research

We saw our first meaningful jump in the ARC-AGI-3 competition today @tufalabs went from 0.68% > 1.17% My notes: - .68% is the score of the b…

researchfrancois-chollet--x

We saw our first meaningful jump in the ARC-AGI-3 competition today @tufalabs went from 0.68% > 1.17% My notes: - .68% is the score of the best template (which is why so many people have this score) -

22 May 2026

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When Shared Knowledge Hurts: Spectral Over-Accumulation in Model Merging

DGX agent

arXiv:2602.05536v2 Announce Type: replace-cross Abstract: Model merging combines multiple fine-tuned models into a single model by adding their weight updates, providing a lightweight alternative to r

researcharxiv-cs-cl

22 May 2026

Whose Voice Counts? Mapping Stakeholder Perspectives on AI Through Public Submissions to the U.S. Government

arXiv:2605.22650v1 Announce Type: new Abstract: As artificial intelligence (AI) systems become more common in our daily lives, it is important to understand how different stakeholders comprehend and e

22 May 2026

Zero-Shot Temporal Action Localization Through Textual Guidance

arXiv:2605.22201v1 Announce Type: new Abstract: Zero-shot temporal action localization (ZS-TAL) consists of classifying and localizing actions in untrimmed videos, where action classes are unseen at t

22 May 2026

A Comprehensive Comparison of Deep Learning Architectures for COVID-19 Classification on CT & X-ray Imagery

arXiv:2605.20445v1 Announce Type: new Abstract: COVID-19 was a significant challenge that led to the loss of numerous lives daily. Not only a certain country was involved in this outbreak, but even th

A Dialogue between Causal and Traditional Representation Learning: Toward Mutual Benefits in a Unified Formulation

arXiv:2605.21058v1 Announce Type: new Abstract: Causal representation learning (CRL) and traditional representation learning have largely developed along different trajectories. Traditional representa

A Human-in-the-Loop Framework for Efficient Prompt Selection in Microscopy Vision-Language Models

arXiv:2605.20495v1 Announce Type: new Abstract: Deep-learning pipelines for microscopy image classification often require expensive, labor- and time-intensive expert annotation to produce high-quality

A Mechanistic Study of Tabular Foundation Models

arXiv:2605.21288v1 Announce Type: new Abstract: Tabular foundation models with different architectures converge in accuracy across a range of classification and regression tasks. This raises questions

A Non-Reference Diffusion-Based Restoration Framework for Landsat 7 ETM+ SLC-off Imagery in Antarctica

arXiv:2605.21371v1 Announce Type: new Abstract: Acquiring usable optical imagery in Antarctica is inherently challenging due to prolonged polar nights and frequent cloud cover. Landsat provides the lo

A Rigorous, Tractable Measure of Model Complexity

arXiv:2605.21167v1 Announce Type: cross Abstract: An accurate assessment of a model's complexity is crucial for topics such as interpretation, generalization, and model selection. However, most existi

A Sharper Picture of Generalization in Transformers

arXiv:2605.20988v1 Announce Type: new Abstract: We study transformers' generalization behavior on boolean domains from the perspective of the Fourier Spectra of their target functions. In contrast to

A Terrain-Adaptive epsilon-Constraint MPC for Uneven Terrain Kinodynamic Planning

arXiv:2605.21188v1 Announce Type: new Abstract: Kinodynamic planning for car-like vehicles on uneven terrain requires simultaneously optimizing competing objectives such as path efficiency and pose st

researcharxiv-cs-ro

A Typed Tensor Language for Federated Learning

arXiv:2605.21103v1 Announce Type: new Abstract: Federated learning and analytics are often described as collections of separate protocols, even when they share the same mathematical form: client-local

Activation-Free Backbones for Image Recognition: Polynomial Alternatives within MetaFormer-Style Vision Models

arXiv:2605.20839v1 Announce Type: new Abstract: Modern vision backbones treat pointwise activations (e.g., ReLU, GELU) and exponential softmax as essential sources of nonlinearity, but we demonstrate

Adaptive Signal Resuscitation: Channel-wise Post-Pruning Repair for Sparse Vision Networks

arXiv:2605.21426v1 Announce Type: new Abstract: One-shot magnitude pruning can cause severe accuracy collapse in the high-sparsity regime, even when the pruning mask preserves the largest weights. We

