Search: “inference”

Q-DiT4SR: Exploration of Detail-Preserving Diffusion Transformer Quantization for Real-World Image Super-Resolution

arXiv:2602.01273v4 Announce Type: replace Abstract: Recently, Diffusion Transformers (DiTs) have emerged in Real-World Image Super-Resolution (Real-ISR) to generate high-quality textures, yet their he

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Q-SpiRL: Quantum Spiking Reinforcement Learning for Adaptive Robot Navigation

DGX agent

arXiv:2605.20801v1 Announce Type: new Abstract: Adaptive robot navigation in dynamic environments requires policies that can reach the target reliably while producing efficient and stable trajectories

safetyarxiv-cs-ro

21 May 2026

R2AoP: Reliable and Robust Angle of Progression Estimation from Intrapartum Ultrasound

arXiv:2605.21099v1 Announce Type: new Abstract: Accurate estimation of the Angle of Progression (AoP) from intrapartum transperineal ultrasound is critical for objective assessment of labor progressio

local-aiarxiv-cs-cv

RCGDet3D: Rethinking 4D Radar-Camera Fusion-based 3D Object Detection with Enhanced Radar Feature Encoding

arXiv:2605.21112v1 Announce Type: new Abstract: 4D automotive radar is indispensable for autonomous driving due to its low cost and robustness, yet its point cloud sparsity challenges 3D object detect

Tutorials

Reducing Object Hallucination in LVLMs via Emphasizing Image-negative Tokens

arXiv:2605.21300v1 Announce Type: new Abstract: Object hallucination is a significant challenge that hinders the application of large vision-language models (LVLMs) in practice. We hypothesize that on

tutorialsarxiv-cs-cv

ReMATF: Recurrent Motion-Adaptive Multi-scale Turbulence Mitigation for Dynamic Scenes

arXiv:2605.21440v1 Announce Type: new Abstract: Atmospheric turbulence severely degrades video quality by introducing distortions such as geometric warping, blur, and temporal flickering, posing signi

researcharxiv-cs-cv

RePCM: Region-Specific and Phenotype-Adaptive Bi-Ventricular Cardiac Motion Synthesis

arXiv:2605.21237v1 Announce Type: new Abstract: Cardiac motion over a cardiac cycle is crucial for quantifying regional function and is strongly affected by cardiovascular diseases. Since temporally d

local-aiarxiv-cs-cv

Retrospective Sparse Attention for Efficient Long-Context Generation

arXiv:2508.09001v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed in long-context tasks such as reasoning, code generation, and multi-turn dialogue. However, i

researcharxiv-cs-cl

Reviving Error Correction in Modern Deep Time-Series Forecasting

arXiv:2605.21088v1 Announce Type: new Abstract: Modern deep-learning models have achieved remarkable success in time-series forecasting. Yet, their performance degrades in long-term prediction due to

researcharxiv-cs-lg

ROAR-3D: Routing Arbitrary Views for High-Fidelity 3D Generation

arXiv:2605.21121v1 Announce Type: new Abstract: Single-image-to-3D generative models can now produce high-quality geometry, yet conditioning on a single view inevitably introduces ambiguity about unse

researcharxiv-cs-cv

Scale-Calibrated Median-of-Means for Robust Distributed Principal Component Analysis

arXiv:2605.20681v1 Announce Type: cross Abstract: Distributed principal component analysis (PCA) produces node-level estimates of both a mean vector and a principal subspace. Robustly aggregating thes

Self-Refining Video Sampling

arXiv:2601.18577v2 Announce Type: replace Abstract: Modern video generators still struggle with complex physical dynamics, often falling short of physical realism. Existing approaches address this usi

safetyarxiv-cs-cv

Single-Pass, Depth-Selective Reading for Multi-Aspect Sentiment Analysis

arXiv:2605.20998v1 Announce Type: new Abstract: Aspect-Term Sentiment Analysis (ATSA) in multi-aspect sentences faces a fundamental tradeoff between efficiency and expressiveness. Existing models eith

researcharxiv-cs-cl

Spectral Souping: A Unified Framework for Online Preference Alignment

arXiv:2605.20408v1 Announce Type: new Abstract: Reinforcement Learning from Human Feedback (RLHF) effectively aligns Large Language Models (LLMs) with aggregate human preferences but often fails to ad

