research

arXiv:2605.15421v1 Announce Type: new Abstract: In this study, we explore in depth a few under-studied topics at the intersection of uncertainty estimation and segmentation. Prior work has shown that

arXiv:2605.15894v1 Announce Type: cross Abstract: Rapid and accurate wildfire smoke severity assessment from satellite images is essential for emergency response, air quality modeling, and human healt

arXiv:2605.15285v1 Announce Type: cross Abstract: Derivative-Informed Operator Learning (DIOL), i.e. learning a (nonlinear) operator and its derivatives, is an open research frontier at the foundation

arXiv:2605.16230v1 Announce Type: cross Abstract: Magnetic order is a fundamental property of materials, governing collective behavior and enabling a broad range of functionalities. Yet magnetic struc

arXiv:2601.21028v2 Announce Type: replace-cross Abstract: AI-generated media is radically changing the way content is both consumed and produced on the internet, and in no place is this potentially mo

arXiv:2605.15583v1 Announce Type: new Abstract: We propose a method of estimating a 3D human pose from a single view without 3D supervision. The key to our method is to leverage the 2D diffusion prior

arXiv:2605.15920v1 Announce Type: cross Abstract: We developed a tool for detecting domain shifts, namely subtle differences in the probability distributions of datasets. We identify these shifts usin

arXiv:2605.16020v1 Announce Type: new Abstract: Monte Carlo methods are essential across diverse scientific fields, yet their efficiency is frequently hampered by critical slowing down-a sharp increas

arXiv:2511.03606v2 Announce Type: replace-cross Abstract: The study of self-normalized processes plays a crucial role in a wide range of applications, from sequential decision-making to econometrics.

arXiv:2508.03810v4 Announce Type: replace-cross Abstract: Neural Network (NN) architectures that break statistical independence of parameters have been proposed as a new approach for simulating local

arXiv:2504.05451v2 Announce Type: replace Abstract: Traditional methods for view-invariant learning rely on controlled multi-view training data with minimal scene clutter. However, they struggle with

arXiv:2504.21850v3 Announce Type: replace Abstract: Visual instruction tuning (VIT) datasets have grown rapidly in scale, yet the informativeness of individual training samples has largely been overlo

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. When Google opens its doors tomorrow for its annual developer

arXiv:2602.04003v3 Announce Type: replace Abstract: Most adversarial threats in artificial intelligence (AI) target the computational behavior of models rather than the humans who rely on them. Yet mo

arXiv:2605.15484v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) networks promise favorable accuracy-compute trade-offs, yet practical vision deployments are hindered by expert collapse and li

arXiv:2605.15440v1 Announce Type: new Abstract: Surprisal theory posits that the processing difficulty of a word is determined by its predictability in context, offering a potential link between human

Witchcraft is a Rust reimplementation of Stanford's XTR-Warp semantic search engine that uses a single-file SQLite database for storage, enabling client-side deployment. The system operates completely

Appreciate it when the AI doomer crowd occasionally lets the mask slip a little (Allen is a co-founder of the anti-AI group Humans First and frequent guest on conservative podcasts pushing, uh, Unabom

This post reflects on how Pixar films resonate differently with adults, particularly uncles, compared to children, suggesting that mature viewers gain deeper emotional appreciation for themes of respo

The power of Trump, Putin, and Netanyahu appears to be waning. 'Plummeting approval ratings for these three poisonous comrades-in-arms show voters are demoralized and tiring of forever wars.' https://

The salvation is Project Tapestry https://thealliance.ai/projects/tapestry I don't think people understand just how bad it will be if an American open source champion doesn't emerge soon and the big l

The Top AI Papers of the Week (May 11 - May 17) - AEvo - δ-mem - AutoTTS - AI Co-Mathematician - Lighthouse Attention - Is Grep All You Need? - A Geometric Calculator Inside a Neural Network Read on f

1/3 My time at Meta FAIR will soon come to a close. I joined nearly two years ago full-time to help advance LLM reasoning. It has been a remarkable journey working with and leading an exceptionally ta

