research

Sketch2MinSurf: Vision-Language Guided Generation of Editable Minimal Surfaces from Hand-Drawn Sketches

arXiv:2605.20733v1 Announce Type: new Abstract: Converting hand-drawn sketches into structured 3D geometries remains challenging due to the difficulty of representing non-Euclidean surfaces and mainta

Research

Smarter edits? Post-editing with error highlights and translation suggestions

DGX agent

arXiv:2605.21135v1 Announce Type: new Abstract: As MT quality increases, interest in enhanced post-editing features such as QE-derived error highlights is growing, yet evidence for their usefulness re

researcharxiv-cs-cl

21 May 2026

SmoCap: Unified Scale-Pose Canonicalization with Proxy-Mapped Trust-Region QP

arXiv:2605.20850v1 Announce Type: new Abstract: Objective: Stage-wise workflows that separate model scaling and inverse kinematics can induce morphology-posture compensation, resulting in anatomically

researcharxiv-cs-ro

SPARC: Spatial-Aware Path Planning via Attentive Robot Communication

arXiv:2603.02845v3 Announce Type: replace Abstract: Efficient communication is critical for decentralized Multi-Robot Path Planning (MRPP), yet existing learned communication methods treat all neighbo

researcharxiv-cs-ro

SpectralEarth-FM: Bringing Hyperspectral Imagery into Multimodal Earth Observation Pretraining

arXiv:2605.21075v1 Announce Type: new Abstract: Earth observation (EO) foundation models (FMs) are increasingly trained on multisensor data, spanning multispectral imagery (MSI), synthetic aperture ra

SR-Ground: Image Quality Grounding for Super-Resolved Content

arXiv:2605.21244v1 Announce Type: new Abstract: Super-Resolution (SR) has advanced rapidly in recent years, with diffusion-based models achieving unprecedented fidelity at the cost of introducing new

Stimulus symmetries can confound representational similarity analyses

arXiv:2605.21324v1 Announce Type: cross Abstract: What can representational similarity matrices (RSMs) tell us about a neural code? As the popularity of these summary statistics grows, so too does the

Strategy-Induct: Task-Level Strategy Induction for Instruction Generation

arXiv:2605.20924v1 Announce Type: new Abstract: Designing effective task-level prompts is crucial for improving the performance of Large Language Models (LLMs). While prior work on instruction inducti

StreamGVE: Training-Free Video Editing via Few-Step Streaming Video Generation

arXiv:2605.21466v1 Announce Type: new Abstract: Although existing video editing methods are generally feasible, they often require many costly iterations and still struggle to deliver high-quality yet

Sutra: Tensor-Op RNNs as a Compilation Target for Vector Symbolic Architectures

arXiv:2605.20919v1 Announce Type: new Abstract: Sutra is a typed, purely functional programming language whose compiled forward pass is a PyTorch neural network. The compiler beta-reduces the whole pr

Symmetrization of Loss Functions for Robust Training of Neural Networks in the Presence of Noisy Labels

arXiv:2605.20347v1 Announce Type: new Abstract: Labeling a training set is often expensive and susceptible to errors, making the design of robust loss functions for label noise an important problem. T

TabPFN-MT: A Natively Multitask In-Context Learner for Tabular Data

arXiv:2605.20234v1 Announce Type: new Abstract: Prior-Data Fitted networks (PFNs) have been very successful in tabular contexts, handling prediction tasks in context. However, they are designed for si

Temporal Counterfactual Explanations of Behaviour Tree Decisions

arXiv:2509.07674v2 Announce Type: replace Abstract: Explainability, in particular, the ability for robots to explain why they have made a decision or behaved in a certain way, is a critical tool in he

researcharxiv-cs-ro

Testing Support Size More Efficiently Than Learning Histograms

arXiv:2410.18915v4 Announce Type: replace-cross Abstract: Consider two problems about an unknown probability distribution p: 1. How many samples from p are required to test if p is supported on n elem

TextReg: Mitigating Prompt Distributional Overfitting via Regularized Text-Space Optimization

arXiv:2605.21318v1 Announce Type: new Abstract: Large language models (LLMs) are highly sensitive to the prompts used to specify task objectives and behavioral constraints. Many recent prompt optimiza

The Devil is in the Condition Numbers: Why is GLU Better than non-GLU Structure?

