Search: “pretraining”

Opto-ViT-v2: Noise-Resilient On-Chip Fine-Tuning for Photonic Near-Sensor Vision Transformer Accelerators

model-releasesarxiv-cs-ai

arXiv:2607.19421v1 Announce Type: cross Abstract: Silicon-photonic (SiPh) accelerators have emerged as a promising platform for Vision Transformer (ViT) inference by performing matrix multiplications

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Seeing Before Generating: Object Perception Enhances Single-View 3D Reconstruction

DGX agent

arXiv:2607.18630v1 Announce Type: new Abstract: The relationship between object perception and reconstruction is well established in human vision, yet remains underexplored in computer vision. In this

model-releasesarxiv-cs-cv

23 Jul 2026

Self-supervision drives representational convergence in medical foundation models more than clinical supervision

arXiv:2607.20274v1 Announce Type: cross Abstract: Medical image encoders from different groups are increasingly treated as interchangeable, on the assumption that scale and clinical supervision concen

local-aiarxiv-cs-ai

Strength-Parity Ensembling with Parameter-Isolated Experts for Multi-Task Affect Recognition

arXiv:2607.16290v2 Announce Type: replace Abstract: Leading entries on the multi-task track of the 11th ABAW challenge rely on heavy ensembling, yet which member is worth adding to an already strong e

Synthetic and Derived Training Images for Campus Waste Detection: A Multi-Seed Evaluation with YOLOv8n

arXiv:2607.19535v2 Announce Type: new Abstract: Incorrect disposal can contaminate campus recycling streams, and a bin-mounted camera could provide feedback as an item is discarded. We evaluated wheth

Test-Time Registers as Global Priors for Tokenized Image Generation

arXiv:2607.16824v2 Announce Type: replace Abstract: Attention-based models often develop attention sinks, where a small number of tokens repeatedly attract attention and accumulate unusually large act

safetyarxiv-cs-cv

Toward Reliable RGB-D Semantic Segmentation: Handling Missing Modalities via Condition Dropout

arXiv:2607.20326v1 Announce Type: cross Abstract: RGB-D semantic segmentation has achieved remarkable progress, yet most models assume that RGB and depth are always available. In practice, failures or

Train the Model, Not the Reader: Decodability Supervision for Verifiable Activation Explanations

model-releasesarxiv-cs-ai

arXiv:2607.20379v1 Announce Type: new Abstract: Natural-language autoencoders score explanations of hidden activations by reconstruction: an explanation is deemed faithful if the activation can be reg

Wave2Body: Rethinking mmWave Human Pose Estimation as Radar-to-Body Token Translation

arXiv:2607.18875v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar enables privacy-friendly human sensing, but its sparse point clouds are physical measurements of view-dependent electroma

safetyarxiv-cs-cv

AeroMap3D: Anchoring Monocular UAV 6-DoF Localization to Visual-Geometric-Semantic Map Priors

arXiv:2607.14009v1 Announce Type: new Abstract: We present AeroMap3D, a monocular 6-DoF UAV localization system that anchors onboard imagery to visual, geometric, and semantic map priors for GNSS-deni

researcharxiv-cs-ro

Agile perceptive multi-skill locomotion for quadrupedal robots in the wild

arXiv:2607.13579v1 Announce Type: cross Abstract: Enabling quadrupedal robots to traverse complex terrains-from rugged outdoor environments to urban landscapes-requires seamless integration of multipl

Anatomically Faithful but Temporally Blind: Auditing Attribution for Left-Ventricular Ejection-Fraction Estimation from Echocardiography

arXiv:2607.13738v1 Announce Type: cross Abstract: Background and Objective: Deep video models estimate left-ventricular ejection fraction (EF) from echocardiography with near-expert accuracy, and post

local-aiarxiv-cs-ai

Attentive multilayer fusion for vision transformers

arXiv:2601.09322v2 Announce Type: replace Abstract: With the rise of large-scale foundation models, efficiently adapting them to downstream tasks remains a central challenge. Linear probing, which fre

Benefits and Limitations of Communication in Multi-Agent Reasoning

arXiv:2510.13903v2 Announce Type: replace-cross Abstract: Chain-of-thought prompting has popularized step-by-step reasoning in large language models, yet model performance still degrades as problem co

agentsarxiv-cs-ai

Designing Safety-Constrained LLM Systems for Public Health Information Access

arXiv:2607.13038v1 Announce Type: cross Abstract: We present the design and implementation of a safety constrained large language model (LLM) system for public health information access, focusing on m

Evaluating Vision Foundation Models for Pixel and Object Classification in Microscopy

arXiv:2603.19802v2 Announce Type: replace Abstract: Deep learning underlies most modern approaches and tools in computer vision, including biomedical imaging. However, for interactive semantic segment

