Search: “inference”

arXiv:2606.07585v1 Announce Type: cross Abstract: This thesis addresses group emotion recognition (GER) in-the-wild with a focus on privacy preservation. Unlike traditional emotion recognition methods

applicationsarxiv-cs-ai

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Model Releases

NGram-MoSE: Efficient Remote Sensing Super-Resolution via N-Gram Context and Mixture-of-Experts

DGX agent

arXiv:2606.08535v1 Announce Type: new Abstract: Remote sensing applications for environmental monitoring and disaster management are frequently constrained by a spatial--temporal trade-off: imagery wi

model-releasesarxiv-cs-cv

9 Jun 2026

Agents

Observability for Delegated Execution in Agentic AI Systems

arXiv:2606.09692v1 Announce Type: cross Abstract: Delegation-scoped execution is not identifiable from standard observables: audit logs and execution traces can be identical under multiple incompatibl

agentsarxiv-cs-ai

Observation-driven correction of numerical weather prediction for marine winds

arXiv:2512.03606v2 Announce Type: replace Abstract: Accurate marine wind forecasts are essential for safe navigation, ship routing, and energy operations, yet they remain challenging because observati

local-aiarxiv-cs-lg

omega-EVA: Envision, Verify, and Act with Latent Interactive World Models

arXiv:2606.09457v1 Announce Type: new Abstract: Embodied policies typically map current observations directly to actions, leaving candidate-action consequences implicit. World models provide predictiv

safetyarxiv-cs-ro

OmniGen-AR: AutoRegressive Any-to-Image Generation

arXiv:2606.09156v1 Announce Type: new Abstract: Autoregressive (AR) models have demonstrated strong potential in visual generation, offering superior performance with simple architectures and optimiza

OmniTryOn: Video Try-On Anything at Once!

arXiv:2606.08514v1 Announce Type: new Abstract: Although video virtual try-on (VVT) has achieved significant progress, existing methods still exhibit two fundamental limitations: first, they are restr

On Choosing the mu Parameter in Gaussian Differential Privacy

model-releasesarxiv-cs-lg

arXiv:2606.09582v1 Announce Type: new Abstract: Recent work argues for using Gaussian differential privacy (GDP) to report the privacy guarantees in privacy-preserving machine learning. We provide pri

Optimality of Sequential Filtering Under Independent Cost and Selectivity Models

arXiv:2606.07589v1 Announce Type: new Abstract: Sequential filtering pipelines are a common design pattern in large-scale systems, where a large population of items is progressively reduced by a seque

PAFO: Pareto Fairness Optimization for Personalized Reward Modeling

arXiv:2606.07988v1 Announce Type: new Abstract: Large language models (LLMs) increasingly rely on reward models to align their outputs with diverse user preferences. While personalized reward models a

safetyarxiv-cs-ai

PBSD: Privileged Bayesian Self-Distillation for Long-Horizon Credit Assignment

arXiv:2606.09348v1 Announce Type: new Abstract: Long-horizon agentic tasks pose a fundamental credit assignment challenge for outcome-base reinforcement learning: trajectory-level rewards verify final

safetyarxiv-cs-lg

Applications

PhysGraph: A Physics-aware 3D Scene Graph for Perception and Reasoning

arXiv:2606.08655v1 Announce Type: cross Abstract: To perform a wide range of daily tasks, robots need to construct a 3D representation that is semantically rich, physically grounded, and structured en

applicationsarxiv-cs-cv

PicoSAM3: Real-Time In-Sensor Region-of-Interest Segmentation

arXiv:2603.11917v2 Announce Type: replace Abstract: Real-time, on-device segmentation is critical for latency-sensitive and privacy-aware applications such as smart glasses and Internet-of-Things devi

local-aiarxiv-cs-cv

POTATR: A Lightweight Image-to-Graph Model for Page-Level Table Extraction

arXiv:2606.09788v1 Announce Type: new Abstract: Large-scale document processing requires contextually aware table extraction (TE) that is both accurate and efficient. Yet current approaches require bi

PRISM: PRior-guided Imagination Sampling in world Models

model-releasesarxiv-cs-ai

arXiv:2606.07974v1 Announce Type: cross Abstract: A learned world model provides a powerful physical intuition for evaluating future states. But its effectiveness in continuous control also depends cr

Agents

PRISM: Recovering Instruction Sets from Language Model Activations

arXiv:2606.09563v1 Announce Type: new Abstract: As LLMs are deployed as agents, reliable monitoring requires knowing not only what they output, but which instructions are steering their behavior. This

agentsarxiv-cs-ai

Proposal Refinement for Few-Shot Object Detection

arXiv:2606.09245v1 Announce Type: cross Abstract: Few-shot object detection has gained widely attention in recent years. Some excellent algorithms have been proposed to handle this task. However, most