arXiv:2605.20749v1 Announce Type: new Abstract: Gated Linear Units (GLU) and their variants are widely adopted in modern open-source large language model architectures and consistently outperform thei

The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering

arXiv:2605.20745v1 Announce Type: cross Abstract: Generative verifiers have emerged as a promising paradigm for step-wise verification, but their verification behavior is often poorly calibrated: they

The new issue of Daedalus, the open-access Journal of the American Academy of Arts and Sciences, is chock full of good material on AI. w/@de…

The new issue of Daedalus, the open-access Journal of the American Academy of Arts and Sciences, is chock full of good material on AI. w/@demishassabis @ylecun @alondra @pushmeet and so many others I

Thinking-while-speaking: A Controlled, Interleaved Reasoning Method for Real-Time Speech Generation

arXiv:2605.20946v1 Announce Type: new Abstract: The thinking-while-speaking paradigm aims to make AI communication more human. A key challenge is maintaining fluent speech while performing deep reason

This New York Times piece is worth your time. Here’s what is happening, as simply as I can put it. Back in January, Trump sued the IRS, an a…

This New York Times piece is worth your time. Here’s what is happening, as simply as I can put it. Back in January, Trump sued the IRS, an agency he controls, demanding 10 billion over the leak of his

This New York Times piece on the January 6th slush fund is worth your time. Here’s what is happening, as simply as I can put it. Back in Jan…

This New York Times piece on the January 6th slush fund is worth your time. Here’s what is happening, as simply as I can put it. Back in January, Trump sued the IRS, an agency he controls, demanding 1

Tiny-Engram: Trigger-Indexed Concept Tables for Generative Vision

arXiv:2605.20309v1 Announce Type: new Abstract: Current personalization methods for generative vision models typically encode new concepts through continuous adapters or weight updates, yet provide li

torchtune: PyTorch native post-training library

arXiv:2605.21442v1 Announce Type: new Abstract: Modern LLMs typically require multistage training pipelines to achieve strong downstream performance, with post-training serving as the main interface f

Towards Integrated Rock Support Visualisation in 3D Point Cloud of Underground Mines

arXiv:2605.20973v1 Announce Type: new Abstract: The effectiveness of rock support in underground mines depends on the interaction between installed rock bolts and the structural fabric of the surround

Tracing the ongoing emergence of human-like reasoning in Large Language Models

arXiv:2605.21299v1 Announce Type: new Abstract: Humans effortlessly go beyond literal meanings: If you mow the lawn, I will give you fifty dollars, is typically understood as implying that the speaker

TreeText-CTS: Compact, Source-Traceable Tree-Path Evidence for Irregular Clinical Time-Series Prediction

arXiv:2605.20292v1 Announce Type: new Abstract: Numerical time-series models can effectively process irregular electronic health record (EHR) trajectories, but they do not naturally expose the measure

TriForces: Augmenting Atomistic GNNs for Transferable Representations

arXiv:2605.20581v1 Announce Type: new Abstract: Machine learning interatomic potentials (MLIPs) achieve excellent accuracy when trained on large Density Functional Theory (DFT) data. To be useful in p

Trump’s latest corruption seems to breach the constitution, creating a $1.8 billion slush fund for his friends without congressional authori…

Trump’s latest corruption seems to breach the constitution, creating a $1.8 billion slush fund for his friends without congressional authorization and effectively pardoning himself by stopping IRS aud

Trump’s use of taxpayer money to create a $1.8 billion political slush fund may be the episode of presidential corruption that is the most b…

Trump’s use of taxpayer money to create a $1.8 billion political slush fund may be the episode of presidential corruption that is the most blatant and threatening to the constitutional order in modern

Uncertainty-Guided Conservative Propagation for Structured Inference in Vessel Segmentation

arXiv:2605.20543v1 Announce Type: new Abstract: Accurate vessel segmentation is essential for medical image analysis, yet remains challenging due to complex vascular patterns and imaging ambiguity. Mo

Understanding Model Behavior in Monocular Polyp Sizing

arXiv:2605.20461v1 Announce Type: new Abstract: Accurate polyp size stratification guides surveillance decisions, with lesions larger than 5 mm typically requiring closer follow-up. However, monocular

Uni-Edit: Intelligent Editing Is A General Task For Unified Model Tuning

arXiv:2605.21487v1 Announce Type: new Abstract: Currently, enhancing Unified Multimodal Models (UMMs) with image understanding, generation, and editing capabilities mainly relies on mixed multi-task t

