research

HAD: Hallucination-Aware Diffusion Priors for 3D Reconstruction

arXiv:2605.16873v1 Announce Type: new Abstract: Diffusion priors have recently demonstrated strong capability in enhancing the quality of sparse-view 3D reconstruction by augmenting training views at

Haptic Rendering of Fractional-Order Viscoelasticity: Passivity and Rendering Fidelity

DGX agent

arXiv:2605.16389v1 Announce Type: cross Abstract: Haptic rendering of viscoelastic materials that exhibit creep and stress relaxation is crucial for many applications, such as medical training with re

researcharxiv-cs-ai

19 May 2026

HDTree: Generative Modeling of Cellular Hierarchies for Robust Lineage Inference

arXiv:2506.23287v3 Announce Type: replace Abstract: In single-cell research, tracing and analyzing high-throughput single-cell differentiation trajectories is crucial for understanding biological proc

Here’s why Elon Musk lost his suit against OpenAI

On Monday, the jury in Musk v. Altman dealt Elon Musk a major blow—reaching a unanimous advisory verdict that he had sued OpenAI too late and, as a result, his claims are barred by the applicable stat

researchmit-tech-review

HexagonalWarriorMamba: Superior Threshold-Dependent Multi-label Classification of 12-Lead ECG Cardiac Abnormalities

arXiv:2605.17875v1 Announce Type: new Abstract: The accurate automated diagnosis of cardiac abnormalities from 12-lead electrocardiograms (ECGs) is critical for managing cardiovascular disease. Howeve

Hierarchical Two-Stage Framework for Environment-Aware Long-Horizon Vessel Trajectory Prediction

arXiv:2605.16442v1 Announce Type: cross Abstract: Long-horizon vessel trajectory forecasting under real ocean conditions is critical for collision avoidance, traffic management, and route planning. Ho

High-dimensional Limit of SGD for Diagonal Linear Networks

arXiv:2605.17177v1 Announce Type: cross Abstract: Understanding the behavior of stochastic gradient methods is a central problem in modern machine learning. Recent work has highlighted diagonal linear

Historical Knowledge Graphs for Global Maritime Estimated Time of Arrival

arXiv:2605.18408v1 Announce Type: new Abstract: Accurate vessel estimated-time-of-arrival forecasts are critical for port operations and decarbonization, yet global-scale travel-time prediction remain

HL-OutPaint: Coarse-to-Fine Video Outpainting for High-Resolution Long-Range Videos

arXiv:2605.17543v1 Announce Type: new Abstract: Video outpainting generates plausible visual content beyond the original spatial extent of a video, playing a key role in adapting videos to diverse dis

How do Humans Process AI-generated Hallucination Contents: a Neuroimaging Study

arXiv:2605.16953v1 Announce Type: new Abstract: While AI-generated hallucinations pose considerable risks, the underlying cognitive mechanisms by which humans can successfully recognize or be misled b

How do we design materials with AI? Excited to introduce Crys-JEPA, a new generative technique in collaboration w/ @liun_online, Kostya Novo…

How do we design materials with AI? Excited to introduce Crys-JEPA, a new generative technique in collaboration w/ @liun_online, Kostya Novoselov, @ylecun & team. We achieved 47.9% VSUN on MP20 by bui

researchyann-lecun--x

How does loss functions work in PINN? [D]

researchr-machinelearning

Physics-informed neural networks (PINNs) use specialized loss functions that combine data-fitting terms with physics constraints derived from differential equations, allowing the network to learn solu

Human-Certified Module Repositories for the AI Age

arXiv:2603.02512v4 Announce Type: replace-cross Abstract: Human-Certified Module Repositories (HCMRs) are introduced in this work as a new architectural model for constructing trustworthy software in

Hybrid Feature Combinations with CNN for Bangla Fake News Classification

arXiv:2605.17481v1 Announce Type: new Abstract: Nowadays, people in Bangladesh frequently rely on the internet and social media for daily news instead of traditional newspapers. However, the spread of

Hybrid Quantum-Classical Neural Architecture Search

arXiv:2605.18345v1 Announce Type: cross Abstract: Hybrid quantum-classical neural networks (HQNNs) are emerging as a practical approach for quantum machine learning in the noisy intermediate-scale qua

