Search: “inference”

Tensor Channel Equivariant Graph Neural Networks for Molecular Polarizability Prediction

arXiv:2605.16891v1 Announce Type: new Abstract: We introduce a tensor-channel equivariant graph neural network for direct prediction of molecular polarizability tensors. Building on the efficient PaiN

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Tutorials

The Silent Brush: Evaluating Artistic Style Leakage in AI Art Generation

DGX agent

arXiv:2605.17500v1 Announce Type: cross Abstract: Generative text-to-image models are typically trained on large-scale web-scraped datasets that include diverse visual content such as copyrighted and

tutorialsarxiv-cs-cv

19 May 2026

Hardware

Token-Space Mask Prediction for Efficient Vision Transformer Segmentation

arXiv:2605.18177v1 Announce Type: new Abstract: Query-based Vision Transformer segmentation models typically reconstruct dense spatial feature maps to predict masks, inheriting design patterns from co

hardwarearxiv-cs-cv

Toward Near-Real-Time Marine Oil Spill Detection in SAR Imagery using Quantum-Assisted SVM

arXiv:2605.17217v1 Announce Type: cross Abstract: Marine oil spills require rapid detection to mitigate severe ecological and economic damage. While satellite-based Synthetic Aperture Radar (SAR) prov

researcharxiv-cs-lg

Towards Sustainable Growth: A Multi-Value-Aware Retrieval Framework for E-Commerce Search

arXiv:2605.17994v1 Announce Type: cross Abstract: New item growth is critical for maintaining a healthy ecosystem in large-scale e-commerce platforms. However, existing systems tend to prioritize pres

TPV: Parameter Perturbations Through the Lens of Test Prediction Variance

arXiv:2512.11089v4 Announce Type: replace-cross Abstract: We introduce test prediction variance (TPV)--the first-order sensitivity of a trained model's outputs to parameter perturbations--as a unifyin

TRACE: Trajectory Correction from Cross-layer Evidence for Hallucination Reduction

arXiv:2605.18163v1 Announce Type: new Abstract: Hallucination correction is not a one-direction problem. We show that intermediate layers are neither uniformly more truthful than final layers nor unif

researcharxiv-cs-ai

Training-Free Occluded Text Rendering via Glyph Priors and Attention-Guided Semantic Blending

arXiv:2605.16810v1 Announce Type: new Abstract: We present a training-free framework for occluded text rendering with a pretrained FLUX.1-dev backbone. The task requires a model to render recognizable

local-aiarxiv-cs-cv

Transformer-Based MCS Prediction for 5G Multicast-Broadcast Services (MBS)

arXiv:2605.16735v1 Announce Type: cross Abstract: The deployment of 5G Multicast-Broadcast Services (MBS) is emerging as a critical technology for spectral-efficient UHD content delivery and serving a

safetyarxiv-cs-lg

TTE-Flash: Accelerating Reasoning-based Multimodal Representations via Think-Then-Embed Tokens

arXiv:2605.16638v1 Announce Type: new Abstract: Recent research has demonstrated that Universal Multimodal Embedding (UME) benefits significantly from Chain-of-Thought (CoT) reasoning. In this paradig

UbuntuGuard: A Culturally-Grounded Policy Benchmark for Equitable AI Safety in African Languages

model-releasesarxiv-cs-cl

arXiv:2601.12696v2 Announce Type: replace Abstract: Current guardian models are predominantly Western-centric and optimized for high-resource languages, leaving low-resource African languages vulnerab

UniAlign: A Model-Agnostic Framework for Robust Network Traffic Classification under Distribution Shifts

arXiv:2605.17575v1 Announce Type: cross Abstract: Network traffic classification (NTC) models often suffer severe performance degradation when deployed in real-world environments due to distribution s

Unifying Contrastive and Generative Objectives for Visual Understanding and Text-to-Image Generation

arXiv:2603.02667v2 Announce Type: replace Abstract: Unifying text-image contrastive learning and text-to-image (T2I) generation in a single end-to-end model is challenging because the two objectives d

Applications

Universal Time-Series Representation Learning: A Survey

arXiv:2401.03717v4 Announce Type: replace-cross Abstract: Time-series data exists in every corner of real-world systems and services, ranging from satellites in the sky to wearable devices on human bo

applicationsarxiv-cs-ai

Usenix'23 Extended Version: Smart Learning to Find Dumb Contracts

arXiv:2304.10726v3 Announce Type: replace-cross Abstract: We introduce the Deep Learning Vulnerability Analyzer (DLVA) for Ethereum smart contracts based on neural networks. We train DLVA to judge byt

