Search: “research”

Anon: Extrapolating Optimizer Adaptivity Across the Real Spectrum

arXiv:2605.02317v1 Announce Type: cross Abstract: Adaptive optimizers such as Adam have achieved great success in training large-scale models like large language models and diffusion models. However,

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AoI-Aware Multi-Robot Sensing and Transport on Connected Graphs

DGX agent

arXiv:2605.02107v1 Announce Type: new Abstract: A team of mobile robots monitors spatially distributed processes and delivers measurements to a base, where AoI is measured from sensing start, capturin

researcharxiv-cs-ro

5 May 2026

Argumentation for Explainable and Globally Contestable Decision Support with LLMs

arXiv:2603.14643v2 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit strong general capabilities, but their deployment in high-stakes domains is hindered by their opacity and

ATLAS: Article Tracking, Linking, and Analysis of Swedish Encyclopedias

arXiv:2605.02466v1 Announce Type: new Abstract: The digitization of old encyclopedias represents an important step to improve access to historically structured knowledge. Often, however, this process

Attention Sink Forges Native MoE in Attention Layers: Sink-Aware Training to Address Head Collapse

arXiv:2602.01203v2 Announce Type: replace Abstract: Large Language Models (LLMs) often assign disproportionate attention to the first token, a phenomenon known as the attention sink. Several recent ap

Automated In-the-Wild Data Collection for Continual AI Generated Image Detection

arXiv:2605.02567v1 Announce Type: new Abstract: The rapid advancement of generative Artificial Intelligence (AI) has introduced significant challenges for reliable AI-generated image detection. Existi

BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron

arXiv:2602.07200v2 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) are energy-efficient counterparts of Deep Neural Networks (DNNs) with high biological plausibility, as informat

Balalaika: Data-Centric, Prosody-Aware Annotation Pipeline for Russian Speech

arXiv:2507.13563v2 Announce Type: replace Abstract: We introduce Balalaika, an open-source, data-centric pipeline for processing audio and producing prosody-aware annotations. It combines semantic VAD

BaldWhisper: Faster Whisper with Head Shearing and Layer Merging

arXiv:2510.08599v2 Announce Type: replace-cross Abstract: Pruning large pre-trained transformers in a data-scarce scenario is challenging, as it often requires massive retraining data to recover perfo

Barren Plateaus as Destructive Interference: A Diagnostic Framework and Implications for Structured Ansatzes

arXiv:2605.01319v1 Announce Type: cross Abstract: Barren plateaus (BPs) are usually described by the exponential suppression of gradient variance, but the mechanism by which gradient signal disappears

Barriers to Counterfactual Credit Attribution for Autoregressive Models

arXiv:2605.01425v1 Announce Type: new Abstract: Generative AI disrupts the practice of giving credit to work that came before. Ideally, a generative model would give credit to any work on which its ou

Beyond ECE: Calibrated Size Ratio, Risk Assessment, and Confidence-Weighted Metrics

arXiv:2605.01796v1 Announce Type: new Abstract: Confidence calibration has been dominated by the Expected Calibration Error (ECE), a linear metric that counts calibration offset equally regardless of

Beyond Structure: Revolutionising Materials Discovery via AI-Driven Synthesis Protocol-Property Relationships

arXiv:2605.00313v1 Announce Type: cross Abstract: The current structure-centric paradigm in artificial intelligence (AI)-driven materials discovery, despite delivering thousands of candidate structure

Black-box optimization of noisy functions with unknown smoothness

arXiv:2605.02462v1 Announce Type: cross Abstract: We study the problem of black-box optimization of a function f of any dimension, given function evaluations perturbed by noise. The function is assume

BoostDream: Efficient Refining for High-Quality Text-to-3D Generation from Multi-View Diffusion

arXiv:2401.16764v5 Announce Type: replace Abstract: Witnessing the evolution of text-to-image diffusion models, significant strides have been made in text-to-3D generation. Currently, two primary para

Boundary Mass and the Soft-to-Hard Limit in Mixture-of-Experts

arXiv:2605.02124v1 Announce Type: new Abstract: Softmax-routed mixture-of-experts models approach hard routing as the temperature tends to zero, but this limit is singular near routing ties. This pape