I cannot provide a reliable summary for this entry. The title appears to be a social media post containing political rhetoric rather than factual information suitable for a knowledge base. Without acc

I don’t know why data centers have become this generations nuclear power. Unlike nuclear power, there is a 0% chance that a data center can lead to any sort of disaster scenario. This project in Utah

I just learned that the 'data centers are using our water!' bullshit started because of a book called Empire of AI by Karen Hao in which she totally fucks up the math when determining how much water t

If you're not obsessed with the research problem you're working on, for its own sake, you're unlikely to succeed. Intrinsic motivation is far more powerful than external rewards. An Econ PhD student a

KDD 2026 Cycle 2 Results covers the announcement of review decisions and outcomes from the second submission cycle of KDD 2026, which accepts papers across multiple tracks including Research, Applied

Trump disparages the European Union as a collective force against the United States, but his threats, tariffs, and arbitrary conduct have done more than anything else in recent years to unify Europe.

arXiv:2304.03641v4 Announce Type: replace-cross Abstract: Nonsmooth composite optimization with orthogonality constraints has a wide range of applications in statistical learning and data science. How

arXiv:2605.14949v1 Announce Type: new Abstract: Carotid atherosclerosis is a major contributor to ischemic stroke and transient ischemic attack. Conventional ultrasound assessment is commonly based on

arXiv:2605.14360v1 Announce Type: cross Abstract: Wearable devices capture physiological and behavioral data with increasing fidelity, but the psychological context shaping these outcomes is difficult

arXiv:2605.14929v1 Announce Type: new Abstract: Scaled Outer Product (SOP) is a post-training quantization methodology for large language model weights, designed to deliver near-lossless fidelity at 4

arXiv:2605.14802v1 Announce Type: new Abstract: Large language models often suffer from fact loss, timeline confusion, persona drift, and reduced stability during long-range interaction, especially un

arXiv:2605.13858v1 Announce Type: cross Abstract: Large Language Models have demonstrated remarkable capabilities in generating contextually relevant and grammatically correct text. However, they fund

arXiv:2605.14917v1 Announce Type: new Abstract: Active learning for continuous regression has lacked an acquisition function that targets epistemic uncertainty when the predictive distribution is mult

arXiv:2605.14860v1 Announce Type: cross Abstract: Training deep neural networks at scale can benefit from domain decomposition, where the network is split into subdomains trained in parallel and coupl

arXiv:2605.14426v1 Announce Type: cross Abstract: Reliable precipitation monitoring is essential for disaster risk reduction, water resources management, and agricultural decision-making. Multi-source

arXiv:2605.14147v1 Announce Type: new Abstract: Objective: The primary goal of this study was to systematically examine the impact of commonly used imbalance handling methods (IHMs) on predictive perf

arXiv:2605.13943v1 Announce Type: new Abstract: Contrastive learning (CL) aims to preserve relational structure between samples by learning representations that reflect a similarity graph. Yet, the ge

arXiv:2602.05319v3 Announce Type: replace Abstract: Sequential probabilistic inference from streaming observations requires modeling distributions over future trajectories as new observations arrive.

arXiv:2605.14983v1 Announce Type: cross Abstract: An index is a function that given an election outputs a value between 0 and 1, indicating the extent to which this election has a particular feature.

arXiv:2605.14761v1 Announce Type: new Abstract: Accurately predicting individual aesthetic evaluation for images is a fundamental challenge for AI. Various deep learning (DL)-based models have been pr

arXiv:2605.14327v1 Announce Type: cross Abstract: Drug-drug interaction (DDI) prediction is a critical task in computational biomedicine, as adverse interactions between co-administered drugs can caus

arXiv:2605.14584v1 Announce Type: cross Abstract: Implicit solvent models are widely used to decrease the number of solvent degrees of freedom and enable the calculation of solvation energetics withou

America is eating its young. We’re a nation built on the greatness of our research universities, it’s what gave us the Manhattan Project, victory in the Cold War, over HIV/AIDS. Our future depends on