VA-Adapter: Adapting Ultrasound Foundation Model to Echocardiography Probe Guidance

arXiv:2510.06809v3 Announce Type: replace Abstract: Echocardiography is a critical tool for detecting heart diseases, yet its steep operational difficulty causes a shortage of skilled personnel. Probe

Tutorials

Venom: A PyTorch Generative Modeling Toolkit

arXiv:2605.17605v1 Announce Type: new Abstract: Modern generative modeling has grown into a broad collection of related but often separately implemented paradigms, including denoising diffusion models

tutorialsarxiv-cs-lg

Verifier-Guided Code Translation via Meta-Step Decoding

arXiv:2605.17626v1 Announce Type: new Abstract: Test-time scaling is an important mechanism for improving large language models, especially on tasks with deterministic verifiers. Code translation is a

VerifyMAS: Hypothesis Verification for Failure Attribution in LLM Multi-Agent Systems

model-releasesarxiv-cs-cl

arXiv:2605.17467v1 Announce Type: new Abstract: Large language model-driven multi-agent systems (LLM-MAS) excel at complex tasks, yet unreliable agents remain a key bottleneck to system-level reliabil

VGGT-CD: Training-Free Robust Registration for 3D Change Detection

arXiv:2605.16859v1 Announce Type: cross Abstract: 3D change detection from multi-view images is essential for urban monitoring, disaster assessment, and autonomous driving. However, existing methods p

VGGT-Occ: Geometry-Grounded and Density-Aware Gated Fusion for 3D Occupancy Prediction

model-releasesarxiv-cs-cv

arXiv:2605.16911v1 Announce Type: new Abstract: 3D semantic occupancy prediction requires accurate 2D-to-3D feature lifting, yet current methods restrict camera geometry to initial projections. Subseq

VideoNeuMat: Neural Material Extraction from Generative Video Models

arXiv:2602.07272v2 Announce Type: replace Abstract: Creating photorealistic materials for 3D rendering requires exceptional artistic skill. Generative models for materials could help, but are currentl

Vision Foundation Models as Generalist Tokenizers for Image Generation

arXiv:2605.18390v1 Announce Type: new Abstract: In this work, we explore the largely unexplored direction of building a generalist image tokenizer directly on top of a frozen vision foundation model (

Vision-OPD: Learning to See Fine Details for Multimodal LLMs via On-Policy Self-Distillation

arXiv:2605.18740v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) still struggle with fine-grained visual understanding, where answers often depend on small but decisive evide

local-aiarxiv-cs-ai

We Think, Therefore We Align LLMs to Helpful, Harmless and Honest Before They Go Wrong

model-releasesarxiv-cs-cl

arXiv:2509.22510v3 Announce Type: replace Abstract: Alignment of Large Language Models (LLMs) is the ability to satisfy desired objectives during generation, which is critical for trustworthy deployme

When a Zero-Shooter Cheats: Improving Age Estimation via Activation Steering

arXiv:2605.17658v1 Announce Type: new Abstract: Different age-related regulations have been proposed to protect minors from harmful content and interactions online. Automated age estimation is central

researcharxiv-cs-lg

When Marginals Match but Structure Fails: Covariance Fidelity in Generative Models

arXiv:2603.17041v2 Announce Type: replace-cross Abstract: Generative models are increasingly deployed as substitutes for real data in downstream scientific workflows, yet standard evaluation criteria

researcharxiv-cs-ai

When Personalization Legitimizes Risks: Uncovering Safety Vulnerabilities in Personalized Dialogue Agents

arXiv:2601.17887v2 Announce Type: replace Abstract: Long-term memory enables large language model (LLM) agents to support personalized and sustained interactions. However, most work on personalized ag

When Vision Speaks for Sound

arXiv:2605.16403v1 Announce Type: new Abstract: Despite rapid progress in video-capable MLLMs, we find that their apparent audio understanding in videos is often vision-driven: models rely on visual c

