research

Valdi: Value Diffusion World Models

arXiv:2607.00917v1 Announce Type: cross Abstract: World models can enable Model Predictive Control (MPC), but this requires dynamics prediction that is both fast enough for online use and expressive e

Vertigo Vertigo: Reconstructing a Cinematic Ideal through its Predictive AI Double

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arXiv:2607.00047v1 Announce Type: cross Abstract: Vertigo Vertigo is a scene-for-scene AI reconstruction of Hitchcock's Vertigo (1958), generated from only 2.78% of the original film's frames. Using t

researcharxiv-cs-cv

2 Jul 2026

Vibe Coding Ate My Homework: An evaluation of AI approaches to greenfield software engineering and programming

arXiv:2606.18293v2 Announce Type: replace-cross Abstract: Thanks to rapid developments in generative AI, we are in the midst of a paradigm shift that may change how we interact with computers forever.

Visualizing Impedance Control in Augmented Reality for Teleoperation: Design and User Evaluation

arXiv:2603.25418v2 Announce Type: replace Abstract: Teleoperation for contact-rich manipulation remains challenging, especially when using low-cost, motion-only interfaces that provide no haptic feedb

researcharxiv-cs-ro

Vitality-Aware Compression for Efficient Image-to-Shape Diffusion Transformers

arXiv:2607.00382v1 Announce Type: new Abstract: We propose the first compression approach for image-to-shape Diffusion Transformers (DiTs) that substantially reduces model size while preserving geomet

VOCA: Visual Odometry with Codec Awareness

arXiv:2607.00189v1 Announce Type: new Abstract: Camera pose estimation from image streams is a critical component of spatial world models that integrate perception into planning and decision-making. N

Watermarking for Proprietary Dataset Protection

arXiv:2607.00325v1 Announce Type: cross Abstract: A growing body of literature suggests that training data membership inference problems are fundamentally hard tasks in modern language modeling settin

We don’t take stakes in healthy companies. Proposing that as last ditch regulatory capture attempt in commodity market is 😢 … or at best un…

We don’t take stakes in healthy companies. Proposing that as last ditch regulatory capture attempt in commodity market is 😢 … or at best un-American disingenuous WWE politics, not pro-market, not pro-

researchyann-lecun--x

🔥 We introduce LeVLJEPA: the first fully non-contrastive end-to-end vision-language pretraining method competitive with CLIP & SigLIP 💪🏼 …

🔥 We introduce LeVLJEPA: the first fully non-contrastive end-to-end vision-language pretraining method competitive with CLIP & SigLIP 💪🏼 👀 No negatives. No temperature. No momentum encoder. No teacher

researchyann-lecun--x

What Survives Into Context: A Diagnostic for Budget-Constrained Multi-Hop RAG and When Submodular Evidence Packing Improves It

arXiv:2607.00725v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) under a fixed reader-context budget forces a selection problem: of the evidence retrieved, only a fraction can be s

What's a Credit Worth? A Market Framework for Attribution-Aware Compensation in Generative Music

arXiv:2607.00641v1 Announce Type: cross Abstract: Advances in generative AI are rapidly increasing the quality and commercial value of generated music, and this progress depends on large catalogs of c

When AI meets quantum information: A comprehensive review

arXiv:2607.00365v1 Announce Type: cross Abstract: Artificial intelligence (AI) and quantum information (QI) are rapidly co-evolving. AI is becoming a practical tool for learning, designing, controllin

When Classic Cache Policies Fail: Learning-Augmented Replacement for Semantic Retrieval Buffers

arXiv:2607.00394v1 Announce Type: cross Abstract: LLM agents increasingly rely on retrieval buffers to store and reuse past experience, yet the cache management policies governing these buffers remain

When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models

arXiv:2512.18934v2 Announce Type: replace-cross Abstract: Catastrophic forgetting poses a fundamental challenge in continual learning, particularly when models are quantized for deployment efficiency.

