research

Towards Accurate State Estimation: Motion Dynamics Kalman Filter for 3D Multi-Object Tracking

arXiv:2505.07254v2 Announce Type: replace Abstract: Precise 3D state estimation in multi-object tracking (MOT) is critical for self-driving cars, particularly for objects occluded. Motion modeling in

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Towards Developing a Multimodal Chat Assistant for University Stakeholders: RAG-based Approach

DGX agent

arXiv:2607.01115v1 Announce Type: cross Abstract: University stakeholders often face difficulties in accessing timely and reliable information, especially in developing countries, where there are very

researcharxiv-cs-ai

2 Jul 2026

Towards Robust Driving Perception: A Flexible Scale-Driven Family for Self-Supervised Monocular Depth Estimation

arXiv:2607.00736v1 Announce Type: new Abstract: Self-Supervised Monocular Depth Estimation (MDE) has garnered attention in recent years due to its independence from ground truth. However, most existin

Towards Weaker Variance Assumptions for Stochastic Optimization

arXiv:2504.09951v2 Announce Type: replace-cross Abstract: We revisit a classical assumption for analyzing stochastic gradient algorithms where the squared norm of the stochastic subgradient (or the va

TRACE: State-Aware Query Processing over Temporal Evidence Graphs for Conversational Data

arXiv:2607.00339v1 Announce Type: new Abstract: Conversational data is increasingly used as a persistent source of user state for long-running assistants and AI agents. However, querying this data rem

TRCGL-Net: A Long-Tailed Multi-Label Chest X-Ray Classification Framework with Generative Data Augmentation and Label Co-Occurrence Modeling

arXiv:2607.00975v1 Announce Type: cross Abstract: Chest X-ray multi-label classification is a core task in intelligent medical imaging diagnosis. However, real clinical data often exhibit extreme long

Triangular Consistency as a Universal Constraint for Learning Optical Flow

arXiv:2606.19938v2 Announce Type: replace-cross Abstract: We propose triangular consistency as a first-principled constraint for optical flow, which is agnostic to network architecture, supervision ty

Trust the Prior (or Not): Uncertainty-Aware Abdominal Aortic Aneurysm Segmentation

arXiv:2607.00201v1 Announce Type: new Abstract: Robust segmentation of intraluminal thrombus is critical for risk assessment in Abdominal Aortic Aneurysm, yet it remains challenging due to heterogeneo

Uncertainty-aware tree height change regression

arXiv:2607.00638v1 Announce Type: new Abstract: Monitoring canopy height change is essential for understanding carbon sinks and forest dynamics. Remote sensing enables consistent, large-scale observat

Understanding Guest Preferences and Optimizing Two-sided Marketplaces: Airbnb as an Example

arXiv:2607.00280v1 Announce Type: new Abstract: Airbnb is a community based on connection and belonging -- many hosts on Airbnb are everyday people who share their worlds to provide guests with the fe

Understanding Large Language Models

arXiv:2607.01006v1 Announce Type: new Abstract: Large Language Models (LLMs) represent one of the most significant advances in AI and natural language processing in recent years. Still, many pressing

Unexplainability of Artificial Intelligence Judgments and Functional Implementation in Kant's Perspective

arXiv:2407.18950v5 Announce Type: replace Abstract: Kant's Critique of Pure Reason, a major contribution to the history of epistemology, proposes a table of categories to elucidate the structure of th

Unifying Convolution and Attention via Convolutional Nearest Neighbors

arXiv:2511.14137v3 Announce Type: replace Abstract: Convolutional Neural Networks and Vision Transformers are the two dominant architectural families in computer vision, defined by spatially local con

Unsurprisingly, all of the strong contenders on ARC-AGI-3 so far use this type of approach.

researchfrancois-chollet--x

François Chollet observed that all leading contenders on the ARC-AGI-3 benchmark employ a similar methodological approach, suggesting a convergence in techniques for solving abstract reasoning tasks.

Utilizing Earth Foundation Models to Enhance the Simulation Performance of Hydrological Models with AlphaEarth Embeddings

arXiv:2601.01558v2 Announce Type: replace-cross Abstract: Predicting river flow in places without streamflow records is challenging because basins respond differently to climate, terrain, vegetation,

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

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

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