EXPLORE: Exploration with Guided Search for Analog Topology Generation using Language Models

model-releasesarxiv-cs-lg

arXiv:2607.13416v1 Announce Type: new Abstract: Automating analog circuit topology design is essential to reduce the extensive manual effort required to meet increasingly diverse and customized applic

FM^2: Unified Federated Foundation Models for Heterogeneous Multimodal Medical Imaging

arXiv:2607.13386v1 Announce Type: new Abstract: Building foundation models for medical imaging requires pooling data across institutions, yet privacy regulations prohibit centralized aggregation. Exis

GigaWorld-Policy-0.5: A Faster and Stronger WAM Empowered by AutoResearch

arXiv:2607.13960v1 Announce Type: new Abstract: World Action Models (WAMs) improve robot policy learning by jointly modeling actions and future visual observations, using future scene evolution as den

local-aiarxiv-cs-ro

Improving Medical Image Generative Models with Frechet Distance Loss

arXiv:2607.13300v1 Announce Type: new Abstract: Diffusion generative models have demonstrated immense potential for synthetic medical image generation. However, these models often struggle to capture

Leveraging unlabelled data for generalizable neural population decoding

arXiv:2607.14086v1 Announce Type: new Abstract: Robust and accurate neural decoders are integral to neurotechnologies such as brain-computer interfaces and closed-loop experiments. Recent work has sho

researcharxiv-cs-lg

LLM-Guided Reinforcement Learning for Audio-Visual Speech Enhancement

arXiv:2603.13952v3 Announce Type: replace-cross Abstract: In existing Audio-Visual Speech Enhancement (AVSE) methods, objectives such as Scale-Invariant Signal-to-Noise Ratio (SI-SNR) and Mean Squared

Local Redundancy: An Information-Theoretic Measure of Plasticity from Synthetic Memorization

arXiv:2607.13432v1 Announce Type: new Abstract: Plasticity -- a neural network's ability to adapt to new tasks -- is critical for continual and transfer learning. Existing measures, such as effective

local-aiarxiv-cs-lg

M+Adam: Low-Precision Training via Additive-Multiplicative Optimization

model-releasesarxiv-cs-lg

arXiv:2607.10611v2 Announce Type: replace Abstract: Training with quantized weights can reduce costs but often results in degraded accuracy, especially when optimization is carried out in low precisio

Memory as a Controlled Process: Learned Adaptive Memory Management for LLM Agents

arXiv:2607.13591v1 Announce Type: cross Abstract: Large Language Model (LLM) agents increasingly rely on external memory systems to accumulate experience across tasks. Yet nearly all existing approach

Peak-End-Net: A Peak-End Rule Inspired Framework for Generalizable Video Aesthetic Assessment

arXiv:2607.13941v1 Announce Type: new Abstract: Video aesthetic assessment (VAA) aims to predict how aesthetically pleasing a video is, yet remains far less explored than other visual assessment tasks

Task-Specific Feature Fusion Method for Multi-Task Affective Behavior Analysis

arXiv:2607.13986v1 Announce Type: new Abstract: The 11th Affective Behavior Analysis in-the-wild (ABAW11) Multi-Task Learning Challenge requires a unified system to predict valence-arousal, categorica

Hardware

Text2Sign: A Single-GPU Diffusion Baseline for Text-to-Sign Language Video Generation

arXiv:2607.13164v1 Announce Type: cross Abstract: Sign language is a primary communication channel for millions of Deaf and hard-of-hearing people, yet text-to-signer video generation remains costly b

hardwarearxiv-cs-cv

Tutorials

The Hitchhiker's Guide to Monoculture

arXiv:2607.13077v1 Announce Type: cross Abstract: Large language models (LLMs) often produce homogeneous outputs, raising concerns that AI coding assistants may lead to convergence in the software art

tutorialsarxiv-cs-ai

Towards Enhancing 3D Spatial Reasoning in Medical Multimodal Large Language Models

arXiv:2607.13860v1 Announce Type: new Abstract: While Multimodal Large Language Models (MLLMs) have demonstrated remarkable success in 2D medical image understanding, their extension to 3D volumetric

TRACE-PCa: Predicting Prostate Cancer Progression from Longitudinal MRI During Active Surveillance

arXiv:2607.13506v1 Announce Type: new Abstract: Active surveillance (AS) is the preferred strategy for favorable-risk prostate cancer, yet current protocols rely on scheduled repeat biopsies, most of

Unleashing Multimodal Large Language Models for Training-free HOI Detection in the Wild

arXiv:2607.13881v1 Announce Type: cross Abstract: Human-object interaction detection (HOID) has traditionally been formulated as a supervised detection problem over predefined interaction categories.

