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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

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

DGX agent

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

researcharxiv-cs-lg

21 May 2026

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

Safety

The Download: online safety’s future and climate tech’s big pivot

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. Tech researchers are suing the Trump administration over the f

safetymit-tech-review

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

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

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.

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

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

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

A Data-Driven Approach to Idiomaticity Based on Experts' Criteria in Theoretical Linguistics

arXiv:2605.19575v1 Announce Type: new Abstract: The article observes data analysis of 286 multi-word expressions (MWEs) based on 16 lexical, grammatical and other criteria described in theoretical boo

A Derandomization Framework for Structure Discovery: Applications in Neural Networks and Beyond

arXiv:2510.19382v2 Announce Type: replace-cross Abstract: Understanding the dynamics of feature learning in neural networks (NNs) remains a significant challenge. The work of (Mousavi-Hosseini et al.,

A first-order method for nonconvex-nonconcave minimax problems under a local Kurdyka-Lojasiewicz condition

arXiv:2507.01932v2 Announce Type: replace-cross Abstract: We study a class of nonconvex-nonconcave minimax problems in which the inner maximization problem satisfies a local Kurdyka-Lojasiewicz (KL) c

A Framework for Evaluating Zero-Shot Image Generation in Concept-based Explainability

arXiv:2605.19855v1 Announce Type: cross Abstract: Concept-based Explainable Artificial Intelligence (XAI) interprets deep learning models using human-understandable visual features (e.g., textures or

A Grid-Based Framework for E-Scooter Demand Representation and Temporal Input Design for Deep Learning: Evidence from Austin, Texas

arXiv:2603.13609v2 Announce Type: replace Abstract: Despite progress in deep learning for shared micromobility demand prediction, the systematic design and statistical validation of temporal input str

A Measure-Theoretic Analysis of Reasoning: Structural Generalization and Approximation Limits

arXiv:2605.19944v1 Announce Type: cross Abstract: While empirical scaling laws for LLM reasoning are well-documented, the theoretical mechanisms governing out-of-distribution (OOD) generalization rema

A Nash Equilibrium Framework For Training-Free Multimodal Step Verification

arXiv:2605.20033v1 Announce Type: new Abstract: Multimodal large language models often generate reasoning chains containing subtle errors that lead to incorrect answers. Current verification approache

A Practical Framework of Key Performance Indicators for Multi-Robot Lunar and Planetary Field Tests

arXiv:2601.20529v3 Announce Type: replace Abstract: Robotic prospecting for critical resources on the Moon, such as ilmenite, rare earth elements, and water ice, requires robust exploration methods gi

researcharxiv-cs-ro

A Two-Phase Adaptive Balanced Penalty Method for Controllable Pareto Front Learning under Split Feasibility Conditions

arXiv:2605.19306v1 Announce Type: new Abstract: We address the open problem of training hypernetworks for Controllable Pareto Front Learning (CPFL) under split feasibility conditions with rigorous the

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems

arXiv:2605.19366v1 Announce Type: new Abstract: Environmental science plays a pivotal role in safeguarding ecosystems, a domain driven by large-scale, heterogeneous data. In the big data era, artifici

Adaptive Multi-Scale Goodness Aggregation for Forward-Forward Learning

arXiv:2605.18804v1 Announce Type: cross Abstract: We propose Adaptive Multi-Scale Goodness Aggregation (AMSGA), a novel extension of the Forward-Forward (FF) algorithm designed to improve stability, r

Adaptive Residual-Update Steering for Low-Overhead Hallucination Mitigation in Large Vision Language Models

arXiv:2511.10292v2 Announce Type: replace-cross Abstract: Large Vision-Language Models (LVLMs) typically process visual inputs as a prefix to the language decoder. As the model autoregressively genera

Adynamical systems view of training generativemodels and the memorization phenomenon

arXiv:2605.19483v1 Announce Type: new Abstract: Using recent works of one of the authors (VSB) on collapse in generative models and two time scale dynamics in stochastic gradient descent in high dimen