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Simultaneous CNN Approximation on Manifolds with Applications to Boundary Value Problems

arXiv:2605.04126v1 Announce Type: new Abstract: This paper develops convolutional neural network (CNN) methods for simultaneous approximation and elliptic boundary value problems on compact Riemannian

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Sparsity is Combinatorial Depth: Quantifying MoE Expressivity via Tropical Geometry

DGX agent

arXiv:2602.03204v2 Announce Type: replace Abstract: While Mixture-of-Experts (MoE) architectures define the state-of-the-art, their theoretical success is often attributed to heuristic efficiency rath

researcharxiv-cs-lg

7 May 2026

Stop Automating Peer Review Without Rigorous Evaluation

arXiv:2605.03202v1 Announce Type: new Abstract: Large language models offer a tempting solution to address the peer review crisis. This position paper argues that today's AI systems should not be used

researcharxiv-cs-ai

Structured 3D Latents Are Surprisingly Powerful: Unleashing Generalizable Style with 2D Diffusion

arXiv:2605.04412v1 Announce Type: new Abstract: 3D asset generation plays a pivotal role in fields such as gaming and virtual reality, enabling the rapid synthesis of high-fidelity 3D objects from a s

Superposition Is Not Necessary: A Mechanistic Interpretability Analysis of Transformer Representations for Time Series Forecasting

arXiv:2605.05151v1 Announce Type: new Abstract: Transformer architectures have been widely adopted for time series forecasting, yet whether the representational mechanisms that make them powerful in N

Syn4D: A Multiview Synthetic 4D Dataset

arXiv:2605.05207v1 Announce Type: new Abstract: Dense 3D reconstruction and tracking of dynamic scenes from monocular video remains an important open challenge in computer vision. Progress in this are

TajikNLP: An Open-Source Toolkit for Comprehensive Text Processing of Tajik (Cyrillic Script)

arXiv:2605.04583v1 Announce Type: new Abstract: The Tajik language, written in Cyrillic script, remains severely under-resourced in terms of publicly available natural language processing (NLP) toolki

Taming Outlier Tokens in Diffusion Transformers

arXiv:2605.05206v1 Announce Type: new Abstract: We study outlier tokens in Diffusion Transformers (DiTs) for image generation. Prior work has shown that Vision Transformers (ViTs) can produce a small

The Download: the tech reshaping IVF and the rise of balcony solar

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. What’s next for IVF IVF has brought millions of babies into th

researchmit-tech-review

The First Token Knows: Single-Decode Confidence for Hallucination Detection

arXiv:2605.05166v1 Announce Type: new Abstract: Self-consistency detects hallucinations by generating multiple sampled answers to a question and measuring agreement, but this requires repeated decodin

The Impact of Vocabulary Overlaps on Knowledge Transfer in Multilingual Machine Translation

arXiv:2605.04196v1 Announce Type: new Abstract: Knowledge transfer, especially across related languages, has been found beneficial for multilingual neural machine translation (MNMT), but some aspects

The Implicit Curriculum: Learning Dynamics in RL with Verifiable Rewards

arXiv:2602.14872v2 Announce Type: replace Abstract: Reinforcement learning with verifiable rewards (RLVR) has been a main driver of recent breakthroughs in large reasoning models. Yet it remains a mys

The Impossibility Triangle of Long-Context Modeling

arXiv:2605.05066v1 Announce Type: new Abstract: We identify and prove a fundamental trade-off governing long-sequence models: no model can simultaneously achieve (i) per-step computation independent o

The Newsworthiness of Brazilian Distress: A Peak Analysis on Time Series of International Media Attention to Disasters in Brazil

arXiv:2605.04552v1 Announce Type: new Abstract: Media coverage influences disaster response, yet the drivers of international media attention to local events remain unevenly understood. Brazil offers

The Pinocchio Dimension: Phenomenality of Experience as the Primary Axis of LLM Psychometric Differences

arXiv:2605.05080v1 Announce Type: new Abstract: We administer 45 validated psychometric questionnaires to 50 large language models (LLMs) to identify the dimensions along which LLMs differ psychometri

The Tsetlin Machine Goes Deep: Logical Learning and Reasoning With Graphs

arXiv:2507.14874v2 Announce Type: replace Abstract: Pattern recognition with concise and flat AND-rules makes the Tsetlin Machine (TM) both interpretable and efficient, while the power of Tsetlin auto