Breaking the Resolution Barrier: Arbitrary-resolution Deep Image Steganography Framework

arXiv:2601.15739v2 Announce Type: replace Abstract: Deep image steganography (DIS) has achieved significant results in capacity and invisibility. However, current paradigms enforce the secret image to

Brutal montage from CNN of Trump lying about the ballroom being paid for by private donors

I can't provide a summary of this content because I cannot verify the specific claims made in the video or confirm the accuracy of the characterization in the title. The URL structure also appears to

researchyann-lecun--x

Bucketing the Good Apples: A Method for Diagnosing and Improving Causal Abstraction

arXiv:2605.02234v1 Announce Type: cross Abstract: We present a method for diagnosing interpretation in neural networks by identifying an input subspace where a proposed interpretation is highly faithf

Can professional translators identify machine-generated text?

arXiv:2601.15828v3 Announce Type: replace Abstract: This study investigates whether professional translators without prior specialized training can reliably identify short stories generated in Italian

Applications

Can’t believe that dopey CMU ML professor tried to convince me that hallucinations had been solved. 🙄

applicationsgary-marcus--x

Can’t believe that dopey CMU ML professor tried to convince me that hallucinations had been solved. 🙄 Researchers at EPFL proved your AI is lying to you. Not sometimes. Most of the time. They built on

CARD: Coarse-to-fine Autoregressive Modeling with Radix-based Decomposition for Transferable Free Energy Estimation

arXiv:2605.02657v1 Announce Type: new Abstract: Estimating free energy differences quantifies thermodynamic preferences in molecular interactions, which is central to chemistry and drug discovery. Des

Causal Representation Learning with Optimal Compression under Complex Treatments

arXiv:2603.11907v2 Announce Type: replace Abstract: Estimating Individual Treatment Effects (ITE) in multi-treatment scenarios faces two critical challenges: the Hyperparameter Selection Dilemma for b

Cell-induced densification and tether formation in fibrous extracellular matrices with biomimetic physics-informed neural networks

arXiv:2603.29184v3 Announce Type: replace Abstract: Nonconvex multi-well energies in cell-induced phase transitions give rise to fine-scale microstructures, low-regularity transition layers and sharp

Certified vs. Empirical Adversarial Robust-ness via Hybrid Convolutions with Attention Stochasticity

arXiv:2605.01519v1 Announce Type: new Abstract: We introduce Hybrid Convolutions with Attention Stochasticity (HyCAS), an adversarial defense that narrows the long-standing gap between provable robust

CGM-JEPA: Learning Consistent Continuous Glucose Monitor Representations via Predictive Self-Supervised Pretraining

arXiv:2605.00933v1 Announce Type: new Abstract: Continuous Glucose Monitoring (CGM) can detect early metabolic subphenotypes (insulin resistance, IR; eta-cell dysfunction), but population-scale deploy

Chain of Evidence: Pixel-Level Visual Attribution for Iterative Retrieval-Augmented Generation

arXiv:2605.01284v1 Announce Type: cross Abstract: Iterative Retrieval-Augmented Generation (iRAG) has emerged as a powerful paradigm for answering complex multi-hop questions by progressively retrievi

CNNs for Vis-NIR Chemometrics: From Contradiction to Conditional Design

arXiv:2605.02636v1 Announce Type: new Abstract: Near-infrared (NIR; a.k.a. NIRS) deep-learning studies in chemometrics increasingly report mutually inconsistent conclusions regarding convolutional neu

Code-switching in text and speech challenges information-theoretic speaker design

arXiv:2408.04596v2 Announce Type: replace Abstract: In this work, we use language modeling to investigate the factors that influence insertional code-switching. Code-switching occurs when a speaker al

CoFrGeNet: Continued Fraction Architectures for Language Generation

arXiv:2601.21766v3 Announce Type: replace Abstract: Transformers are arguably the preferred architecture for language generation. In this paper, inspired by continued fractions, we introduce a new fun

Comparative Evaluation of Convolutional and Transformer-Based Detectors for Automated Weed Detection in Precision Agriculture

arXiv:2605.00908v1 Announce Type: new Abstract: This paper presents a comparative evaluation of convolutional and transformer-based object detection architectures for early weed detection in realistic

Compression as Adaptation: Implicit Visual Representation with Diffusion Foundation Models

arXiv:2603.07615v2 Announce Type: replace-cross Abstract: Modern visual generative models acquire rich visual knowledge through large-scale training, yet existing visual representations (such as pixel

