research

EEG-FM-Audit: A Systematic Evaluation and Analysis Pipeline for EEG Foundation Models

arXiv:2605.26910v1 Announce Type: cross Abstract: Large EEG Foundation Models (FMs) have shown great potential for decoding EEG signals across diverse cognitive tasks. However, existing EEG-FM studies

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Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNN

DGX agent

arXiv:2210.02573v5 Announce Type: replace Abstract: Learning the physical simulation on large-scale meshes with flat Graph Neural Networks (GNNs) and stacking Message Passings (MPs) is challenging due

researcharxiv-cs-lg

27 May 2026

Emergent Causal-Geometric Dynamics Across Depth in Large Language Models

arXiv:2602.04931v2 Announce Type: replace-cross Abstract: Geometric analyses of large language model (LLM) representations reveal structured variation across depth but remain fundamentally correlation

Energy-Gated Attention and Wavelet Positional Encoding: Complementary Inductive Biases for Transformer Attention

arXiv:2605.26355v1 Announce Type: cross Abstract: Standard transformer attention computes pairwise token similarity but treats all tokens as equally salient and all positions as equally local, regardl

Equivariant Filter for Relative Attitude and Target's Angular Velocity Estimation

arXiv:2506.06016v3 Announce Type: replace-cross Abstract: Accurate estimation of the relative attitude and angular velocity between two rigid bodies is fundamental in aerospace applications such as sp

researcharxiv-cs-ro

Eroding Trust in Real Speech: A Large-Scale Study of Human Audio Deepfake Perception

arXiv:2605.26136v1 Announce Type: cross Abstract: Audio deepfakes have improved rapidly recently, yet their effect on human trust in real speech remains unstudied. We present the largest listening stu

Error Analysis of Discrete Flow with Generator Matching

arXiv:2509.21906v3 Announce Type: replace-cross Abstract: Discrete flow models offer a powerful framework for learning distributions over discrete state spaces and have demonstrated superior performan

ESMFold2 is a state of the art folding model. It's crazy good. The -Fast model does better on antibody-antigen complexes than AF3 with MSAs.

ESMFold2 is described as a high-performance protein structure prediction model that demonstrates particular strength in predicting antibody-antigen complex structures, reportedly outperforming AlphaFo

Evaluating the Relevance of Uncertainty Estimators for LLM Hallucination

arXiv:2605.27016v1 Announce Type: cross Abstract: Large language models (LLMs) are prone to hallucinations, i.e., statements unsupported by the input or training data, hindering reliable deployment. I

Evidence Absence Is Not Evidence Insufficiency: Diagnosing NEI Construction Artifacts in Fact Verification

arXiv:2605.26663v1 Announce Type: new Abstract: Evidence absence is not evidence insufficiency, but fact verification benchmarks can make them observationally similar. The Not Enough Information (NEI)

Explainable Comparison of Feature-Based and Deep Learning Models for TROPOMI Methane Plume Screening

arXiv:2605.27236v1 Announce Type: new Abstract: Continuous and global detection of large methane emissions is a crucial step for global warming mitigation. Satellite observations, such as from S5P/TRO

Exploring the robustness of TractOracle methods in RL-based tractography

arXiv:2507.11486v2 Announce Type: replace Abstract: Tractography algorithms leverage diffusion MRI to reconstruct the fibrous architecture of the brain's white matter. Among machine learning approache

ExTax: Explainable Disinformation Detection via Persuasion, Emotion, and Narrative Role Taxonomies

arXiv:2605.27045v1 Announce Type: new Abstract: The democratization of LLMs has accelerated the generation and circulation of highly fluent disinformation, making traditional syntax-semantic verificat

Extending Human Intelligence Through AI

researchmicrosoft-research

Understanding AI as an extension of human intelligence—not a replacement for it—offers a more grounded path for building trustworthy AI systems. The post Extending Human Intelligence Through AI appear

First of all, all of this is open sourced. Even the binder design protocol [coming soon], which has been rigorously experimentally validated…

First of all, all of this is open sourced. Even the binder design protocol [coming soon], which has been rigorously experimentally validated. Paper: https://biohub.ai/papers/esm_protein.pdf 🤗: https:/

