Search: “research”

Improving 3D Labeling in Self-Driving by Inferring Vehicle Information using Vision Language Models

arXiv:2605.21747v1 Announce Type: new Abstract: We present an approach to improve 3D vehicle labeling in self-driving applications through zero-shot inference of vehicle information, leveraging Vehicl

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Research

Improving Viewpoint-Invariance and Temporal Consistency for Action Detection

DGX agent

arXiv:2605.22695v1 Announce Type: new Abstract: Viewpoint change invariance and action temporal consistency are critical aspects for the effective deployment of human action detection of untrimmed vid

researcharxiv-cs-cv

22 May 2026

In Silico Modeling of the RAMPHO Buffer: Dissociating Informational and Energetic Masking via Phonetic Entropy in Deep Neural Networks

arXiv:2605.22465v1 Announce Type: new Abstract: The fundamental challenge of listening in multi-talker environments is a cognitive bottleneck, defined by the Ease of Language Understanding (ELU) model

Industrial Dual-Arm Box Handling via Online Inertial Estimation and Convex Wrench Optimization

arXiv:2605.22021v1 Announce Type: new Abstract: Industrial robotic object handling often involves boxes and packages whose mass and center of mass are not known in advance. These uncertainties affect

Internal narratives parameterise affective states

arXiv:2502.09487v3 Announce Type: replace Abstract: Characterising how we verbalise our feelings is central to psychological assessment and intervention, yet the mapping between narrative and affectiv

Interpreting and Enhancing Emotional Circuits in Large Vision-Language Models via Cross-Modal Information Flow

arXiv:2605.21980v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) represent a significant leap towards empathetic agents, demonstrating remarkable capabilities in emotion understand

Label tree semantic losses for rich multi-class medical image segmentation

arXiv:2507.15777v3 Announce Type: replace Abstract: Rich and accurate medical image segmentation is poised to underpin the next generation of AI-defined clinical practice by delineating critical anato

LatentOmni: Rethinking Omni-Modal Understanding via Unified Audio-Visual Latent Reasoning

arXiv:2605.22012v1 Announce Type: new Abstract: Joint audio-visual reasoning is essential for omnimodal understanding, yet current multimodal large language models (MLLMs) still struggle when reasonin

LFX: Towards Unified Light Field Dense Semantic Segmentation and Salient Object Detection

arXiv:2503.00747v2 Announce Type: replace Abstract: Light field cameras capture multi-view observations within a single exposure. However, existing studies are typically tailored to specific LF repres

LightReasoner: Can Small Language Models Teach Large Language Models Reasoning?

arXiv:2510.07962v2 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated remarkable progress in reasoning, often through supervised fine-tuning (SFT). However, SFT is resourc

Model Releases

M3: Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis

model-releasesarxiv-cs-ai

arXiv:2507.01053v4 Announce Type: replace-cross Abstract: Large-scale clinical databases offer opportunities for medical research, but their complexity creates barriers to effective use. The Medical I

Mind the Gaps: Multi-Robot Feedback-Driven Ergodic Coverage in Unknown Environments

arXiv:2605.21719v1 Announce Type: new Abstract: In this work, we address the problem of multi-robot adaptive coverage, where teams of robots perform dynamic sampling by continuously adjusting their po

More Context, Larger Models, or Moral Knowledge? A Systematic Study of Schwartz Value Detection in Political Texts

arXiv:2605.22641v1 Announce Type: new Abstract: Detecting Schwartz values in political text is difficult because implicit cues often depend on surrounding arguments and fine-grained distinctions betwe

Motion Design for Grasp-Based Dynamic Locomotion in Microgravity

arXiv:2605.21704v1 Announce Type: new Abstract: Locomotion in microgravity often relies on sparsely and irregularly arranged anchors, motivating grasp-based mobility with multiple limbs. In this setti

MotionDPS: Motion-Compensated 3D Brain MRI Reconstruction

arXiv:2605.22121v1 Announce Type: new Abstract: Magnetic resonance imaging (MRI) is highly susceptible to patient motion due to its relatively long acquisition times and the fact that data are acquire

Model Releases

MOTOR: A Multimodal Dataset for Two-Wheeler Rider Behavior Understanding

model-releasesarxiv-cs-cv

arXiv:2605.22550v1 Announce Type: new Abstract: Two-wheelers account for a disproportionately high share of road fatalities in the Global South. Research on two-wheeler rider behavior, however, lags f

