Search: “research”

Beyond Expected Information Gain: Stable Bayesian Optimal Experimental Design with Integral Probability Metrics and Plug-and-Play Extensions

arXiv:2604.21849v1 Announce Type: cross Abstract: Bayesian Optimal Experimental Design (BOED) provides a rigorous framework for decision-making tasks in which data acquisition is often the critical bo

Research

Beyond the Frame: Generating 360 Panoramic Videos from Perspective Videos

DGX agent

arXiv:2504.07940v3 Announce Type: replace Abstract: 360{eg} videos have emerged as a promising medium to represent our dynamic visual world. Compared to the 'tunnel vision' of standard cameras, their

researcharxiv-cs-cv

24 Apr 2026

Bridging the Training-Deployment Gap: Gated Encoding and Multi-Scale Refinement for Efficient Quantization-Aware Image Enhancement

arXiv:2604.21743v1 Announce Type: new Abstract: Image enhancement models for mobile devices often struggle to balance high output quality with the fast processing speeds required by mobile hardware. W

Calibeating Prediction-Powered Inference

arXiv:2604.21260v1 Announce Type: cross Abstract: We study semisupervised mean estimation with a small labeled sample, a large unlabeled sample, and a black-box prediction model whose output may be mi

Causal Disentanglement for Full-Reference Image Quality Assessment

arXiv:2604.21654v1 Announce Type: cross Abstract: Existing deep network-based full-reference image quality assessment (FR-IQA) models typically work by performing pairwise comparisons of deep features

Certified Coil Geometry Learning for Short-Range Magnetic Actuation and Spacecraft Docking Application

arXiv:2507.03806v3 Announce Type: replace-cross Abstract: This paper presents a learning-based framework for approximating an exact magnetic-field interaction model, supported by both numerical and ex

ChessArena: A Chess Testbed for Evaluating Strategic Reasoning Capabilities of Large Language Models

arXiv:2509.24239v4 Announce Type: replace-cross Abstract: Recent large language models (LLMs) have shown strong reasoning capabilities. However, a critical question remains: do these models possess ge

climt-paraformer: Stable Emulation of Convective Parameterization using a Temporal Memory-aware Transformer

arXiv:2604.21085v1 Announce Type: cross Abstract: Accurate representation of moist convective sub-grid-scale processes remains a major challenge in global climate models, as traditional parameterizati

Clinical Evaluation of a Tongue-Controlled Wrist Abduction-Adduction Assistance in a 6-DoF Upper-Limb Exoskeleton for Individuals with ALS and SCI

arXiv:2604.20967v1 Announce Type: new Abstract: Upper-limb exoskeletons (ULEs) have the potential to restore functional independence in individuals with severe motor impairments; however, the clinical

researcharxiv-cs-ro

Clinically-Informed Modeling for Pediatric Brain Tumor Classification from Whole-Slide Histopathology Images

arXiv:2604.21060v1 Announce Type: new Abstract: Accurate diagnosis of pediatric brain tumors, starting with histopathology, presents unique challenges for deep learning, including severe data scarcity

CoFEE: Reasoning Control for LLM-Based Feature Discovery

arXiv:2604.21584v1 Announce Type: new Abstract: Feature discovery from complex unstructured data is fundamentally a reasoning problem: it requires identifying abstractions that are predictive of a tar

Component-Based Out-of-Distribution Detection

arXiv:2604.21546v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection requires sensitivity to subtle shifts without overreacting to natural In-Distribution (ID) diversity. However, from

Context Unrolling in Omni Models

arXiv:2604.21921v1 Announce Type: new Abstract: We present Omni, a unified multimodal model natively trained on diverse modalities, including text, images, videos, 3D geometry, and hidden representati

Convergence Rates for Non-Log-Concave Sampling and Log-Partition Estimation

arXiv:2303.03237v4 Announce Type: replace-cross Abstract: Sampling from Gibbs distributions and computing their log-partition function are fundamental tasks in statistics, machine learning, and statis

Cosmological Analysis with Calibrated Neural Quantile Estimation and Approximate Simulators

arXiv:2411.14748v2 Announce Type: replace-cross Abstract: A major challenge in extracting information from current and upcoming surveys of cosmological Large-Scale Structure (LSS) is the limited avail

