We introduce Material Coating, a novel image editing task that simulates applying a thin material layer onto an object while preserving its underlying coarse and fine geometry. Material coating is fundamentally different from existing "material transfer" methods, which are designed to replace an object's intrinsic mate...
Sagie Levy, Elad Aharoni, Matan Levy et al.· 0 citations
Modern data processing workflows frequently encounter ragged data: collections with variable-length elements that arise naturally in domains like natural language processing, scientific measurements, and autonomous AI agents. Existing workflow engines lack native support for tracking the shapes and dependencies inheren...
Sungbin Moon, Jiho Park, Suyoung Hwang et al.· 0 citations
Bayesian optimal experimental design is a principled framework for conducting experiments that leverages Bayesian inference to quantify how much information one can expect to gain from selecting a certain design. However, accurate Bayesian inference relies on the assumption that one's statistical model of the data-gene...
Yasir Zubayr Barlas, Sabina J. Sloman, Samuel Kaski· 0 citations
Large language models represent text as hidden numerical patterns, but what information these representations actually contain remains a mystery. Can we recover the original text from just one of them? In this paper, we introduce Rep2Text, a method designed to answer this question by reconstructing text from a single h...
Haiyan Zhao, Zirui He, Yiming Tang et al.· 0 citations
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From neuroscience and genomics to systems biology and ecology, researchers rely on clustering similarity data to uncover modular structure. Most methods work in two steps: first reduce noise, then cluster. The first step runs without regard to the second: it forces arbitrary choices, discards useful information, and ca...
Magnus Neuman, Jelena Smiljani\'c, Martin Rosvall· 0 citations
Multilingual Large Language Models (LLMs) often exhibit hallucinations such as unintended code-switching, reducing reliability in downstream tasks. We propose latent-space language steering, a lightweight inference-time method that identifies language directions via Principal Component Analysis (PCA) on parallel transl...
Andrey Goncharov, Nikolai Kondusov, Alexey Zaytsev· 0 citations
With European Union initiatives mandating gender quotas on corporate boards, a key question arises: Is greater board gender diversity (BGD) associated with better emissions performance (EP)? To answer this question, we examine the influence of BGD on EP across a sample of European firms from 2016 to 2022. Using panel r...
Mohammad Hassan Shakil, Arne Johan Pollestad, Khine Kyaw et al.· 0 citations
In contemporary cloud-based services, protecting users' sensitive data and ensuring the confidentiality of the server's model are critical. Fully homomorphic encryption (FHE) enables inference directly on encrypted inputs, but its practicality is hindered by expensive bootstrapping and inefficient approximations of non...
Sayan Biswas, Philippe Chartier, Akash Dhasade et al.· 0 citations
This work focuses on the finite-sample regime, quantifying how well a designer can approximate any point on the FA frontier from limited data and bounding the worst-case gap, and derives worst-case-optimal estimators that depend on the designer's knowledge of the covariate distribution.
Alireza Fallah, Michael I. Jordan, Annie Ulichney· arXiv.org· 2 citations
This work develops an epoch-based reinforcement learning algorithm for infinite-horizon average-cost MDPs with continuous state and action spaces that exploits this order through counterfactual inference and instantiates the framework in lost-sales inventory systems with positive lead times, dual-sourcing systems gover...
Zhongju Zhang, Shipra Agrawal, Ilan Lobel et al.· arXiv.org· 1 citation
Trustworthy robot behavior requires not only high levels of task success but also that the robot can reliably quantify how likely it is to succeed. To this end, we present a first-of-its-kind study of confidence calibration in vision-language-action (VLA) foundation models, which map visual observations and natural lan...
Handling missing values is a common challenge in biostatistical analyses, typically addressed by imputation methods. We propose a novel, fast, and easy-to-use imputation method called missing value imputation with adversarial random forests (MissARF), based on generative machine learning, that provides both single and...
Pegah Golchian, Jan Kapar, David S. Watson et al.· 0 citations
A machine-learning approach called CheMeleon provides a practical way to develop new drugs or other molecules with much less detailed, expensive experimentation.
Research Manager Mike Walker reflects on a career spanning hacker culture, cybersecurity, and AI, sharing lessons about trust, teamwork, leadership, and why solving difficult problems requires curiosity, judgment, agility—and an understanding of the rules. The post Learn the rules: The hacker mindset appeared first on Microsoft Research.
Learn how Google Antigravity and our Cheminformatics Skills accelerate drug discovery workflows, search compounds, and propose novel rigidified macrocycles.
MIT News · Artificial Intelligence· news.mit.eduOct 28, 2026
Professor Paris Smaragdis develops computers with superhuman hearing for applications like speech recognition, music understanding, and environmental monitoring.
MIT News · Artificial Intelligence· news.mit.eduOct 27, 2026
Prabha Jha used her experience with MIT Open Learning’s program for senior executives to develop AI solutions for her employer, Verizon, and to write a book.
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