Advanced Scientific Methodology Plays Rossini

arXiv:2605.20220v1 Announce Type: cross Abstract: A musical score provides the essential instructions for its performance while containing indications - at times implicit - regarding the composer's in

AI-Augmented Surveys: Leveraging Large Language Models and Surveys for Opinion Prediction

arXiv:2305.09620v4 Announce Type: replace Abstract: Nationally representative surveys track public opinion, yet they ask only a limited set of questions each year, limiting its potential to capture hi

AIR: Amortized Image Reconstruction Framework for Self-Supervised Feed-Forward 2D Gaussian Splatting

arXiv:2605.20820v1 Announce Type: new Abstract: 2D Gaussian splatting provides an efficient explicit representation for image reconstruction, but existing methods still require costly per-image iterat

AirfoilGen: A valid-by-construction and performance-aware latent diffusion model for airfoil generation

arXiv:2605.20303v1 Announce Type: new Abstract: Airfoil shape design is a fundamental task in aerospace engineering, with a direct impact on flight stability and fuel consumption. Deep learning has re

ArPoMeme: An Annotated Arabic Multimodal Dataset for Political Ideology and Polarization

arXiv:2605.20967v1 Announce Type: new Abstract: Memes have become a prominent medium of political communication in the Arab world, reflecting how humor, imagery, and text interact to express ideologic

Assessing socio-economic climate impacts from text data

arXiv:2605.20793v1 Announce Type: new Abstract: Recent advances in natural language processing (NLP) and large language models (LLMs) have enabled the systematic use of large-scale textual data from n

Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users

arXiv:2605.20198v1 Announce Type: cross Abstract: Augmented analytics has transformed how business intelligence (BI) systems support managerial decision-making. This is especially true for users witho

Automated Kernel Discovery Towards Understanding High-dimensional Bayesian Optimization

arXiv:2605.20249v1 Announce Type: new Abstract: Gaussian Process (GP) kernels are central to Bayesian optimization (BO), yet designing effective kernels for high-dimensional problems still relies on e

Axiomatizing Neural Networks via Pursuit of Subspaces

arXiv:2605.20534v1 Announce Type: new Abstract: While deep neural networks have achieved remarkable success across a wide range of domains, their underlying mechanisms remain poorly understood, and th

BALLAST: Bayesian Active Learning with Look-ahead Amendment for Sea-drifter Trajectories under Spatio-Temporal Vector Fields

arXiv:2509.26005v3 Announce Type: replace-cross Abstract: We introduce a formal active learning methodology for guiding the placement of Lagrangian observers to infer time-dependent vector fields -- a

Beyond Numerical Features: CNN-Driven Algorithm Selection via Contour Plots for Continuous Black-Box Optimization

arXiv:2605.20797v1 Announce Type: new Abstract: The present paper introduces a new representation-driven approach to per-instance algorithm selection, applied to black-box optimization, for automatica

Beyond Routing: Characterising Expert Tuning and Representation in Vision Mixture-of-Experts

arXiv:2605.20610v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models are often interpreted by analysing which categories are routed to which experts. However, routing alone does not reveal

Block-Sparse Global Attention for Efficient Multi-View Geometry Transformers

arXiv:2509.07120v2 Announce Type: replace Abstract: Efficient and accurate feed-forward multi-view reconstruction has long been an important task in computer vision. Recent transformer-based models li

Building Arabic NLP from the Ground Up: Twenty Years of Lessons, Failures, and Open Problems

arXiv:2605.20786v1 Announce Type: new Abstract: This paper reflects on twenty years of building NLP resources and research infrastructure for Arabic, a language spoken by hundreds of millions yet hist

Building Deep Graph Predictors with Graph Imitation Learning

arXiv:2601.15133v3 Announce Type: replace Abstract: Recent years have seen substantial progress in neural generation of text, images, and audio, supported by mature training pipelines and large-scale

C^2FG: Control Classifier-Free Guidance via Score Discrepancy Analysis

arXiv:2603.08155v3 Announce Type: replace Abstract: Classifier-Free Guidance (CFG) is a cornerstone of modern conditional diffusion models, yet its reliance on the fixed or heuristic dynamic guidance

CAdam: Context-Adaptive Moment Estimation for 3D Gaussian Densification in Generative Distillation

arXiv:2605.20872v1 Announce Type: new Abstract: Adaptive densification is the engine of 3D Gaussian Splatting (3DGS). However, when transposed to the optimization-based Generative Distillation paradig