FluxNet: Learning Capacity-Constrained Local Transport Operators for Conservative and Bounded PDE Surrogates

arXiv:2602.01941v2 Announce Type: replace-cross Abstract: Autoregressive learning of time-stepping operators provides an effective approach to data-driven partial differential equation (PDE) simulatio

For over a decade, we’ve accepted that end-to-end backprop is the only way to train deep networks. But holding the entire network in memory …

For over a decade, we’ve accepted that end-to-end backprop is the only way to train deep networks. But holding the entire network in memory all at once is why AI training is hitting a resource wall. W

researchdavid-ha--x

Formalization of Malagasy conjugation

arXiv:2605.27161v1 Announce Type: new Abstract: This paper reports the core linguistic work performed to construct a dictionary-based morphological analyser for Malagasy simple verbs. It uses the Unit

Frequency-Guided Fusion For RGB-Thermal Semantic Segmentation

arXiv:2605.26273v1 Announce Type: new Abstract: Semantic segmentation in complex environments such as urban driving scenes remains challenging under adverse lighting conditions, where RGB images alone

From Contrast to Consistency: Rethinking Event-based Continuous-Time Optical Flow Estimation

arXiv:2605.25570v2 Announce Type: replace Abstract: Estimating continuous optical flow is a fundamental yet challenging problem in dynamic visual perception. Event-based cameras, with microsecond late

From Privacy to Generalization: Linear Max-Information Bounds for DP-SGD

arXiv:2605.26222v1 Announce Type: new Abstract: Understanding the relationship between generalization and privacy remains a central challenge in modern machine learning theory, particularly for deep n

From Scores to Gibbs Correctors: Accelerating Uniform-Rate Discrete Diffusion Models

arXiv:2605.27352v1 Announce Type: new Abstract: Discrete diffusion models have achieved strong empirical performance in text and other symbolic domains, but, especially for uniform-rate models, they o

From Snippets to Semantics: Rethinking Evidence Granularity for Multilingual Fact Verification

arXiv:2605.26755v1 Announce Type: new Abstract: Multilingual fact verification requires evidence that is both relevant and sufficiently complete for reliable factuality prediction. However, existing s

FUCK YEAHHHHHH ANTHROPIC IS NO LONGER DOOMING ABOUT JOBS!!!!! ♥️♥️♥️

I can't provide a summary for this entry as the source URL appears to be invalid (the timestamp format doesn't match actual X/Twitter posts) and the title itself doesn't convey substantive information

GAC: Noise-Aware Adaptive Mixing for Hybrid SFT-RL Post-Training

arXiv:2605.26184v1 Announce Type: cross Abstract: Hybrid post-training usually combines supervised fine-tuning and reinforcement learning, but fixed mixing schedules cannot adapt when the relative noi

Garment Particles: A 2D--3D Symmetric Garment Representation for Generation and Editing

arXiv:2605.26391v1 Announce Type: cross Abstract: Practical garment design spans two modes: intuitive creation from high-level intent, such as a reference image or text description, and complex low-le

Generating realistic global precipitation fields from modelled atmospheric circulation

arXiv:2504.00307v2 Announce Type: replace Abstract: Improving the representation of precipitation in Earth system models (ESMs) is critical for assessing the impacts of climate change and especially o

Generating Robust Portfolios of Optimization Models using Large Language Models

arXiv:2605.27013v1 Announce Type: new Abstract: Mathematical optimization is a powerful tool for structured decision-making across domains such as resource allocation and planning. Formulating optimiz

Genre Controlled Music Generation via Activation Steering

arXiv:2506.10225v2 Announce Type: replace-cross Abstract: Computational Music Generation is evolving towards non-conventional styles, demanding methods that enable precise and controllable blending of

Geometrically Constrained Outlier Synthesis

arXiv:2603.08413v2 Announce Type: replace-cross Abstract: Deep neural networks for image classification often exhibit overconfidence on out-of-distribution (OOD) samples. To address this, we introduce

Geometry-Aware Contrastive Learning for Few-Shot Automatic Modulation Recognition

arXiv:2605.26600v1 Announce Type: cross Abstract: Standard Self-Supervised Learning (SSL) for Automatic Modulation Recognition (AMR) struggles with ineffective isotropic augmentations, spectral instab

Get a state of the art protein structure prediction in just 9 lines of code. No MSAs needed.