Provably Efficient Personalized Multi-Objective Bandits with Proactive Conversational Queries

arXiv:2606.08410v1 Announce Type: cross Abstract: Personalized decision-making in multi-objective bandits requires learning user-specific trade-offs among competing objectives. Since arm utility depen

Quantum-Enhanced Similarity Measures for Polarimetric Materials Classification

arXiv:2606.07766v1 Announce Type: cross Abstract: We present a quantum--classical hybrid pipeline for polarimetric material classification that casts this as a point-matching problem. Voxel cubes, con

Readable Yet Unpredictable: Rotated-Outcome Prediction in Vision-Language Models

arXiv:2606.07641v1 Announce Type: new Abstract: Can vision-language models predict what a 180{eg} rotation would reveal from the original image alone? We study this ability through Rotated-Outcome Pre

Real-Time Industrial Defect Detection on Edge Hardware Using Fine-Tuned YOLOv8: A Systematic Benchmark on the NEU Surface Defect Database and MVTec AD with Automotive & Battery Manufacturing Extensions

arXiv:2606.07659v1 Announce Type: new Abstract: Automated surface defect detection is critical for ensuring rigorous quality control in high-speed manufacturing environments. While deep learning model

ReCoVLA: VLM-Guided Reward Compilation for Failure Recovery in Vision-Language-Action Policies

arXiv:2606.09630v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies provide strong priors for language-conditioned manipulation, but remain brittle in off-nominal states requiring

safetyarxiv-cs-ai

Region-Wise Correspondence Prediction between Manga Line Art Images

arXiv:2509.09501v4 Announce Type: replace Abstract: Understanding region-wise correspondences between manga line art images is fundamental for high-level manga processing, supporting downstream tasks

safetyarxiv-cs-cv

Reinforcing Temporal Answer Grounding in Instructional Video via Candidate-Aware Causal Reasoning

arXiv:2606.08436v1 Announce Type: new Abstract: The task of temporal answer grounding in instructional video (TAGV), which aims to locate precise video segments that respond to natural language querie

safetyarxiv-cs-cv

Relational Epipolar Graphs for Robust Relative Camera Pose Estimation

arXiv:2604.04554v2 Announce Type: replace Abstract: A key component of Visual Simultaneous Localization and Mapping (VSLAM) is estimating relative camera poses using matched keypoints. Accurate estima

local-aiarxiv-cs-cv

Rethinking the Divergence Regularization in LLM RL

arXiv:2606.09821v1 Announce Type: new Abstract: Reinforcement learning (RL) has become a key component of post-training large language models (LLMs). In practice, LLM RL is often off-policy because of

safetyarxiv-cs-lg

Robust In-Context Reinforcement Learning Under Reward Poisoning Attacks

arXiv:2506.06891v3 Announce Type: replace Abstract: We study the corruption-robustness of in-context reinforcement learning (ICRL), focusing on the Decision-Pretrained Transformer (DPT, Lee et al., 20

Seeing is Believing: Aligning Prompt Rewriting with Visual Anchors for Text-to-Image Generation

arXiv:2606.08492v1 Announce Type: cross Abstract: Despite the impressive capabilities of text-to-image (T2I) models, an intent-generation gap often persists due to the brevity and ambiguity of user pr

Seq103: A Unified Neuroevolution Framework for Compact Sequence Architecture Discovery

model-releasesarxiv-cs-ai

arXiv:2606.07664v1 Announce Type: cross Abstract: Neuroevolution is a representative neural architecture search paradigm that evolves both network topology and weights through evolutionary algorithms.

Tutorials

SmartMixed: A Two-Phase Training Strategy for Adaptive Activation Function Learning in Neural Networks

arXiv:2510.22450v3 Announce Type: replace-cross Abstract: The choice of activation function plays a critical role in neural networks, yet most architectures still rely on fixed, uniform activation fun

tutorialsarxiv-cs-ai

Solving Inverse Problems with Flow-based Models via Model Predictive Control

model-releasesarxiv-cs-lg

arXiv:2601.23231v2 Announce Type: replace-cross Abstract: Flow-based generative models provide strong unconditional priors for inverse problems, but guiding their dynamics for conditional generation r