Can Conversational XAI Improve User Performance? An Experimental Study

arXiv:2605.20439v1 Announce Type: new Abstract: Explainable AI (XAI) techniques aim to provide insights into predictive models and enhance user performance, yet they often fall short of these expectat

Can liveness detection models generalise to synthetic media generation techniques they were never trained on? [D]

researchr-machinelearning

Liveness detection and synthetic media detection models often fail to generalize across unseen data and struggle with content from different models. Understanding how factors like data source diversit

CASCADE Conformal Prediction: Uncertainty-Adaptive Prediction Intervals for Two-Stage Clinical Decision Support

arXiv:2605.20468v1 Announce Type: new Abstract: Effective medication management in Parkinson's Disease (PD) is challenging due to heterogeneous disease progression, variable patient response, and medi

Causal Machine Learning Is Not a Panacea: A Roadmap for Observational Causal Inference in Health

arXiv:2605.20782v1 Announce Type: new Abstract: Objective: The growing availability of large-scale observational clinical datasets and challenges in conducting randomized controlled trials have spurre

CHOIR: Contact-aware 4D Hand-Object Interaction Reconstruction

arXiv:2605.20992v1 Announce Type: new Abstract: We ask whether everyday open-world monocular videos can be turned into reusable 4D interaction primitives: articulated hand motion, object shape with 6D

CIG: Exploration via Conditional Information Gain

arXiv:2605.20878v1 Announce Type: new Abstract: Intrinsic rewards for exploration in reinforcement learning condition on different contexts: lifelong rewards score each transition against accumulated

Classification of Single and Mixed Partial Discharges under Switching Voltage Using an AWA-CNN Framework

arXiv:2605.21352v1 Announce Type: new Abstract: The growing use of fast-switching power electronics has made partial discharge (PD) analysis under switching-voltage excitation increasingly important,

Climate tech companies are pivoting to critical minerals

We’re over a year into the second Trump administration here in the US, and support for climate causes is weak. But climate tech companies are finding ways to survive and even thrive in this new enviro

researchmit-tech-review

CMC-Opt: Constraint Manifold with Corners for Inequality-Constrained Optimization

arXiv:2605.20796v1 Announce Type: new Abstract: We introduce a manifold-based framework for addressing optimization problems with equality and inequality constraints found in robotics. Our approach tr

researcharxiv-cs-ro

Component Influence-Driven Fastener Reduction for Robotic Disassemblability-Aware Design Simplification

arXiv:2605.21026v1 Announce Type: new Abstract: To accelerate automated remanufacturing, robotic disassembly must be considered during the product design phase. However, designers currently lack quant

researcharxiv-cs-ro

Computational-Statistical Trade-off in Kernel Two-Sample Testing with Random Fourier Features

arXiv:2407.08976v2 Announce Type: replace-cross Abstract: Recent years have seen a surge in methods for two-sample testing, among which the Maximum Mean Discrepancy (MMD) test has emerged as an effect

Compute Only Once: UG-Separation for Efficient Large Recommendation Models

arXiv:2602.10455v2 Announce Type: replace-cross Abstract: Driven by scaling laws, recommender systems increasingly rely on larger-scale models to capture complex feature interactions and user behavior

Concentration of General Stochastic Approximation Under Heavy-Tailed Markovian Noise

arXiv:2605.20999v1 Announce Type: cross Abstract: We establish maximal concentration bounds for the iterates generated by stochastic approximation algorithms with general step sizes, where the noise h

ConceptSeg-R1: Segment Any Concept via Meta-Reinforcement Learning

arXiv:2605.20385v1 Announce Type: new Abstract: Recent progress in promptable segmentation has shifted visual perception from object-level localization toward concept-level understanding. However, the

Conflict-Aware Additive Guidance for Flow Models under Compositional Rewards

arXiv:2605.20758v1 Announce Type: cross Abstract: Inference-time guided sampling steers state-of-the-art diffusion and flow models without fine-tuning by interpreting the generation process as a contr

Contradiction Graphs Determine VC Dimension

arXiv:2605.20434v1 Announce Type: cross Abstract: We study the contradiction graphs associated with binary concept classes. For a class H subseteq {0,1}^X, the order-m contradiction graph G_m(H) has a