Search: “research”

Surgical Anatomy Recognition with Context Learning using Foundation Representations

arXiv:2606.22124v1 Announce Type: new Abstract: Accurate recognition of anatomical structures is essential for safe and effective minimally invasive surgery (MIS), yet it remains underexplored in surg

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Research

Synthetic Network Packet Generation through Statistical Learning and Genetic Algorithms

DGX agent

arXiv:2606.20864v1 Announce Type: cross Abstract: Developing robust intrusion detection systems (IDS) for IoT environments requires large, labeled datasets capturing realistic traffic distributions ac

researcharxiv-cs-lg

23 Jun 2026

T-MOR: Learning Motion-Aware Skeleton Representations for Human Action Recognition

arXiv:2606.21607v1 Announce Type: new Abstract: Vision-language models such as CLIP have recently achieved strong performance on a wide range of visual understanding tasks. However, most existing mode

T-Rex: Tactile-Reactive Dexterous Manipulation

arXiv:2606.17055v2 Announce Type: replace Abstract: The ability to react dynamically to tactile signals has long been considered crucial to agile human-level dexterity. Yet contemporary learning-based

T-VSS: Test-Time Visual Subspace Steering for Adversarial Robustness of Vision-Language Models

arXiv:2606.23132v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot recognition, but they remain highly vulnerable to adversarial perturbations. Recent test-time ada

Task-Agnostic Federated Continual Learning via Replay-Free Gradient Projection

arXiv:2509.21606v3 Announce Type: replace Abstract: Federated continual learning (FCL) enables collaborative model training across distributed clients on sequentially arriving tasks without revisiting

Tensor Train Decomposition-based 3D Implicit Full Waveform Inversion with Multi-scale Structural Similarity

arXiv:2606.22867v1 Announce Type: cross Abstract: Three-dimensional full waveform inversion (3DFWI) is a powerful technique for reconstructing high-resolution subsurface velocity models. However, its

TF-SNO: Time-Frequency Gated Spectral Neural Operators for Learning Non-Stationary Partial Differential Equations

arXiv:2606.21189v1 Announce Type: new Abstract: Non-stationary partial differential equations (PDEs) arise throughout scientific computing, where the dominant frequency content and energy distribution

The $400 million machine powering the future of chipmaking

Jos Benschop is climbing a ladder to get to the top of his newest machine. It’s a bit of a schlep. The contraption is the size of a double-decker bus—more than 150 tons of gleaming precision-milled al

researchmit-tech-review

The Anatomy of the CTC Oracle Gap: Acoustic Exhaustion and Linguistic Recovery

arXiv:2606.23306v1 Announce Type: cross Abstract: We study the limits of CTC-internal scoring for N-best hypothesis selection and locate the information bottleneck separating acoustic confidence from

The Cost Geometry of Belief: finite-resource inference under noisy observation

arXiv:2606.21585v1 Announce Type: new Abstract: We equip the space of beliefs with a cost geometry (what it costs to pass from one belief to another): optimal transport in Wasserstein space, reweighte

The Download: the future of chipmaking and Anthropic’s government clash

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The $400 million machine powering the future of chipmaking It’

researchmit-tech-review

The Energy Consumption of Transformer Fine-Tuning: A Roofline-Inspired Scaling Model

arXiv:2606.23546v1 Announce Type: new Abstract: Transformer-based models underpin modern natural language processing but incur rapidly growing computational and energy costs. As training scales in bot

The First Assessment of PhiSat-2 Imagery for Monocular Building Height Estimation

arXiv:2603.29245v3 Announce Type: replace Abstract: Monocular building height estimation from optical imagery is important for characterizing urban vertical structure, yet remains challenging due to t

The Keras team is gonna be at the AI Systems DevLabs in Sunnvale tomorrow. Come say hi if you're around!

researchfrancois-chollet--x

François Chollet announced that members of the Keras team would be attending the AI Systems DevLabs event in Sunnyvale and invited people to meet them there. This post indicates a scheduled appearance

The Optimal Token Baseline: Variance Reduction for Long-Horizon LLM-RL

arXiv:2602.07078v2 Announce Type: replace Abstract: Reinforcement Learning (RL) for Large Language Models (LLMs) often suffers from training collapse in long-horizon tasks due to exploding gradient va