Which Metric Reflects the Spelling Rate Accuracy in Event-Related Potential-Based Brain-Computer Interfaces?

arXiv:2607.00794v1 Announce Type: new Abstract: For predictive models, the often-reported performance metrics are the loss and accuracy. In synchronous Brain- Computer Interface (BCI) systems, these m

Why California’s carbon manure math doesn’t add up

Something stinks in California’s climate policies. Years ago, the state set up a system that pays cattle farmers across the country to turn the methane emitted from cattle manure into natural gas, enc

researchmit-tech-review

World from Motion: Generative Dynamic Gaussian Reconstruction from Monocular Video

arXiv:2607.01202v1 Announce Type: cross Abstract: We present World from Motion, a method for generating freely renderable dynamic 3D Gaussian representations from monocular videos. Our approach condit

1/ On Training in Imagination - Dwarkesh's episode has a segment on dreaming as one of the next training paradigms. The idea is that a model…

1/ On Training in Imagination - Dwarkesh's episode has a segment on dreaming as one of the next training paradigms. The idea is that a model learns mostly inside its own, by imagining what would happe

researchyann-lecun--x

2DGH: 2D Gaussian-Hermite Splatting for High-quality Rendering and Better Geometry Features

arXiv:2408.16982v2 Announce Type: replace Abstract: 2D Gaussian Splatting has recently emerged as a significant method in 3D reconstruction, enabling novel view synthesis and geometry reconstruction s

A Bayesian Filtering Approach for Learning Lagrangian Dynamics from Noisy Measurements

arXiv:2606.31137v1 Announce Type: new Abstract: This paper proposes a Bayesian filtering-based approach for learning the dynamics of a physical system from partial, noisy measurements. We model the sy

A Coherence Law for Trainability in Noisy Equivariant Quantum Neural Networks

arXiv:2606.30688v1 Announce Type: cross Abstract: Symmetry provides a quantum neural network structure, but on its own it does not keep the network trainable once noise is present. We ask which physic

A Unified and Stable Risk Minimization Framework for Weakly Supervised Learning with Theoretical Guarantees

arXiv:2511.22823v2 Announce Type: replace-cross Abstract: Weakly supervised learning has emerged as a practical alternative to fully supervised learning when complete and accurate labels are costly or

AA: A Multi-view Multimodal Dataset for Screen-based Gaze Estimation

arXiv:2606.31211v1 Announce Type: new Abstract: We present AA, a multi-view multimodal dataset for screen-based gaze estimation. The dataset captures synchronized facial observations from eight fixed

Accelerated Likelihood Maximization for Diffusion-based Versatile Content Generation

arXiv:2606.31323v1 Announce Type: new Abstract: Generating diverse, coherent, and plausible content from partially given inputs remains a fundamental challenge for diffusion models. Existing approache

Accelerating Conformal Prediction via Approximate Leave-One-Out

arXiv:2606.31915v1 Announce Type: cross Abstract: While conformal prediction provides a general framework for uncertainty quantification in predictive inference, its application is often limited by co

Accelerating Merge with Motion Vector Difference via Filter Difference Analysis for VVenC

arXiv:2606.31084v1 Announce Type: cross Abstract: Merge with Motion Vector Difference (MMVD) is a key coding tool in Versatile Video Coding for improving motion prediction accuracy. However, its exhau

AdaJEPA: An Adaptive Latent World Model

arXiv:2606.32026v1 Announce Type: cross Abstract: Latent world models enable planning from high-dimensional observations by predicting future states in a compact latent space. However, these models ar

AI Transparency: Governance Compliance or Stakeholder Requirements?

arXiv:2606.30652v1 Announce Type: cross Abstract: Transparency is increasingly mandated for public-sector AI systems, with organisations required to publish statements describing their AI use and over

ALM2Vec: Learning Audio Embeddings for Universal Audio Retrieval with Large Audio-Language Models

arXiv:2606.30682v1 Announce Type: cross Abstract: Recent advances in language--audio retrieval have been largely driven by contrastive dual-encoder architectures that align audio and text in a shared

Amplifying Membership Signal Through Chained Regeneration

arXiv:2606.31991v1 Announce Type: cross Abstract: The tendency of large generative models to memorize training data makes sample verification critical for privacy auditing and copyright enforcement. C

ASR-Agnostic Multimodal Spectrotemporal Modeling for Early Dementia Detection

arXiv:2606.30646v1 Announce Type: cross Abstract: Speech recruits the same executive, attentional, and working memory processes underlying instrumental activities of daily living, or IADLs, providing

Attend, Transform, or Silence: Operator-Level Visual Skipping for Efficient Multimodal LLM Inference

arXiv:2606.31903v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) increasingly process long visual-token sequences, increasing the overall inference computation. Existing acce