agentsarxiv-cs-ai

When Vision Overrides Language: Evaluating and Mitigating Counterfactual Failures in VLAs

arXiv:2602.17659v2 Announce Type: replace Abstract: Vision-Language-Action models (VLAs) promise to ground language instructions in robot control, yet in practice often fail to faithfully follow langu

A Shortcut to Statistically Steady-State Turbulence with Flow Matching

arXiv:2607.13022v1 Announce Type: cross Abstract: Many nonlinear physical systems exhibit an initial transient phase in which perturbations grow before nonlinear interactions lead to a statistically s

researcharxiv-cs-lg

Amplitude-Only FFN Intervention for Tool-Structured LLM Inference Method: Gated Evaluation Protocol, and Cross-Model Empirical Results

arXiv:2607.11183v2 Announce Type: replace Abstract: Large language models increasingly operate as tool-using agents, where small format, argument, or function-call errors can invalidate otherwise plau

agentsarxiv-cs-cl

Beyond Perceptual Distance: Discrepancy Assessment on Deep Representation for Out-of-Distribution Detection with Diffusion Model

arXiv:2409.10094v3 Announce Type: replace Abstract: Out-of-Distribution (OoD) detection aims to justify whether a given sample is from the training distribution of the classifier-under-protection, i.e

DeGuNet: Depth-Guided Ultra-Compact Backbones for Efficient LiDAR-Camera 3D Detection

arXiv:2607.12419v1 Announce Type: new Abstract: In autonomous driving perception, the fusion of LiDAR and camera modalities has become the dominant paradigm for 3D object detection. However, current m

Fine-Tuned Multi-Agent Framework for Detecting OCEAN in Life Narratives

arXiv:2607.12215v1 Announce Type: new Abstract: Accurately assessing personality from text is challenging because traits are latent, context-dependent, and often subtly expressed across long narrative

agentsarxiv-cs-cl

From Reconstruction to Interpretation: Zero-Setup Multi-Phase Segmentation of X-ray Tomography Data

arXiv:2607.12175v1 Announce Type: cross Abstract: X-ray tomography enables nondestructive characterization of material microstructures, while advances in micro-CT imaging have accelerated volumetric d

GaitSpan: Growing Humanoid Locomotion from Walking to Running

arXiv:2607.12114v1 Announce Type: cross Abstract: A humanoid that can walk should not relearn locomotion from scratch to jog or run. Yet current approaches often obtain gait diversity by prescribing g

Generating Developable 3D Molecules via Pocket-Conditioned Diffusion and Property-Aware Optimization

model-releasesarxiv-cs-lg

arXiv:2607.12349v1 Announce Type: new Abstract: Drug discovery and development is time-consuming and resource-intensive, motivating computational approaches such as diffusion models for de novo drug d

High-Dimensional Gaussian Mean Estimation under Realizable Contamination

arXiv:2603.16798v2 Announce Type: replace Abstract: We study mean estimation for a Gaussian distribution with identity covariance in R^d under a missing data scheme termed realizable epsilon-contamina

researcharxiv-cs-lg

HSEmotion Team at the 11th ABAW Challenge: Multi-Task Learning and Ambivalence/Hesitancy Video Recognition

arXiv:2607.12774v1 Announce Type: cross Abstract: This article presents our results for the 11th Affective Behavior Analysis in-the-Wild (ABAW) competition. For multi-task learning with simultaneous p

Hybrid Continual Learning for Low-Resource Australian Aboriginal Language Identification

arXiv:2607.11946v1 Announce Type: new Abstract: Language identification is an important step toward integrating endangered Australian Aboriginal languages (AALs) into speech technologies supporting la

researcharxiv-cs-cl

Mind the Gap: Promises and Pitfalls of Hierarchical Planning in LeWorldModel

arXiv:2607.12547v1 Announce Type: cross Abstract: We investigate whether temporal hierarchy can improve LeWorldModel on long-horizon goal-conditioned control. We introduce Hi-LeWM, an extension that f

Optimization Is Not All You Need

model-releasesarxiv-cs-ai

arXiv:2607.11977v1 Announce Type: new Abstract: In 2019, OpenAI released two million GPT-2 outputs-ungrammatical, half broken-to aid the detection of machine-generated text. The alignment that produce

Representation and Reference Selection in Training-Free Synthetic Image Attribution

arXiv:2607.12052v1 Announce Type: cross Abstract: Synthetic image attribution aims at identifying the generator responsible for a given AI-generated image. Training-free reference-based attribution me

RFMSR: Residual Flow Matching for Image Super-Resolution

arXiv:2607.12753v1 Announce Type: new Abstract: Image super-resolution (ISR) has witnessed remarkable progress with diffusion models and flow matching. The dominant text-to-image (T2I) based approache