The Optimization Landscape of Caratheodory Decomposition of Toeplitz Covariances

arXiv:2511.01605v2 Announce Type: replace Abstract: Toeplitz covariance estimation is a classical problem in statistical signal processing, yet the geometry of the Gaussian maximum-likelihood objectiv

The Trilemma of Truth in Large Language Models

arXiv:2506.23921v5 Announce Type: replace-cross Abstract: The public often attributes human-like qualities to large language models (LLMs), assuming that they 'know' certain things. In reality, LLMs e

The Unreasonable Effectiveness of VLMs for Zero-shot Procedural Mistake Detection

arXiv:2606.21579v1 Announce Type: new Abstract: Procedural mistake detection is important for quality control and user assistance across many disciplines. Recent work in this field has achieved signif

ThermoLLM: Thermodynamics-Aware HVAC Control with Spatial-Semantic Knowledge Graph

arXiv:2606.22911v1 Announce Type: cross Abstract: Multi-zone HVAC control is a spatial decision problem in which indoor thermal evolution and control decisions depend not only on outdoor conditions an

TIDY: Thermal Infrared Image Denoising via Wavelet Domain Entropy and Directional Stripe Index

arXiv:2606.19813v1 Announce Type: cross Abstract: Thermal infrared (TIR) imaging has been a popular choice for field robotics due to its robust perception capability under low light visual degradation

TooBad: Backdoor Diffusion Models with Ultra-Low Poison Rate and Imperceptible Trigger

arXiv:2606.23362v1 Announce Type: cross Abstract: Diffusion models (DMs), despite their impressive capabilities across a wide range of generative tasks, have been shown to be vulnerable to backdoor at

Towards a Novel Wearable Robotic Vest for Hemorrhage Suppression

arXiv:2602.01448v2 Announce Type: replace Abstract: This paper introduces a novel robotic system designed to manage severe bleeding in emergency scenarios, including unique environments like space sta

Towards Accurate and Robust Surveillance Roadside IVD via Trackletized Audio-Visual Reasoning

arXiv:2606.22299v1 Announce Type: new Abstract: Idling Vehicle Detection (IVD) seeks to determine, at the final frame of a video clip, whether any vehicle is idling, meaning the vehicle is stationary

Towards CSI-Native Foundation Models: A Channel-Adaptive Roadmap for 6G

arXiv:2606.20670v1 Announce Type: new Abstract: Wireless foundation models offer a path toward reusable channel state information (CSI) intelligence for sixth-generation (6G) systems. However, existin

Towards Robust Training in NNGPT AutoML Pipeline: A Loss-Optimizer Pairing Selection Study

arXiv:2606.20933v1 Announce Type: new Abstract: The choice of loss function and optimizer is an important decision, that shapes further model training. Yet automated architecture search pipelines (Aut

Towards Understanding the Power and Limits of the Muon Optimizer: A River-Valley Perspective

arXiv:2606.21514v1 Announce Type: new Abstract: Recently, Muon has gained substantial attention as an appealing alternative to Adam-like optimizers, with many works highlighting its advantages through

TraceMark-LDM: Authenticatable Watermarking for Latent Diffusion Models via Binary-Guided Rearrangement

arXiv:2503.23332v2 Announce Type: replace Abstract: Image generation algorithms are increasingly integral to diverse aspects of human society, driven by their practical applications. However, insuffic

TriMotion: Modality-Agnostic Camera Control for Video Generation

arXiv:2606.20774v1 Announce Type: new Abstract: Camera motion control is essential for directing viewpoint changes in generative systems. However, existing methods typically condition the generation p

Trustworthy MRI Reconstruction via Bayesian Uncertainty Quantification with Sparsity Prior Models

arXiv:2606.17343v2 Announce Type: replace Abstract: We propose a novel Bayesian framework for joint image reconstruction and uncertainty quantification from compressed sensing magnetic resonance imagi

Turning Tabular Foundation Models into Graph Foundation Models

arXiv:2508.20906v3 Announce Type: replace Abstract: While foundation models have revolutionized fields such as natural language processing and computer vision, their potential in graph machine learnin

Model Releases

Two-Bridge: Exclusive Objectives and Extended Horizon StarCraft II Benchmark

model-releasesarxiv-cs-lg

arXiv:2603.06608v2 Announce Type: replace-cross Abstract: The research community lacks a middle ground between StarCraft II full game and its mini-games. The full-game's sprawling state-action space r