MRecover: A Conditional Generative Model for Recovering Motion-Corrupted MR images Using AI Generated Contrast

arXiv:2605.21669v1 Announce Type: new Abstract: Hippocampal subfield segmentation requires high-resolution T2w turbo spin echo (TSE) MRI, yet this sequence is susceptible to motion artifacts, leading

MuKV: Multi-Grained KV Cache Compression for Long Streaming Video Question-Answering

arXiv:2605.22269v1 Announce Type: new Abstract: Long streaming video QA remains challenging due to growing visual tokens and limited reasoning length of large language models (LLMs). KV-caching stores

Multi-scale interaction network for stereo image super-resolution

arXiv:2605.21913v1 Announce Type: new Abstract: Stereo image super-resolution aims to generate high-resolution images by leveraging complementary information from binocular systems. Although previous

Multi-Stage Training for Abusive Comment Detection in Indic Languages

arXiv:2605.22380v1 Announce Type: new Abstract: In recent years social media has become an increasingly popular tool for communication. People use it to share their ideas, exchange information, and di

My new article 'Toward a science of intelligence: unifying physics, neuroscience and AI' https://www.amacad.org/publication/daedalus/toward-…

My new article 'Toward a science of intelligence: unifying physics, neuroscience and AI' https://www.amacad.org/publication/daedalus/toward-science-of-intelligence-unifying-physics-neuroscience-ai pub

researchyann-lecun--x

No Pose, No Problem in 4D: Feed-Forward Dynamic Gaussians from Unposed Multi-View Videos

arXiv:2605.22190v1 Announce Type: new Abstract: Recent feed-forward 3D gaussian splatting methods have made dramatic progress on individual aspects of 3D scene reconstruction, but no existing method j

OCELOT: Odometry and Contact Estimation for Legged Robots

arXiv:2605.21863v1 Announce Type: new Abstract: One of the significant challenges in legged robotics is achieving accurate odometry using only onboard proprioceptive sensors. In this study, we present

On the Complexity of Entailment for Cumulative Propositional Dependence Logics

arXiv:2605.21113v1 Announce Type: cross Abstract: This paper establishes and proves complexity results for entailment for cumulative propositional dependence logic and for cumulative propositional log

One prompt is not enough: Instruction Sensitivity Undermines Embedding Model Evaluation

arXiv:2605.22544v1 Announce Type: new Abstract: Instruction embedding models have become common among state-of-the-art models, however are evaluated using a single prompt per task. The single-point ev

Optical Quantum Mixed-State Reconstruction With Multiple Deep Learning Approaches

arXiv:2407.01734v4 Announce Type: replace-cross Abstract: Quantum state tomography is a crucial technique for characterizing the state of a quantum system, which is essential for many applications in

Pattern-and-root inflectional morphology: the Arabic broken plural

arXiv:2605.22310v1 Announce Type: new Abstract: We present a substantially implemented model of description of the inflectional morphology of Arabic nouns, with special attention to the management of

PIU: Proximity-guided Identity Unlearning in ID-Conditioned Diffusion Models

arXiv:2605.22311v1 Announce Type: new Abstract: Identity-conditioned diffusion models enable high-quality and identity-consistent face generation, but they also raise severe privacy concerns, as model

PolycubeNet: A Dual-latent Diffusion Model for Polycube-Based Hexahedral Mesh Generation

arXiv:2605.20274v1 Announce Type: cross Abstract: Hexahedral meshes are widely used in simulation pipelines, yet automatic generation remains challenging for complex CAD geometries. Polycube-based hex

Probabilistic Attribution For Large Language Models

arXiv:2605.21726v1 Announce Type: new Abstract: The generative nature of Large Language Models (LLMs) is reflected in the conditional probabilities they compute to sample each response token given the

Proportional Selection in Networks

arXiv:2502.03545v2 Announce Type: replace-cross Abstract: We address the problem of selecting k representative nodes from a network, aiming to achieve two objectives: identifying the most influential

Quantifying Full-Body Immersion

arXiv:2605.22521v1 Announce Type: new Abstract: Humanity is at the forefront of yet another digital revolution, where the lines between real and virtual worlds are dissolving, reshaping how we perceiv