ZeroSiam: An Efficient Asymmetry for Test-Time Entropy Optimization without Collapse

arXiv:2509.23183v3 Announce Type: replace Abstract: Test-time entropy minimization helps adapt a model to novel environments and incentivize its reasoning capability, unleashing the model's potential

safetyarxiv-cs-lg

Adaptive Conformal Prediction for Quantum Machine Learning

arXiv:2511.18225v2 Announce Type: replace Abstract: Quantum machine learning seeks to leverage quantum computers to improve upon classical machine learning algorithms. Currently, robust uncertainty qu

researcharxiv-cs-lg

Agents

Agent4POI: Agentic Context-Conditioned Affordance Reasoning for Multimodal Point-of-Interest Recommendation

arXiv:2605.15203v1 Announce Type: cross Abstract: We introduce Agent4POI, the first POI recommendation framework that generates context-conditioned multimodal representations at recommendation time, r

agentsarxiv-cs-ai

AgentStop: Terminating Local AI Agents Early to Save Energy in Consumer Devices

arXiv:2605.15206v1 Announce Type: cross Abstract: Autonomous agents powered by large language models (LLMs) are increasingly used to automate complex, multi-step tasks such as coding or web-based ques

local-aiarxiv-cs-ai

An Algebraic Exposition of the Theory of Dyadic Morality

arXiv:2605.16153v1 Announce Type: new Abstract: This paper provides an algebraic exposition of the theory of dyadic morality (TDM), a psychological model of moral judgment grounded in a simple two-nod

Argus: Evidence Assembly for Scalable Deep Research Agents

arXiv:2605.16217v1 Announce Type: cross Abstract: Deep research agents have achieved remarkable progress on complex information seeking tasks. Even long ReAct style rollouts explore only a single traj

CAPS: Cascaded Adaptive Pairwise Selection for Efficient Parallel Reasoning

arXiv:2605.15513v1 Announce Type: new Abstract: Parallel reasoning, where a generator samples many candidate solutions and an aggregator selects the best, is one of the most effective forms of test-ti

researcharxiv-cs-ai

ChangeFlow -- Latent Rectified Flow for Change Detection in Remote Sensing

arXiv:2605.15375v1 Announce Type: cross Abstract: Remote sensing change detection (RSCD) aims to localise changes between two images of the same geographic region. In practice, change masks often foll

local-aiarxiv-cs-ai

Agents

Context, Reasoning, and Hierarchy: A Cost-Performance Study of Compound LLM Agent Design in an Adversarial POMDP

arXiv:2605.16205v1 Announce Type: new Abstract: Deploying compound LLM agents in adversarial, partially observable sequential environments requires navigating several design dimensions: (1) what the a

agentsarxiv-cs-ai

Tutorials

Contexting as Recommendation: Evolutionary Collaborative Filtering for Context Engineering

arXiv:2605.15721v1 Announce Type: new Abstract: Large Language Models (LLMs) are highly sensitive to their input contexts, motivating the development of automated context engineering. However, existin

tutorialsarxiv-cs-cl

DealMaTe: Multi-Dimensional Material Transfer via Diffusion Transformer

arXiv:2605.15681v1 Announce Type: cross Abstract: Recently, diffusion-based material transfer methods rely on image fine-tuning or complex architectures with auxiliary networks but face challenges suc

DebiasRAG: A Tuning-Free Path to Fair Generation in Large Language Models through Retrieval-Augmented Generation

arXiv:2605.16113v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved unprecedented success due to their exceptional generative capabilities. However, because they depend on kno

Agents

Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models

arXiv:2605.15706v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existi

agentsarxiv-cs-lg

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space

arXiv:2605.15368v1 Announce Type: new Abstract: Group-convolutional neural networks (GCNNs) are among the most important methods for introducing symmetry as an inductive bias in deep learning: In each

Tutorials

DiscussLLM: Teaching Large Language Models When to Speak

arXiv:2508.18167v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding and generating human-like text, yet they largely operate as

tutorialsarxiv-cs-cl

Don't Stop Me Yet: Sampling Loss Minima via Dissipative Riemannian Mechanics

arXiv:2605.15459v1 Announce Type: new Abstract: The minima of modern neural network loss functions are typically not isolated, rather they form connected components of reparameterization invariant sol

local-aiarxiv-cs-lg

EgoExo-WM: Unlocking Exo Video for Ego World Models

arXiv:2605.15477v1 Announce Type: new Abstract: Egocentric world models present a promising direction for enabling agents to predict and plan, but their performance is constrained by the limited avail

ElasticDiT: Efficient Diffusion Transformers via Elastic Architecture and Sparse Attention for High-Resolution Image Generation on Mobile Devices

arXiv:2605.15684v1 Announce Type: new Abstract: The Diffusion Transformer (DiT) architecture is the state-of-the-art paradigm for high-fidelity image generation, underpinning models like Stable Diffus

ELDOR: A Dataset and Benchmark for Illegal Gold Mining in the Amazon Rainforest

model-releasesarxiv-cs-cv

arXiv:2605.15397v1 Announce Type: new Abstract: Illegal gold mining in the Amazon rainforest causes deforestation, water contamination, and long-term ecosystem disruption, yet remains difficult to mon