Search: “inference”

FlowAWR: Online Adaptive Flow Reinforcement via Advantage-Weighted Rectification

arXiv:2606.30376v1 Announce Type: cross Abstract: Aligning generative flow models on continuous spaces via online reinforcement learning is constrained by intractable trajectory likelihoods. Existing

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FreqOrtho-SR: Frequency-Guided Orthogonal Expert Learning for Real-World Image Super-Resolution

DGX agent

arXiv:2606.28745v1 Announce Type: new Abstract: Diffusion prior-based methods have shown impressive results in real-world image super-resolution (ISR), yet two key challenges persist: balancing pixel-

applicationsarxiv-cs-cv

30 Jun 2026

Friend or Foe

arXiv:2509.00123v2 Announce Type: replace-cross Abstract: A fundamental challenge in microbial ecology is determining whether bacteria compete or cooperate in different environmental conditions. With

From Accuracy to Visual Dependence: Auditing and Filtering Modality Collapse in Traffic VideoQA

model-releasesarxiv-cs-cv

arXiv:2606.30220v1 Announce Type: new Abstract: High benchmark accuracy does not guarantee genuine use of visual evidence. We study this problem in traffic accident Video Question Answering (VideoQA),

FutureNav: Unified World-Action Modeling for Vision-and-Language Navigation

arXiv:2606.30367v1 Announce Type: new Abstract: Vision-and-language navigation (VLN) in continuous environments requires an agent to ground instructions in egocentric observations while maintaining sp

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Generation of Uncertainty-Aware High-Level Spatial Concepts in Factorized 3D Scene Graphs via Graph Neural Networks

arXiv:2409.11972v4 Announce Type: replace-cross Abstract: Enabling robots to autonomously discover high-level spatial concepts (e.g., rooms and walls) from primitive geometric observations (e.g., plan

Good Enough? An Investigation on the Impact of Label Quality in Large-Scale Medical Datasets

arXiv:2505.20928v2 Announce Type: replace Abstract: Manually refining radiological segmentation masks is highly resource-intensive. To determine when this expert commitment is truly justified for the

Ground Truths in Suicide Research: The Current State of AI-Based Suicide Detection in Social Media

arXiv:2606.28334v1 Announce Type: cross Abstract: Recent advances in artificial intelligence (AI) and social media data have led to growing optimism about the ability to detect suicide risk at scale.

researcharxiv-cs-ai

H-GRPO: Permutation-Invariant Reinforcement Learning for Grounded Visual Reasoning

arXiv:2606.29915v1 Announce Type: new Abstract: Vision-Language Models (VLMs) often achieve high performance on benchmarks while remaining 'black boxes', yet they remain prone to hallucination or rely

HASTE: A Framework for Training-Free, Dynamic, and Steerable Compression of Pre-Trained Convolutional Neural Networks

arXiv:2606.30516v1 Announce Type: new Abstract: Deploying large convolutional neural networks (CNNs) on resource-constrained devices is challenging due to their high computational cost. While dynamic

HEARTS: Benchmarking LLM Reasoning on Health Time Series

arXiv:2603.06638v3 Announce Type: replace-cross Abstract: The rise of large language models (LLMs) has shifted time series analysis from narrow analytics to general-purpose reasoning. Yet, existing be

High-Resolution Climate Projections Using Diffusion-Based Downscaling of a Lightweight Climate Emulator

arXiv:2602.13416v2 Announce Type: replace Abstract: The proliferation of data-driven models in weather and climate sciences has marked a significant paradigm shift, with advanced models demonstrating

HorizonRelight: Relighting Long-horizon Videos Consistently via Diffusion Transformers

arXiv:2606.29095v1 Announce Type: new Abstract: Diffusion-based video relighting enables controllable relighting from a single input video, but modern video diffusion backbones are trained on short cl

HSD: Training-Free Acceleration for Document Parsing Vision-Language Models with Hierarchical Speculative Decoding

arXiv:2602.12957v3 Announce Type: replace Abstract: Document parsing is a fundamental task in multimodal understanding, supporting a wide range of downstream applications such as information extractio

Hybrid Active-Online Learning Framework for Label-Efficient Concept Drift Adaptation in Optical Network Failure Detection

arXiv:2606.30322v1 Announce Type: new Abstract: We propose a hybrid active-online learning framework for label-efficient concept drift adaptation in optical network failure detection. Using margin-bas