Topology-Preserving Data Augmentation for Ring-Type Polygon Annotations

arXiv:2603.14764v3 Announce Type: replace Abstract: Geometric data augmentation is widely used in segmentation workflows, but polygon annotations are often assumed to remain valid after transformation

Total Jobs Created by Party (1989-2026): Democratic Presidents 50,600,000 Republican Presidents 1,469,000 The biggest scam the GOP has ever …

Total Jobs Created by Party (1989-2026): Democratic Presidents 50,600,000 Republican Presidents 1,469,000 The biggest scam the GOP has ever pulled off is convincing people that Republicans are good fo

researchyann-lecun--x

Toward Human-AI Complementarity Across Diverse Tasks

arXiv:2605.04070v1 Announce Type: cross Abstract: Human-AI complementarity, the idea that combining human and AI judgments can outperform either alone, offers a promising pathway toward robust oversig

Towards Distillation-Resistant Large Language Models: An Information-Theoretic Perspective

arXiv:2602.03396v3 Announce Type: replace Abstract: Proprietary large language models (LLMs) embody substantial economic value and are generally exposed only as black-box APIs, yet adversaries can sti

Towards Self-Referential Analytic Assessment: A Profile-Based Approach to L2 Writing Evaluation with LLMs

arXiv:2605.04298v1 Announce Type: new Abstract: Automated essay scoring (AES) research often relies on rank-based correlation metrics to validate analytic assessment. However, such metrics obscure bot

Transformed Latent Variable Multi-Output Gaussian Processes

arXiv:2605.05133v1 Announce Type: new Abstract: Multi-Output Gaussian Processes (MOGPs) provide a principled probabilistic framework for modelling correlated outputs but face scalability bottlenecks w

Trustworthy Federated Label Distribution Learning under Annotation Quality Disparity

arXiv:2605.04827v1 Announce Type: new Abstract: Label Distribution Learning (LDL) models supervision as an instance-wise probability distribution, enabling fine-grained learning under inherent ambigui

Understanding LoRA as Knowledge Memory: An Empirical Analysis

arXiv:2603.01097v2 Announce Type: replace Abstract: Continuous knowledge updating for pre-trained large language models (LLMs) is increasingly necessary yet remains challenging. Although inference-tim

Understanding Transformers through the Lens of Pavlovian Conditioning

arXiv:2508.08289v2 Announce Type: replace Abstract: Transformer architectures have revolutionized artificial intelligence (AI) through their attention mechanisms, yet the computational principles unde

Undetectable Backdoors in Model Parameters: Hiding Sparse Secrets in High Dimensions

arXiv:2605.04209v1 Announce Type: cross Abstract: We present Sparse Backdoor, a supply-chain attack that plants a provably undetectable backdoor in pre-trained image classifiers, including convolution

Unintended Negative Impacts of Promotional Language in Patent Evaluation

arXiv:2605.04926v1 Announce Type: new Abstract: Promotional language has been increasingly used to aid the communication of innovative ideas in science. Yet, less is known about its role in the contex

UniPCB: A Generation-Assisted Detection Framework for PCB Defect Inspection

arXiv:2605.04635v1 Announce Type: new Abstract: Printed Circuit Board (PCB) defect inspection faces two compounding challenges: scarce and imbalanced defect samples that limit model training, and insu

VC-FeS: Viewpoint-Conditioned Feature Selection for Vehicle Re-identification in Thermal Vision

arXiv:2605.04750v1 Announce Type: new Abstract: Identification of less-articulated objects using single-channel images, such as thermal images, is important in many applications, such as surveillance.

Visual Disentangled Diffusion Autoencoders: Scalable Counterfactual Generation for Foundation Models

arXiv:2601.21851v2 Announce Type: replace Abstract: Foundation models, despite their robust zero-shot capabilities, remain vulnerable to spurious correlations and 'Clever Hans' strategies. Existing mi

Vol-Mark: A Watermark for 3D Medical Volume Data Via Cubic Difference Expansion and Contrastive Learning

arXiv:2605.04705v1 Announce Type: cross Abstract: Today, advances in medical technology extensively utilize 3D volume data for accurate and efficient diagnostics. However, sharing these data across ne

What Can Be Recovered Under Sparse Adversarial Corruption? Assumption-Free Theory for Linear Measurements

arXiv:2510.24215v4 Announce Type: replace-cross Abstract: Recovery from linear measurements under sparse adversarial corruption is typically formulated as an exact-recovery problem: one seeks structur