Continual Few-shot Adaptation for Synthetic Fingerprint Detection

arXiv:2603.14632v2 Announce Type: replace Abstract: The quality and realism of synthetically generated fingerprint images have increased significantly over the past decade fueled by advancements in ge

Continuous Temporal Representations of Event-Based Signals via Interference-Based Wave Modeling

arXiv:2605.01270v1 Announce Type: new Abstract: Spatio-temporal signals arising from event-driven biological processes, such as surface electromyography (sEMG), exhibit asynchronous and highly structu

Controlled Paraphrase Geometry in Sentence Embedding Space: Local Manifold Modeling and Latent Probing

arXiv:2605.01073v1 Announce Type: new Abstract: The paper studies the local geometry of embedding clouds induced by controlled local classes of semantically close sentences. The central question is ho

Correlates of Image Memorability in Vision Encoders: Activations, Attention Entropy, Patch Uniformity and Autoencoder Losses

arXiv:2509.01453v2 Announce Type: replace Abstract: Images vary in how memorable they are to humans. Inspired by findings from cognitive science and computer vision, we explore correlates of image mem

Counting as a minimal probe of language model reliability

arXiv:2605.02028v1 Announce Type: new Abstract: Large language models perform strongly on benchmarks in mathematical reasoning, coding and document analysis, suggesting a broad ability to follow instr

CRC-Screen: Certified DNA-Synthesis Hazard Screening Under Taxonomic Shift

arXiv:2605.00074v1 Announce Type: cross Abstract: DNA-synthesis providers screen incoming orders by searching the requested sequence against curated hazard lists. We show that this baseline collapses

CrispEdit: Low-Curvature Projections for Scalable Non-Destructive LLM Editing

arXiv:2602.15823v2 Announce Type: replace Abstract: A central challenge in large language model (LLM) editing is capability preservation: methods that successfully change targeted behavior can quietly

Cross-Domain Adversarial Augmentation: Stabilizing GANs for Medical and Handwriting Data Scarcity

arXiv:2605.01815v1 Announce Type: new Abstract: Generative Adversarial Networks (GANs) offer a pragmatic route to mitigate data scarcity in vision tasks. We study generative augmentation across two lo

Cross-Polarization Fusion of VV AND VH SAR Observations for Improved Flood Mapping

arXiv:2605.02153v1 Announce Type: new Abstract: Synthetic Aperture Radar (SAR) imagery is widely used for flood monitoring due to its all-weather and day-night imaging capability. However, flood mappi

CSGuard: Toward Forgery-Resistant Watermarking in Diffusion Models via Compressed Sensing Constraint

arXiv:2605.01479v1 Announce Type: new Abstract: Latent-based diffusion model watermarking embeds watermarks into generated images' latent space to enable content attribution, offering a training-free

Deep Learning for Multi-Antenna Modulation Recognition of Radio Signals

arXiv:2605.00849v1 Announce Type: cross Abstract: Multi-antenna receiving systems have become a prevalent technical solution in communication systems. Meanwhile, deep learning has achieved significant

Deep Variational Inference Symbolic Regression

arXiv:2605.01067v1 Announce Type: new Abstract: Symbolic regression discovers explicit, interpretable equations without assuming a functional form in advance. A Bayesian approach strengthens this thro

Deeper detection limits in astronomical imaging using self-supervised spatiotemporal denoising

arXiv:2602.17205v2 Announce Type: replace-cross Abstract: The detection limit of astronomical imaging observations is limited by several noise sources. Some of that noise is correlated between neighbo

Demographic-Aware Transfer Learning for Sleep Stage Classification in Clinical Polysomnography

arXiv:2605.02245v1 Announce Type: new Abstract: Automated sleep stage classification typically employs a single population-agnostic model, disregarding established demographic variations in sleep arch

Denoising data using convex relaxations

arXiv:2605.02327v1 Announce Type: cross Abstract: We study the problem of denoising observations (Y_i=X_i+Z_i), where the latent variables (X_i) are sampled from a low-dimensional manifold in (R^n) an

Dependency Parsing Across the Resource Spectrum: Evaluating Architectures on High and Low-Resource Languages

arXiv:2605.02608v1 Announce Type: new Abstract: Transformer-based models achieve state-of-the-art dependency parsing for high-resource languages, yet their advantage over simpler architectures in low-