Cross-Distribution Diffusion Priors-Driven Iterative Reconstruction for Sparse-View CT

arXiv:2509.13576v2 Announce Type: replace-cross Abstract: Sparse-View CT (SVCT) reconstruction enhances temporal resolution and reduces radiation dose, yet its clinical use is hindered by artifacts du

DCMorph: Face Morphing via Dual-Stream Cross-Attention Diffusion

arXiv:2604.21627v1 Announce Type: new Abstract: Advancing face morphing attack techniques is crucial to anticipate evolving threats and develop robust defensive mechanisms for identity verification sy

Deep kernel video approximation for unsupervised action segmentation

arXiv:2604.21572v1 Announce Type: new Abstract: This work focuses on per-video unsupervised action segmentation, which is of interest to applications where storing large datasets is either not possibl

Dementia classification from spontaneous speech using wrapper-based feature selection

arXiv:2502.03484v2 Announce Type: replace-cross Abstract: Dementia encompasses a group of syndromes that impair cognitive functions such as memory, reasoning, and the ability to perform daily activiti

DiffNR: Diffusion-Enhanced Neural Representation Optimization for Sparse-View 3D Tomographic Reconstruction

arXiv:2604.21518v1 Announce Type: cross Abstract: Neural representations (NRs), such as neural fields and 3D Gaussians, effectively model volumetric data in computed tomography (CT) but suffer from se

Dilated CNNs for Periodic Signal Processing: A Low-Complexity Approach

arXiv:2604.21651v1 Announce Type: cross Abstract: Denoising of periodic signals and accurate waveform estimation are core tasks across many signal processing domains, including speech, music, medical

Distributed Associative Memory via Online Convex Optimization

arXiv:2509.22321v2 Announce Type: replace Abstract: An associative memory (AM) enables cue-response recall, and associative memorization has recently been noted to underlie the operation of modern neu

Do Masked Autoencoders Improve Downhole Prediction? An Empirical Study on Real Well Drilling Data

arXiv:2604.20909v1 Announce Type: new Abstract: Downhole drilling telemetry presents a fundamental labeling asymmetry: surface sensor data are generated continuously at 1~Hz, while labeled downhole me

Early Detection of Latent Microstructure Regimes in Limit Order Books

arXiv:2604.20949v1 Announce Type: new Abstract: Limit order books can transition rapidly from stable to stressed conditions, yet standard early-warning signals such as order flow imbalance and short-t

Efficient Logic Gate Networks for Video Copy Detection

arXiv:2604.21694v1 Announce Type: cross Abstract: Video copy detection requires robust similarity estimation under diverse visual distortions while operating at very large scale. Although deep neural

Enhancing Online Recruitment with Category-Aware MoE and LLM-based Data Augmentation

arXiv:2604.21264v1 Announce Type: new Abstract: Person-Job Fit (PJF) is a critical component for online recruitment. Existing approaches face several challenges, particularly in handling low-quality j

Evaluating Post-hoc Explanations of the Transformer-based Genome Language Model DNABERT-2

arXiv:2604.21690v1 Announce Type: new Abstract: Explaining deep neural network predictions on genome sequences enables biological insight and hypothesis generation-often of greater interest than predi

Evaluation of Automatic Speech Recognition Using Generative Large Language Models

arXiv:2604.21928v1 Announce Type: new Abstract: Automatic Speech Recognition (ASR) is traditionally evaluated using Word Error Rate (WER), a metric that is insensitive to meaning. Embedding-based sema

Even More Guarantees for Variational Inference in the Presence of Symmetries

arXiv:2604.21407v1 Announce Type: new Abstract: When approximating an intractable density via variational inference (VI) the variational family is typically chosen as a simple parametric family that v

Expanding the extreme-k dielectric materials space through physics-validated generative reasoning

arXiv:2604.21068v1 Announce Type: cross Abstract: The most technologically consequential materials are often the rarest: they occupy narrow regions of chemical space, obey competing physical constrain

Feel like very few serious people make the argument Britain should develop its own LLM? Certainly not an argument you see made in Westminste…

Feel like very few serious people make the argument Britain should develop its own LLM? Certainly not an argument you see made in Westminster often during the sovereignty debate. Also some other eyebr

researchyann-lecun--x

Finding Meaning in Embeddings: Concept Separation Curves

arXiv:2604.21555v1 Announce Type: new Abstract: Sentence embedding techniques aim to encode key concepts of a sentence's meaning in a vector space. However, the majority of evaluation approaches for s