What Matters in Practical Learned Image Compression

researchapple-ml-research

One of the major differentiators unlocked by learned codecs relative to their hard-coded traditional counterparts is their ability to be optimized directly to appeal to the human visual system. Despit

What’s next for IVF

MIT Technology Review’s What’s Next series looks across industries, trends, and technologies to give you a first look at the future. You can read the rest of them here. Forty-eight years ago this July

researchmit-tech-review

When Does Gene Regulatory Network Inference Break? A Controlled Diagnostic Study of Causal and Correlational Methods on Single-Cell Data

arXiv:2605.04930v1 Announce Type: new Abstract: Despite theoretical advantages, causal methods for Gene Regulatory Network (GRN) inference from single-cell RNA-seq data consistently fail to match or o

When Engineering Outruns Intelligence: Rethinking Instruction-Guided Navigation

arXiv:2507.20021v3 Announce Type: replace-cross Abstract: Recent ObjectNav systems credit large language models (LLMs) for sizable zero-shot gains, yet it remains unclear how much comes from language

When Relations Break: Analyzing Relation Hallucination in Vision-Language Model Under Rotation and Noise

arXiv:2605.05045v1 Announce Type: cross Abstract: Vision-language models (VLMs) achieve strong multimodal performance but remain prone to relation hallucination, which requires accurate reasoning over

Why Geometric Continuity Emerges in Deep Neural Networks: Residual Connections and Rotational Symmetry Breaking

arXiv:2605.04971v1 Announce Type: cross Abstract: Weight matrices in deep networks exhibit geometric continuity -- principal singular vectors of adjacent layers point in similar directions. While this

3D Human Face Reconstruction with 3DMM face model from RGB image

arXiv:2605.03996v1 Announce Type: new Abstract: Nowadays as convolution neural networks demonstrate its powerful problem-solving ability in the area of image processing, efforts have been made to reco

4RC: 4D Reconstruction via Conditional Querying Anytime and Anywhere

arXiv:2602.10094v2 Announce Type: replace Abstract: We present 4RC, a unified feed-forward framework for 4D reconstruction from monocular videos. Unlike existing approaches that typically decouple mot

A Certifably Correct Algorithm for Generalized Robot-World and Hand-Eye Calibration

arXiv:2507.23045v2 Announce Type: replace Abstract: Automatic extrinsic sensor calibration is a fundamental problem for multi-sensor platforms. Reliable and general-purpose solutions should be computa

researcharxiv-cs-ro

A Closed-Form Adaptive-Landmark Kernel for Certified Point-Cloud and Graph Classification

arXiv:2605.04046v1 Announce Type: new Abstract: We introduce PALACE (Persistence Adaptive-Landmark Analytic Classification Engine), the data-adaptive companion to PLACE, paying a small cross-validatio

A-CODE: Fully Atomic Protein Co-Design with Unified Multimodal Diffusion

arXiv:2605.03360v1 Announce Type: cross Abstract: We present A-CODE, a fully atomic unified one-stage protein co-design model that simultaneously refines discrete atom types and continuous atom coordi

A Comparison of Traditional Machine Learning Algorithms and LSTM-Based Deep Learning Models for Email Sentiment Analysis

arXiv:2605.03440v1 Announce Type: new Abstract: The rapid growth of electronic communication has necessitated more robust systems for email classification and sentiment detection. This study presents

A Comprehensive Analysis of Tokenization and Self-Supervised Learning in End-to-End Automatic Speech Recognition applied on French Language

arXiv:2605.03696v1 Announce Type: new Abstract: The performance of end-to-end automatic speech recognition (ASR) systems enables their increasing integration into numerous applications. While there ar

A Hierarchical Sampling Framework for bounding the Generalization Error of Federated Learning

arXiv:2605.03499v1 Announce Type: new Abstract: We study expected generalization bounds for the Hierarchical Federated Learning (HFL) setup using Wasserstein distance. We introduce a generalized frame

A note on the unique properties of the Kullback--Leibler divergence for sampling via gradient flows

arXiv:2507.04330v2 Announce Type: replace-cross Abstract: We consider the problem of sampling from a probability distribution pi which admits a density w.r.t. a dominating measure. It is well known th

A Paradigm for Interpreting Metrics and Identifying Critical Errors in Automatic Speech Recognition

arXiv:2605.03671v1 Announce Type: new Abstract: The most commonly used metrics for evaluating automatic speech transcriptions, namely Word Error Rate (WER) and Character Error Rate (CER), have been he