HyperVision: A Channel-Adaptive Ground-Based Hyperspectral Vision Pre-trained Backbone

arXiv:2605.17286v1 Announce Type: new Abstract: While hyperspectral imaging provides rich spatial-spectral information across hundreds of narrow wavelength bands for precise material identification, g

I built a tool that shows you what GPT-2 is 'thinking' in real-time as it generates 3D graph of concept activations per token [R]

researchr-machinelearning

A developer created a visualization tool that displays GPT-2's internal concept activations in real-time during text generation, representing the model's 'thinking' process as a 3D graph that updates

Identify Then Project: Contrastive Learning of Latent Dynamics from Partial Observations with Port-Hamiltonian Structure

arXiv:2605.16682v1 Announce Type: new Abstract: Identifying latent state representations and dynamics is essential when direct modeling in observation space is infeasible, particularly under partial a

Image-to-Video Diffusion: From Foundations to Open Frontiers

arXiv:2605.17248v1 Announce Type: new Abstract: Diffusion-based extit{image-to-video} (I2V) generation has become a central direction in generative models by turning a reference image, with optional c

Imaging Hidden Objects with Consumer LiDAR via Motion Induced Sampling

arXiv:2605.17865v1 Announce Type: new Abstract: LiDARs are being increasingly deployed for consumer imaging in handheld, wearable, and robotic applications. These sensors can capture the time-of-fligh

Inducing Spatial Locality in Vision Transformers through the Training Protocol

arXiv:2605.16390v1 Announce Type: new Abstract: We investigate whether the training protocol can induce spatial locality in the early layers of a Vision Transformer (ViT) trained from scratch, without

Infini-News: Efficiently Queryable Access to 1.3 Billion Processed Common Crawl News Articles

arXiv:2605.18337v1 Announce Type: new Abstract: Large-scale news corpora support a wide range of research in Computational Social Science and NLP, yet access remains constrained: commercial archives i

Information-Theoretic Storage Cost in Sentence Comprehension

arXiv:2602.18217v2 Announce Type: replace Abstract: Real-time sentence comprehension imposes a significant load on working memory, as comprehenders must maintain contextual information to anticipate f

InstructAV2AV: Instruction-Guided Audio-Video Joint Editing

arXiv:2605.18467v1 Announce Type: new Abstract: Recent diffusion-based methods have achieved impressive progress in video content manipulation. However, they typically ignore the accompanying audio, l

Integration of AI in Cybersecurity: Current Trends with a Focused Look at Intrusion Detection Applications

arXiv:2605.17219v1 Announce Type: cross Abstract: Artificial Intelligence (AI) is widely adopted today for its ability to detect patterns, automate tasks, and reduce time and cost across various appli

Inter-LPCM: Learning-based Inter-Frame Predictive Coding for LiDAR Point Cloud Compression

arXiv:2605.18006v1 Announce Type: cross Abstract: Because LiDAR sensors acquire point clouds with a fixed angular resolution, the resulting data can be systematically parameterized and efficiently com

Is Complex Training Necessary for Long-Tailed OOD Detection? A Re-think from Feature Geometry

arXiv:2605.17799v1 Announce Type: new Abstract: Long-tailed out-of-distribution (LT-OOD) detection is often addressed with specialized training, including auxiliary out-of-distribution (OOD) data, abs

Iterative Chow Filtering for Learning with Distribution Shift

arXiv:2605.17251v1 Announce Type: cross Abstract: Recent work due to Goel et al. gave the first efficient algorithms for learning with distribution shift in the challenging PQ framework. In this setti

JSPG: Dynamic Dictionary Filtering via Joint Semantic-Pinyin-Glyph Retrieval for Chinese Contextual ASR

arXiv:2605.16896v1 Announce Type: new Abstract: Contextual Automatic Speech Recognition (ASR) faces challenges with large-scale keyword dictionaries, as excessive irrelevant candidates introduce noise

Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains

arXiv:2605.18261v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has demonstrated promising potential to enhance the reasoning capabilities of large language model

Language Acquisition Device in Large Language Models

arXiv:2605.16758v1 Announce Type: new Abstract: Large Language Models (LLMs) remain substantially less data-efficient than humans. Pre-pretraining (PPT) on synthetic languages has been proposed to clo