SOMA: From Surface Observations to Muscle Anatomy

arXiv:2606.09246v1 Announce Type: new Abstract: With the growing demand for realistic virtual humans, parametric body models have become a cornerstone of modern medicine, sports, and entertainment app

researcharxiv-cs-cv

SPIRONet: Spatial-Frequency Learning and Graph-based Channel Interaction Network for Vessel Segmentation

arXiv:2406.19749v2 Announce Type: replace-cross Abstract: Automatic vessel segmentation plays a pivotal role in the development of next-generation interventional navigation systems for surgical roboti

local-aiarxiv-cs-cv

Steer Where It Matters: Token-Level Visual-Sensitivity Steering for LVLMs Hallucination Mitigation

arXiv:2606.07647v1 Announce Type: new Abstract: Large vision language models (LVLMs) have made rapid advancements and are deployed across various applications, yet hallucinations remain a major challe

researcharxiv-cs-cv

Still: Amortized KV Cache Compaction in a Single Forward Pass

model-releasesarxiv-cs-lg

arXiv:2606.07878v1 Announce Type: new Abstract: The KV cache is the memory bottleneck of long-horizon language model deployment. Practically, a deployable compactor must be lightweight enough to call

Stochastic Dimension Implicit Functional Projections for Global Integral Conservation in High-Dimensional PINNs

arXiv:2603.29237v2 Announce Type: replace Abstract: Enforcing prescribed global integral constraints in mesh-free neural PDE solvers is challenging in high-dimensional domains. Existing projection met

Hardware

SwiftVR: Real-Time One-Step Generative Video Restoration

arXiv:2606.09516v1 Announce Type: new Abstract: Real-time video restoration (VR) for live streams requires high-resolution outputs under strict per-frame latency constraints. Existing one-step diffusi

hardwarearxiv-cs-cv

Applications

Synthetic but Not Realistic: The Evaluation Challenge in Generative Modelling for Structured Electronic Medical Records

arXiv:2606.08903v1 Announce Type: new Abstract: Synthetic healthcare data are widely proposed as privacy-preserving substitutes for real patient data, yet their evaluation remains dominated by statist

applicationsarxiv-cs-lg

Test-Time Adaptive Composition for Machine Learning as a Service (MLaaS) in IoT Environments

arXiv:2606.07685v1 Announce Type: cross Abstract: The dynamic nature of Internet of Things (IoT) environments affects the long-term effectiveness of Machine Learning as a Service (MLaaS) compositions.

Test-Time Scaling in Multimodal Foundation Models: A Comprehensive Survey of Generation and Reasoning

arXiv:2606.08231v1 Announce Type: new Abstract: Test-time Scaling (TTS) has emerged as a pivotal research direction for enhancing model performance by dynamically allocating computational resources du

researcharxiv-cs-cv

The Label Horizon Paradox: Rethinking Supervision Targets in Financial Forecasting

arXiv:2602.03395v4 Announce Type: replace Abstract: While deep learning has revolutionized financial forecasting through sophisticated architectures, the design of the supervision signal itself is rar

Hardware

Toward Compiler World Models: Learning Latent Dynamics for Efficient Tensor Program Search

arXiv:2606.09312v1 Announce Type: new Abstract: Tensor program optimization is essential for modern machine learning systems, but its search space is enormous. Existing auto-schedulers reduce measurem

hardwarearxiv-cs-lg

Understanding Benchmark Language Under Weakened Formal Semantics

model-releasesarxiv-cs-ai

arXiv:2509.17455v2 Announce Type: replace-cross Abstract: State-of-the-art NLP benchmarks require interpretation of natural language that specifies conditions, procedures, and exceptions, often relyin

VAIC: Vision-Guided Humanoid Agile Object Interaction Control via Decoupled Commands

arXiv:2606.09286v1 Announce Type: new Abstract: Humanoid robots hold immense potential for real-world assistance, yet agile interaction with objects in unstructured environments demands tightly couple

safetyarxiv-cs-ro

Variational Proximal Policy Optimization

arXiv:2606.08032v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback via Proximal Policy Optimization often suffers from policy mode collapse, brittle exploration loops, and di

local-aiarxiv-cs-lg

Tutorials

Weak-Driven Learning: How Weak Agents make Strong Agents Stronger

arXiv:2602.08222v2 Announce Type: replace Abstract: As post-training optimization becomes central to improving large language models, we observe a persistent saturation bottleneck: once models grow hi

tutorialsarxiv-cs-ai

What Makes a Desired Graph for Relational Deep Learning?

arXiv:2606.08491v1 Announce Type: new Abstract: Relational deep learning (RDL) converts relational databases (RDBs) into heterogeneous graphs, but graphs derived directly from database schemas are oft

safetyarxiv-cs-ai

What's the Point? Spatial Grammar & Index Resolution for Sign Language Processing

arXiv:2606.08056v1 Announce Type: cross Abstract: Sign language models are predominantly trained with gloss-sequence or text supervision, thereby under-modeling non-lexical and productive construction