REACH: Hand Pose Estimation from Room Corners

arXiv:2605.22231v1 Announce Type: new Abstract: We introduce a novel 3D hand pose estimator that can accurately recover the shape and pose of people's hands in a room from afar, typically from fixed c

Real-Time Auto-Optimization in Unknown Environments via Structure-Exploiting Dual Control for Exploration and Exploitation

arXiv:2605.22431v1 Announce Type: new Abstract: This paper develops a fast numerical dual control for exploration and exploitation (DCEE) method to address auto-optimization problems in unknown enviro

Representability-Aware Neural Networks for Reduced Density Matrices: Application to Fractional Chern Insulators

arXiv:2605.20326v1 Announce Type: cross Abstract: We develop a representability-aware and interpolable neural network (NN) framework for predicting two-particle reduced density matrices (2-RDMs). The

Rethinking Token Reduction for Diffusion Models via Output-Similarity-Awareness

arXiv:2605.22011v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve superior image generation quality but suffer from quadratic computational complexity relative to token count. Whil

Revisiting Integration of Image and Metadata for DICOM Series Classification: Cross-Attention and Dictionary Learning

arXiv:2602.23833v2 Announce Type: replace-cross Abstract: Automated identification of DICOM image series is essential for large-scale medical image analysis, quality control, protocol harmonization, a

RiT: Vanilla Diffusion Transformers Suffice in Representation Space

arXiv:2605.21981v1 Announce Type: new Abstract: Flow matching with x-prediction -- regressing the clean data point rather than the ambient velocity -- is known to exploit low-dimensional manifold stru

RobuQ: Pushing DiTs to W1.58A2 via Robust Activation Quantization

arXiv:2509.23582v2 Announce Type: replace Abstract: Diffusion Transformers (DiTs) have recently emerged as a powerful backbone for image generation, demonstrating superior scalability and performance

Robustness of breast lesion segmentation under MRI undersampling improves with k-space-aware deep learning

arXiv:2605.22327v1 Announce Type: new Abstract: Purpose: To assess whether breast lesion segmentation can be learned directly from acquired MRI k-space, and whether doing so improves robustness when d

Scene Abstraction for Lexical Semantics: Structured Representations of Situated Meaning

arXiv:2605.22542v1 Announce Type: new Abstract: Coffee and tea share many properties, yet they evoke strikingly different situations, atmospheres, and affective associations. These situated dimensions

SEGA: Spectral-Energy Guided Attention for Resolution Extrapolation in Diffusion Transformers

arXiv:2605.22668v1 Announce Type: new Abstract: Diffusion transformers (DiTs) have emerged as a dominant architecture for text-to-image generation, yet their performance drops when generating at resol

Sem-Detect: Semantic Level Detection of AI Generated Peer-Reviews

arXiv:2605.21713v1 Announce Type: new Abstract: How can we distinguish whether a peer review was written by a human or generated by an AI model? We argue that, in this setting, authorship should not b

Slimmable ConvNeXt: Width-Adaptive Inference for Efficient Multi-Device Deployment

arXiv:2605.22677v1 Announce Type: new Abstract: Deploying vision models across devices with varying resource constraints, or even on a single device where available compute fluctuates due to battery s

SO-Mamba: State-Ownership Mamba for Unrolled MRI Reconstruction

arXiv:2605.22031v1 Announce Type: new Abstract: Accelerated MRI reconstruction requires recovering missing details while preserving anatomically coherent structures across large spatial regions. State

SPIRAL: Self-Evolving Action-Conditioned Video Generation via Reflective Planning Agents

arXiv:2603.08403v3 Announce Type: replace Abstract: Long-horizon action-conditioned video generation aims to synthesize temporally coherent videos that follow complex action instructions over extended

ST-SimDiff: Balancing Spatiotemporal Similarity and Difference for Efficient Video Understanding with MLLMs

arXiv:2605.22158v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) face significant computational overhead when processing long videos due to the massive number of visual token

Swift Sampling: Selecting Temporal Surprises via Taylor Series

arXiv:2605.22678v1 Announce Type: new Abstract: While most frames in long-form video are redundant, the critical information resides in temporal surprises: moments where the actual visual features dev