Language Models as Efficient Reward Function Searchers for Custom-Environment Multi-Objective Reinforcement

arXiv:2409.02428v4 Announce Type: replace-cross Abstract: Achieving the effective design and improvement of reward functions in reinforcement learning (RL) tasks with complex custom environments and m

Large Language Models and Impossible Language Acquisition: 'False Promise' or an Overturn of our Current Perspective towards AI

arXiv:2602.08437v5 Announce Type: replace Abstract: In Chomsky's provocative critique 'The False Promise of CHATGPT,' Large Language Models (LLMs) are characterized as mere pattern predictors that do

Latent Heuristic Search: Continuous Optimization for Automated Algorithm Design

arXiv:2605.17137v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into evolutionary frameworks has established a new paradigm for automated heuristic discovery. Despite t

Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators

arXiv:2601.20888v3 Announce Type: replace-cross Abstract: We study sampling from posterior distributions in Bayesian linear inverse problems where A, the parameters to observables operator, is computa

Lean Meets Theoretical Computer Science: Scalable Synthesis of Theorem Proving Challenges in Formal-Informal Pairs

arXiv:2508.15878v2 Announce Type: replace-cross Abstract: Formal theorem proving (FTP) has emerged as a critical foundation for evaluating the reasoning capabilities of large language models, enabling

Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural Refinement

arXiv:2605.17316v1 Announce Type: cross Abstract: Sensor networks increasingly govern modern infrastructure, yet the data they lose are rarely missing in the uniform-random patterns assumed by standar

Learning in Position-Aware Multinomial Logit Bandits: From Multiplicative to General Position Effects

arXiv:2605.17238v1 Announce Type: new Abstract: We study the dynamic joint assortment selection and positioning problem, where the attraction of each product depends on both its intrinsic appeal and i

Learning Lifted Action Models from Traces with Minimal Information About Actions and States

arXiv:2605.18627v1 Announce Type: new Abstract: It has been recently shown that lifted STRIPS models can be learned correctly and efficiently from action traces alone; i.e., applicable action sequence

Learning more physically realistic dynamics in machine-learning based weather forecasting with latent-space constraints

arXiv:2510.04006v2 Announce Type: replace Abstract: Data-driven machine learning (ML) models are reshaping weather forecasting and have shown the potential to accelerate and surpass traditional physic

Learning Normal Representations for Blood Biomarkers

arXiv:2605.18701v1 Announce Type: new Abstract: Blood-based biomarkers underpin clinical diagnosis and management, yet their interpretation relies largely on fixed population reference intervals that

Learning over Positive and Negative Edges with Contrastive Message Passing

arXiv:2605.17854v1 Announce Type: new Abstract: Conventional approaches to learning on graphs involve message passing along existing (i.e., positive) edges to update node features. However, these appr

Learning Quantifiable Visual Explanations Without Ground-Truth

arXiv:2605.18681v1 Announce Type: new Abstract: Explainable AI (XAI) techniques are increasingly important for the validation and responsible use of modern deep learning models, but are difficult to e

Learning spatially adaptive sparsity level maps for arbitrary convolutional dictionaries

arXiv:2602.21707v2 Announce Type: replace-cross Abstract: State-of-the-art learned reconstruction methods often rely on black-box modules that, despite their strong performance, raise questions about

Learning to Look Benign: Targeted Evasion of Malware Detectors via API Import Injection

arXiv:2605.18624v1 Announce Type: cross Abstract: Machine learning-based malware detectors are widely deployed in antivirus and endpoint detection systems, yet their reliance on static features makes

Learning Unbiased Permutations via Flow Matching

arXiv:2605.16755v1 Announce Type: cross Abstract: Learning permutations is fundamental to sorting, ranking, and matching, but existing differentiable methods based on entropy-regularized Sinkhorn prod

Learning Variable-Length Tokenization for Generative Recommendation

arXiv:2605.17779v1 Announce Type: new Abstract: Generative recommendation reformulates recommendation as next-token prediction over discrete semantic identifiers (IDs). A fundamental yet unexplored de

Lever: Speculative LLM Inference on Smartphones

arXiv:2605.16786v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly needed for interactive mobile applications, but high-quality models exceed the limited DRAM available on s