Applications

HyPER-GAN: Hybrid Patch-Based Image-to-Image Translation for Real-Time Photorealism Enhancement in Game Engines

arXiv:2603.10604v3 Announce Type: replace Abstract: Generative models are increasingly used in video game engines to enhance the photorealism of rendered images for visual synthetic data generation an

applicationsarxiv-cs-cv

Tutorials

Implementing resilience patterns with Amazon Bedrock and LLM gateway

In this post, you will learn five practical patterns for building resilient generative AI applications on AWS, progressing from native Amazon Bedrock features to multi-model orchestration using an LLM

tutorialsaws-ml-blog

IMU-HOI: A Symbiotic Framework for Coherent Human-Object Interaction and Motion Capture via Contact-Conscious Inertial Fusion

arXiv:2606.28604v1 Announce Type: new Abstract: Capturing full-body human motion with object interactions is crucial for AR/VR and robotics applications, yet it remains challenging for conventional vi

Instance-Conditioned Adaptation for Large-scale Generalization of Neural Routing Solver

arXiv:2405.01906v3 Announce Type: replace Abstract: In modern intelligent transportation systems (ITS), particularly in freight transportation and logistics, real-time route planning is crucial. It pr

Keypose Exploration: Efficient Automatic Trajectory Labelling and Cross-Embodiment Policy Transfer

arXiv:2606.29028v1 Announce Type: new Abstract: Keypose-based manipulation decomposes tasks into critical waypoints to simplify policy learning for long-horizon tasks, but existing approaches rely on

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Knowing Bias, Doing Better: Mitigating Social Bias in LLMs via Know-Bias Neuron Enhancement

arXiv:2601.21864v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit social biases that reinforce harmful stereotypes, limiting their safe deployment. Most existing debiasing metho

safetyarxiv-cs-ai

L2D2-GS: Learning to Densify for Feedforward Dynamic Gaussian Scene Reconstruction

arXiv:2606.29374v1 Announce Type: new Abstract: High-fidelity reconstruction of dynamic urban environments is a cornerstone of autonomous driving simulation and large-scale world modeling. While 3D Ga

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Agents

LAMP: Lean-based Agentic framework with MCP and Proof Repair

arXiv:2606.28841v1 Announce Type: cross Abstract: Large language models are increasingly capable of mathematical reasoning, but the proofs they generate are often unreliable and hard to verify. Intera

agentsarxiv-cs-ai

Applications

Latent-CURE for Breast Cancer Diagnosis

arXiv:2606.29928v1 Announce Type: cross Abstract: Multimodal Large Models have significantly advanced automated breast ultrasound diagnosis. However, most existing frameworks utilize opaque, end-to-en

applicationsarxiv-cs-ai

Leader Reward for POMO-Based Neural Combinatorial Optimization

arXiv:2405.13947v2 Announce Type: replace Abstract: Deep neural networks based on reinforcement learning (RL) for solving combinatorial optimization (CO) problems are developing rapidly and have shown

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Learning to Adaptively Allocate Gaussians for Arbitrary-Scale Image Super-Resolution

arXiv:2606.29400v1 Announce Type: cross Abstract: In computer graphics, visual content is continuously warped, zoomed and resampled. This occurs when engines upscale frames, users zoom into 3D scenes,

researcharxiv-cs-ai

Learning to Distributedly Estimate under Partially Known Dynamics: A Covariance-Agnostic Neural Kalman Consensus Filter

arXiv:2606.28441v1 Announce Type: cross Abstract: Online latent state estimation constitutes a fundamental challenge within the artificial intelligence field, serving as a foundational tool for divers

researcharxiv-cs-ai

Learning to Route and Schedule LLMs from User Retrials via Contextual Queueing Bandits

model-releasesarxiv-cs-lg

arXiv:2602.02061v2 Announce Type: replace Abstract: Explosive demands for LLMs often cause user queries to accumulate in server queues, requiring efficient routing (query-LLM matching) and scheduling

Agents

Linguistic Firewall: Geometry as Defense in Multi-Agent Systems Routing

arXiv:2606.30555v1 Announce Type: new Abstract: The rapid integration of Large Language Models (LLMs) has driven the evolution of Multi-Agent Systems (MAS), where specialized agents collaborate to exe

agentsarxiv-cs-ai

LLM Semantic Signaling Game and Mechanism Design: Systematic Blindness, Awareness Shaping, and Mindset Dynamics

arXiv:2606.29113v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate strategic interactions through natural language, making semantic control a critical element of commu

safetyarxiv-cs-ai

LNN-Fly: Continuous-Time UAV Navigation for Robust Obstacle Avoidance under Timing Mismatch

arXiv:2606.28827v1 Announce Type: new Abstract: End-to-end unmanned aerial vehicle (UAV) navigation can achieve impressive agility in simulation, yet its obstacle-avoidance behavior often degrades aft

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Lost in Execution: On the Multilingual Robustness of Tool Calling in Large Language Models

arXiv:2601.05366v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly deployed as agents that invoke external tools through structured function calls. While recent wo