UniEdit-Flow: Unleashing Inversion and Editing in the Era of Flow Models

arXiv:2504.13109v2 Announce Type: replace Abstract: Flow matching models have emerged as a strong alternative to diffusion models, but existing inversion and editing methods designed for diffusion are

UniT: Unified Geometry Learning with Group Autoregressive Transformer

arXiv:2605.21131v1 Announce Type: new Abstract: Recent feed-forward models have significantly advanced geometry perception for inferring dense 3D structure from sensor observations. However, its essen

Unsupervised clustering and classification of upper limb EMG signals during functional movements: a data-driven

arXiv:2605.20599v1 Announce Type: new Abstract: This study presents a comprehensive approach for the clustering and classification of upper-limb surface electromyography (sEMG) signals during function

UOTIP: Unbalanced Optimal Transport Map for Unpaired Inverse Problems

arXiv:2605.21094v1 Announce Type: new Abstract: We investigate unpaired image inverse problems, a challenging setting where only independent, non-paired sets of noisy measurements and clean target sig

USV: Towards Understanding the User-generated Short-form Videos

arXiv:2605.20838v1 Announce Type: new Abstract: Several large-scale video datasets have been published these years and have advanced the area of video understanding. However, the newly emerged user-ge

Variance Reduction for Expectations with Diffusion Teachers

arXiv:2605.21489v1 Announce Type: cross Abstract: Pretrained diffusion models serve as frozen teachers feeding downstream pipelines such as text-to-3D, single-step distillation, and data attribution.

Vega: Zero-knowledge proofs for digital identity in the age of AI

researchmicrosoft-research

Vega turns a full credential into a single proof, sharing only what is needed and nothing more, with performance that works in real apps. The post Vega: Zero-knowledge proofs for digital identity in t

VIHD: Visual Intervention-based Hallucination Detection for Medical Visual Question Answering

arXiv:2605.20772v1 Announce Type: new Abstract: While medical Multimodal Large Language Models (MLLMs) have shown promise in assisting diagnosis, they still frequently generate hallucinated responses

Weasel: Out-of-Domain Generalization for Web Agents via Importance-Diversity Data Selection

arXiv:2605.20291v1 Announce Type: new Abstract: Large language models (LLMs) have enabled web agents that follow natural language goals through multi-step browser interactions. However, agents fine-tu

What we find most useful about this study is the decomposition. For byte-level pretraining, the ordering is throughput first and boundary si…

What we find most useful about this study is the decomposition. For byte-level pretraining, the ordering is throughput first and boundary signal second; the boundary benefit can be recovered without a

researchnous-research--x

When Does Adaptation Win? Scaling Laws for Meta-Learning in Quantum Control

arXiv:2601.18973v4 Announce Type: replace Abstract: Quantum hardware suffers from intrinsic device heterogeneity and environmental drift, forcing practitioners to choose between suboptimal non-adaptiv

When Reasoning Supervision Hurts: TTCW-Based Long-Form Literary Review Generation

arXiv:2605.20364v1 Announce Type: new Abstract: Automatic evaluation of long-form literary writing remains challenging, as generic LLM-as-Judge approaches may not fully capture creativity-related dime

Whenever an AI tells me I'm absolutely right, my trust in it drops by a bit

researchfrancois-chollet--x

Francois Chollet observes that AI systems which always affirm user correctness without nuance or disagreement reduce his confidence in their reliability. This reflects a concern that uncritical agreem

You Are What You Say: Exploiting Linguistic Content for VoicePrivacy Attacks

arXiv:2506.09521v2 Announce Type: replace-cross Abstract: Speaker anonymization systems hide the identity of speakers while preserving other information such as linguistic content and emotions. To eva

3D aperture-engineered diffractive neural networks for super-resolution electromagnetic wave computing

arXiv:2603.00995v2 Announce Type: replace-cross Abstract: The rapid progress in 6G communication and high-bandwidth radar has driven an unprecedented surge in the spatial density of signal sources, re

researcharxiv-cs-ai

20 May 2026

3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion

arXiv:2404.07106v2 Announce Type: replace Abstract: Point cloud completion aims to generate a complete and high-fidelity point cloud from an initially incomplete and low-quality input. A prevalent str