Get a state of the art protein structure prediction in just 9 lines of code. No MSAs needed. I'm so excited to show the world what we've been working on the for the past months!! I'm going to highligh

Global Structure-from-Motion Meets Feedforward Reconstruction

arXiv:2605.26103v2 Announce Type: replace Abstract: Structure-from-Motion -- the process of simultaneously estimating camera poses and 3D scene structure from a collection of images -- remains a centr

Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering

arXiv:2605.26620v1 Announce Type: new Abstract: Natural language conveys information at varying levels of granularity, from fine-grained references to broad descriptions. While granularity is fundamen

Graph is a Substrate Across Data Modalities

arXiv:2601.22384v2 Announce Type: replace-cross Abstract: Graphs provide a natural representation of relational structure that arises across diverse domains. Despite this ubiquity, graph structure is

GraphReview: Scientific Paper Evaluation via LLM-Based Graph Message Passing

arXiv:2605.27204v1 Announce Type: new Abstract: Scientific paper evaluation often involves not only assessing a manuscript itself, but also relating it to contemporaneous research and prior literature

Greening AI Inference with Accuracy and Latency-aware User Incentives

arXiv:2605.27309v1 Announce Type: new Abstract: The widespread use of AI services has raised concerns for its environmental sustainability, towards which recent studies have identified carbon emission

GS-CLIP: Zero-shot 3D Anomaly Detection by Geometry-Aware Prompt and Synergistic View Representation Learning

arXiv:2602.19206v3 Announce Type: replace Abstract: Zero-shot 3D Anomaly Detection is an emerging task that aims to detect anomalies in a target dataset without any target training data, which is part

GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL

arXiv:2602.22190v2 Announce Type: replace-cross Abstract: Open-source native GUI agents still lag behind closed-source systems on long-horizon navigation tasks. This gap stems from two limitations: a

Guiding LLM Post-training Data Engineering with Model Internals from Sparse Autoencoders

arXiv:2605.27354v1 Announce Type: cross Abstract: Model internals encode rich information about how a large language model (LLM) processes its training data; however, post-training data engineering la

Gumbel Machine: Counterfactual Student Writing Generation via Gumbel Noise Steering

arXiv:2605.27249v1 Announce Type: new Abstract: An effective method of teaching across disciplines is to provide examples of high-quality work. However, an example may be significantly different from

High-Quality Synthetic Financial Time-Series using a GAN-Diffusion Framework

arXiv:2605.27113v1 Announce Type: cross Abstract: In recent years, financial institutions and firms have increasingly adopted synthetic data to address data scarcity and to generate counterfactual mar

HiSpec: Hierarchical Speculative Decoding for LLMs

arXiv:2510.01336v2 Announce Type: replace-cross Abstract: Speculative decoding accelerates LLM inference by using a smaller draft model to speculate tokens that a larger target model verifies. Verific

HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection

arXiv:2605.26421v1 Announce Type: new Abstract: The rapid evolution of generative models has precipitated a proliferation of fabricated content, posing significant challenges to existing Synthetic Ima

ICICLE: Expanding Retrieval with In-Context Documents

arXiv:2605.26902v1 Announce Type: cross Abstract: Generative retrieval (GR) maps queries directly to document identifiers (docids) using parametric knowledge, However, this design makes corpus expansi

If you have been experiencing issues with OpenAI Codex oAuth, it is now fixed. OpenAI has been fixing it in the background and then seemed t…

If you have been experiencing issues with OpenAI Codex oAuth, it is now fixed. OpenAI has been fixing it in the background and then seemed to change their whole spec today to solve it, you must `herme

researchnous-research--x

Image Feature Fusion-based Federated Client Unlearning (FCU)

arXiv:2605.26715v1 Announce Type: new Abstract: Major data protection regulations all mention the 'right to be forgotten,' and that's what pushed federated unlearning (FU) techniques forward. But one

Inference-Time Search Using Side Information for Diffusion-Based Image Reconstruction

arXiv:2510.03352v3 Announce Type: replace-cross Abstract: Diffusion models have been used as priors for solving inverse problems. However, existing approaches typically overlook side information that