MemLeak: Diagnosing Information Leaks in Multimodal Agent Memory

model-releasesarxiv-cs-lg

arXiv:2606.29788v1 Announce Type: new Abstract: When a multimodal AI agent is asked to forget a fact, current memory systems usually delete the text entry and report success. We find that the fact can

Metric Aggregation Divergence: A Hidden Validity Threat in Agent-Based Policy Optimization and a Contractual Remedy

arXiv:2606.29038v1 Announce Type: cross Abstract: Metric aggregation divergence (MAD) is the silent inconsistency that arises when distinct pipeline stages in an agent-based model coupled with a multi

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Local Ai

MF-UAVPose6D: A Model-Free Monocular 6-DoF Pose Estimation Framework for Fixed-Wing UAVs

arXiv:2606.29697v1 Announce Type: new Abstract: For uncrewed aerial vehicles (UAVs), estimating six-degree-of-freedom (6-DoF) poses is essential for airspace situational awareness, target tracking, an

local-aiarxiv-cs-cv

MIRROR: Aligning Semantic Relations from Language to Image via Gromov--Wasserstein

arXiv:2606.29462v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) inherit rich relational priors from their language backbones, yet often fail when asked to apply these relation

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MirrorCode: AI can rebuild entire programs from behavior alone

arXiv:2606.30182v1 Announce Type: new Abstract: AI models are rapidly improving at autonomous coding, as shown by benchmark progress and one-off demonstrations such as AI implementing a C compiler. Ho

MirrorPPR: Exemplar-Based Portrait Photo Retouching

arXiv:2606.29308v1 Announce Type: new Abstract: While text-guided image editing has made remarkable progress, it remains limited in structural portrait retouching. Textual descriptions struggle to con

Multiply Robust Causal Mediation Analysis with Continuous Treatments

model-releasesarxiv-cs-lg

arXiv:2105.09254v4 Announce Type: replace-cross Abstract: In many applications, researchers are interested in the direct and indirect causal effects of a treatment or exposure on an outcome of interes

Tutorials

Mural: Transferring LLM knowledge to image generation via Mixture-of-Transformers

arXiv:2606.29013v1 Announce Type: new Abstract: Leveraging capabilities of large language models (LLMs) in text-to-image (T2I) synthesis is an important research direction. In this work we investigate

tutorialsarxiv-cs-cv

Agents

NaLA: A 3D Native LLM Layout Agent for High-quality 3D Scene Generation

arXiv:2606.29395v1 Announce Type: new Abstract: Recently, Large Language Models (LLMs) have emerged as promising layout agents for 3D scene generation. Existing layout agents still suffer from implaus

agentsarxiv-cs-cv

Nano Banana 2 Lite (Gemini 3.1 Flash Lite Image) now on AI Gateway

model-releasesvercel-blog

Vercel has announced the availability of Nano Banana 2 Lite, a lightweight image variant featuring Google's Gemini 3.1 Flash model, through its AI Gateway service. This release likely provides develop

Nemotron-Labs-Diffusion-Image: Advancing Masked Discrete Diffusion for High-Resolution Image Synthesis

model-releasesarxiv-cs-cv

arXiv:2606.29814v1 Announce Type: new Abstract: We propose Nemotron-Labs-Diffusion-Image, a state-of-the-art masked discrete diffusion model (MDM) for high-resolution text-to-image synthesis. Compared

Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models

arXiv:2603.18907v2 Announce Type: replace Abstract: We propose a new Neural Galerkin Normalizing Flow framework to approximate the transition probability density function of a diffusion process by sol

NeuReasoner: Theory-grounded Mapping of Reasoning Elicitation Boundaries

arXiv:2606.29971v1 Announce Type: new Abstract: A growing body of work suggests that the reasoning capabilities of large language models are largely latent in their base form, with post-training prima

NoiseTilt: Noise-Tilted Reverse Kernels for Diffusion Reward Alignment

arXiv:2606.18066v2 Announce Type: replace Abstract: We introduce the Noise-Tilted Reverse Kernel (NTRK), a reward-guided diffusion sampler that injects reward gradients through the noise term, leaving

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OmniCoT: A Benchmark for Global and Multi-Step Panoramic Reasoning

model-releasesarxiv-cs-cv

arXiv:2606.30378v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated promising spatial reasoning capabilities, while these abilities remain underexplored in the e

On design-unbiased algorithmic Machine Learning

arXiv:2606.28795v1 Announce Type: new Abstract: Machine Learning (ML) algorithms, such as k-Nearest Neighbours (kNN) or random forest, eschew the ideal of true data models in favour of predictive perf