Fixation Sequences as Time Series: A Topological Approach to Dyslexia Detection

arXiv:2604.21698v1 Announce Type: new Abstract: Persistent homology, a method from topological data analysis, extracts robust, multi-scale features from data. It produces stable representations of tim

Focus on What Matters: Fisher-Guided Adaptive Multimodal Fusion for Vulnerability Detection

arXiv:2601.02438v3 Announce Type: replace-cross Abstract: Software vulnerability detection can be formulated as a binary classification problem that determines whether a given code snippet contains se

Forget, Then Recall: Learnable Compression and Selective Unfolding via Gist Sparse Attention

arXiv:2604.20920v1 Announce Type: new Abstract: Scaling large language models to long contexts is challenging due to the quadratic computational cost of full attention. Mitigation approaches include K

Foveated Reasoning: Stateful, Action-based Visual Focusing for Vision-Language Models

arXiv:2604.21079v1 Announce Type: new Abstract: Vision-language models benefit from high-resolution images, but the increase in visual-token count incurs high compute overhead. Humans resolve this ten

Frequency-Forcing: From Scaling-as-Time to Soft Frequency Guidance

arXiv:2604.20902v1 Announce Type: cross Abstract: While standard flow-matching models transport noise to data uniformly, incorporating an explicit generation order - specifically, establishing coarse,

From Tokens to Concepts: Leveraging SAE for SPLADE

arXiv:2604.21511v1 Announce Type: cross Abstract: Learned Sparse IR models, such as SPLADE, offer an excellent efficiency-effectiveness tradeoff. However, they rely on the underlying backbone vocabula

FunduSegmenter: Leveraging the RETFound Foundation Model for Joint Optic Disc and Optic Cup Segmentation in Retinal Fundus Images

arXiv:2508.11354v3 Announce Type: replace-cross Abstract: Purpose: This study introduces the first adaptation of RETFound for joint optic disc (OD) and optic cup (OC) segmentation. RETFound is a well-

Generalization Properties of Score-matching Diffusion Models for Intrinsically Low-dimensional Data

arXiv:2603.03700v2 Announce Type: replace-cross Abstract: Despite the remarkable empirical success of score-based diffusion models, their statistical guarantees remain underdeveloped. Existing analyse

Generative Discovery of Magnetic Insulators under Competing Physical Constraints

arXiv:2604.21073v1 Announce Type: cross Abstract: Discovering materials that must simultaneously satisfy multiple competing constraints remains a central challenge in computational materials design, p

GRISP: Guided Recurrent IRI Selection over SPARQL Skeletons

arXiv:2604.21133v1 Announce Type: new Abstract: We present GRISP (Guided Recurrent IRI Selection over SPARQL Skeletons), a novel SPARQL-based question-answering method over knowledge graphs based on f

GS-Quant: Granular Semantic and Generative Structural Quantization for Knowledge Graph Completion

arXiv:2604.21649v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown immense potential in Knowledge Graph Completion (KGC), yet bridging the modality gap between continuous graph em

Health-care AI is here. We don’t know if it actually helps patients.

I don’t need to tell you that AI is everywhere. Or that it is being used, increasingly, in hospitals. Doctors are using AI to help them with notetaking. AI-based tools are trawling through patient rec

researchmit-tech-review

HHL with a Coherent Fourier Oracle: A Proof-of-Concept Quantum Architecture for Joint Melody-Harmony Generation

arXiv:2604.20882v1 Announce Type: cross Abstract: Quantum algorithms with a proven theoretical speedup over classical computation are rare. Among the most prominent is the Harrow-Hassidim-Lloyd (HHL)

Higher Order Approximation Rates for ReLU CNNs in Korobov Spaces

arXiv:2501.11275v2 Announce Type: replace Abstract: This paper investigates the L_p approximation error for higher order Korobov functions using deep convolutional neural networks (CNNs) with ReLU act

How Much Is One Recurrence Worth? Iso-Depth Scaling Laws for Looped Language Models

arXiv:2604.21106v1 Announce Type: cross Abstract: We measure how much one extra recurrence is worth to a looped (depth-recurrent) language model, in equivalent unique parameters. From an iso-depth swe

Human Presence Detection via Wi-Fi Range-Filtered Doppler Spectrum on Commodity Laptops

arXiv:2603.10845v3 Announce Type: replace-cross Abstract: Human Presence Detection (HPD) is key to enable intelligent power management and security features in everyday devices. In this paper we propo