abstract: We investigate whether an explicit learned memory graph can replace the Feed-Forward Network (FFN) sublayer in a decoder-only transformer while preserving the…

Source: arXiv cs.LG Nicola Zanarini, Niccol\`o Ferrari, Evelina Lamma
AI Research AI

ACTIVA: Amortized Causal Effect Estimation via Variational Autoencoders

arXiv:2503.01290v4 Announce Type: replace Abstract: Predicting post-intervention distributions from observational data is central to many scientific and decision-making problems, but remains challenging due to causal…

Source: arXiv cs.LG Andreas Sauter, Saber Salehkaleybar, Frank van Harmelen, Aske Plaat, Erman Acar

877 items available