Two Layers of Instability in Causal Estimation

arXiv:2606.21185v1 Announce Type: cross Abstract: There is a precise sense in which drawing causal inferences from observational data is hard, even when identifiability is assumed. In particular, Robi

Ultra-Peripheral Collisions as a Nuclear-Structure Interferometer with Interpretable Multitask Deep Learning

arXiv:2606.23353v1 Announce Type: cross Abstract: Precise knowledge of nuclear structure is essential across fundamental physics, yet probing these structures is notoriously difficult. To address this

Uncertainty-Aware Domain Adaptation for Vitiligo Segmentation in Clinical Photographs

arXiv:2512.11791v2 Announce Type: replace Abstract: Accurately quantifying vitiligo extent in routine clinical photographs is crucial for longitudinal monitoring of treatment response. We propose a tr

Understanding Latent Flow Models for Tabular Data Synthesis: Targets, Paths, and Sampling

arXiv:2606.20878v1 Announce Type: new Abstract: Synthetic tabular data enables microdata sharing in regulated domains, yet deploying continuous-time generative models requires balancing analytical uti

Unified Motion-Action Modeling for Heterogeneous Robot Learning

arXiv:2606.16917v3 Announce Type: replace Abstract: We present Unified Motion-Action (UMA) Model, an approach that uses 3D object motion trajectories as a shared interface to bridge visuomotor control

UniFS: Unified Fast-to-Slow Hierarchical Architecture for Vision-Language-Action Models

arXiv:2606.22794v1 Announce Type: new Abstract: Mainstream Fast-Slow dual system vision-language-action models decouple a high-frequency action expert from a low-frequency vision-language model for ef

Universal Encoders for Modular Relational Deep Learning

arXiv:2606.21434v1 Announce Type: new Abstract: Relational Deep Learning (RDL) models multi-tabular databases as temporal heterogeneous graphs for end-to-end representation learning. While RDL is evol

Universal priors: solving empirical Bayes via Bayesian inference and pretraining

arXiv:2602.15136v2 Announce Type: replace-cross Abstract: We theoretically justify the recent empirical finding of [Teh et al., 2025] that a transformer pretrained on synthetically generated data achi

UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation

arXiv:2606.23503v1 Announce Type: new Abstract: Vision Transformers (ViT) dominate computer vision. However, their reliance on rigid patch projectors hinders transfer to Earth Observation (EO), where

Unlocking In-Context Learning in Audio-Language Models from Decentralized Medical Audio

arXiv:2606.23243v1 Announce Type: new Abstract: Clinical audio diagnosis in low-resource settings requires models that identify conditions from minimal examples without large annotated corpora. We pro

Unmasking LAION-5B: Age, Gender, Race, and Emotion Biases in Large-Scale Image Datasets

arXiv:2606.23204v1 Announce Type: new Abstract: Large-scale image-text datasets, such as LAION-5B, are foundational to modern AI systems, yet their vast scale and uncurated nature raise significant co

Unsupervised Disentanglement Without Compromises : How Functional Orthogonality Enforces Identifiability

arXiv:2606.21385v1 Announce Type: new Abstract: This paper explores unsupervised disentangled representation learning from a functional perspective. We define latent concepts as factors that influence

Unsupervised Susceptibility Distortion Correction of EPI without Calibration Scans via Image Translation-Based Registration

arXiv:2606.21588v1 Announce Type: cross Abstract: Functional magnetic resonance imaging (fMRI) utilizes echo-planar imaging (EPI) to capture blood-oxygen-level-dependent (BOLD) signals with high tempo

Industry

USAID funding was central to the creation of COVID-19

USAID funding was central to the creation of COVID-19 USAID funneled $53 million to EcoHealth Alliance, which funded coronavirus gain-of-function research at the Wuhan Institute of Virology. That rese

industryelon-musk--x

Variance-Tilted Diffusion Models for Diverse Sampling

arXiv:2606.22239v1 Announce Type: cross Abstract: Diffusion models are typically sampled independently, even when the downstream objective is to obtain a diverse set of candidates. We introduce a vari

Venice-H1: Failure-Aware Query Re-Ranking with Multi-Scale Grid Signatures for Referring Image Segmentation

arXiv:2606.22546v1 Announce Type: new Abstract: Modern Referring Image Segmentation (RIS) systems generate multiple candidate masks per expression but rely on a simple heuristic--typically the argmax