Auditing Generalization in AI-Generated Video Detection: A Six-Control Protocol and the VidAudit Toolkit

arXiv:2606.31004v1 Announce Type: new Abstract: AI-generated video detection benchmarks such as GenVidBench and AIGVDBench are the de facto leaderboards, yet most evaluation protocols leave uncontroll

AugSplat: Radiance Field-Informed Gaussian Splatting for Sparse-View Settings

arXiv:2606.31556v1 Announce Type: new Abstract: Generating high-quality novel views at real-time frame rates remains a central challenge in 3D vision, particularly in sparse-view scenarios. Neural rad

Automated Background Swapping for Robustness against Spurious Backgrounds

arXiv:2606.32018v1 Announce Type: new Abstract: Classifiers based on Deep Neural Networks exhibit strong performance across domains, yet can fail catastrophically if they rely on spurious correlations

Automated Discovery of Operable Dynamics from Videos

arXiv:2410.11894v3 Announce Type: replace-cross Abstract: Dynamical systems form the foundation of scientific discovery, traditionally modeled with predefined state variables such as the angle and ang

Belief Contraction in Dynamic Epistemic Logic

arXiv:2606.31861v1 Announce Type: cross Abstract: Dynamic epistemic logic represents belief change via model transformations induced by epistemic events. Its standard formulation (Baltag, Moss, Soleck

BEST-RQ-2: Contextualize-Then-Predict, a Two-Step Approach for Self-Supervised Audio Representations

arXiv:2606.30700v1 Announce Type: cross Abstract: Self-supervised learning enables audio representations that transfer across domains and tasks. We present BEST-RQ-2, an evolution of BEST-RQ that reta

Beyond But-for Test: Counterfactual Explanation in Abstract Argumentation via Actual Causality (Extended Version)

arXiv:2606.31080v1 Announce Type: cross Abstract: Counterfactual explanation in abstract argumentation calls for an answer to the what-if query: would the topic argument still be accepted if the statu

Bridging the Gap Between Latent and Explicit Reasoning with Looped Transformers

arXiv:2606.31779v1 Announce Type: cross Abstract: Language models typically reason via explicit chain-of-thought (CoT), generating intermediate steps token-by-token. Latent CoT offers an alternative:

Bridging Video Understanding and Generation in a Unified Framework

arXiv:2606.31326v1 Announce Type: new Abstract: Recently, unified image generation and understanding have been extensively explored. However, extending such unified modeling paradigms to the video dom

Budget-Adaptive Routing: Skipping the Weak When the Strong Answers Anyway

arXiv:2606.30919v1 Announce Type: cross Abstract: Edge-cloud inference collaborations are often designed with a routing estimator that decides whether to offload each frame from weak models at the edg

Can VLMs Reason Robustly? A Neuro-Symbolic Investigation

arXiv:2603.23867v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) have been applied to a wide range of reasoning tasks, yet it remains unclear whether they can reason robustly un

CharDiff-LP: A Diffusion Model with Character-Level Guidance for License Plate Image Restoration

arXiv:2510.17330v3 Announce Type: replace-cross Abstract: License plate image restoration is important not only as a preprocessing step for license plate recognition but also for enhancing evidential

Combined Constrained Sampling and Reinforcement Learning for Robotic Manipulation

arXiv:2602.08557v2 Announce Type: replace Abstract: Training non-prehensile manipulation policies in contact-rich settings is a core challenge in robotics. While Reinforcement Learning (RL) has demons

researcharxiv-cs-ro

CoMet: Context and Multiplicity Decomposition for Multimodal Uncertainty Estimation

arXiv:2606.32012v1 Announce Type: cross Abstract: Uncertainty estimation has been a long-standing challenge in AI models; it amounts to 'knowing what you don't know,' and metacognition is notoriously

Communication-Aware Robot Execution for Cloud Inference under Spatially Heterogeneous Connectivity

arXiv:2606.31497v1 Announce Type: new Abstract: Cloud-hosted foundation models enable robots to use semantic reasoning beyond onboard computational limits. In this setting, the robot executes a curren

researcharxiv-cs-ro

Conditional Tropical Cyclogenesis Rates via Rare-Event Sampling in a Neural Weather Emulator

arXiv:2606.30920v1 Announce Type: cross Abstract: We couple Forward Flux Sampling (FFS), a non-equilibrium rare-event technique from statistical mechanics, to a neural weather emulator (SDL-WXFormer,