safetyarxiv-cs-lg

SpineContextResUNet: A Computationally Efficient Residual UNet for Spine CT Segmentation

arXiv:2605.20760v1 Announce Type: new Abstract: Automated segmentation of the vertebral column in Computed Tomography (CT) scans is a prerequisite for pathological assessment and surgical planning. Ho

local-aiarxiv-cs-cv

STiTch: Semantic Transition and Transportation in Collaboration for Training-Free Zero-Shot Composed Image Retrieval

arXiv:2605.21261v1 Announce Type: new Abstract: Training-free zero-shot composed image retrieval models are recently gaining increasing research interest due to their generalizability and flexibility

safetyarxiv-cs-cv

SymbolicLight V1: Spike-Gated Dual-Path Language Modeling with High Activation Sparsity and Sub-Billion-Scale Pre-Training Evidence

arXiv:2605.21333v1 Announce Type: new Abstract: Natively trained spiking language models struggle to combine Transformer-like language quality, stable multi-domain pre-training, and high activation sp

The General Theory of Localization Methods

arXiv:2605.20635v1 Announce Type: new Abstract: This paper proposes a general machine learning framework called the localization method, which is fundamentally built on two core concepts: localization

The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering

arXiv:2605.20745v1 Announce Type: cross Abstract: Generative verifiers have emerged as a promising paradigm for step-wise verification, but their verification behavior is often poorly calibrated: they

researcharxiv-cs-cl

The Visual Iconicity Challenge: Evaluating Vision-Language Models on Sign Language Form-Meaning Mapping

arXiv:2510.08482v3 Announce Type: replace-cross Abstract: Iconicity, the resemblance between linguistic form and meaning, is pervasive in signed languages, offering a natural testbed for visual ground

TreeText-CTS: Compact, Source-Traceable Tree-Path Evidence for Irregular Clinical Time-Series Prediction

arXiv:2605.20292v1 Announce Type: new Abstract: Numerical time-series models can effectively process irregular electronic health record (EHR) trajectories, but they do not naturally expose the measure

researcharxiv-cs-lg

Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs

arXiv:2505.19075v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have demonstrated remarkable general capabilities, but enhancing skills such as reasoning often demands substanti

Velocityformer: Broken-Symmetry-Matched Equivariant Graph Transformers for Cosmological Velocity Reconstruction

arXiv:2605.21483v1 Announce Type: cross Abstract: Precise measurement of the kinematic Sunyaev-Zel'dovich (kSZ) effect - a probe of the large-scale distribution of baryonic matter, a key observable fo

safetyarxiv-cs-lg

Agents

What if Agents Could Imagine? Reinforcing Open-Vocabulary HOI Comprehension through Generation

arXiv:2602.11499v2 Announce Type: replace Abstract: Multimodal Large Language Models have shown promising capabilities in bridging visual and textual reasoning, yet their reasoning capabilities in Ope

agentsarxiv-cs-cv

WildRoadBench: A Wild Aerial Road-Damage Grounding Benchmark for Vision-Language Models and Autonomous Agents

arXiv:2605.20306v1 Announce Type: new Abstract: We introduce WildRoadBench, a wild aerial road-damage grounding benchmark that couples direct visual grounding by vision-language models with autonomous

A Family of Divergence Measures for Evaluating the Reconstruction Quality of Explainable Ensemble Trees

model-releasesarxiv-cs-lg

arXiv:2605.19618v1 Announce Type: new Abstract: Validating interpretable surrogate models for ensemble learners requires measuring agreement between the ensemble's internal representation and its surr

Automatically Improving Simulation Physics for Articulated Objects

arXiv:2605.19136v1 Announce Type: new Abstract: Simulation is a central tool for scalable robot learning, but its effectiveness depends on the quality of object assets. While modern 3D datasets provid

safetyarxiv-cs-ro

Backtracking When It Strays: Mitigating Dual Exposure Biases in LLM Reasoning Distillation

arXiv:2605.19433v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success in complex reasoning tasks via long chain-of-thought (CoT), yet their immense computatio

safetyarxiv-cs-ai

Boosting Text-to-Image Diffusion Models via Core Token Attention-Based Seed Selection

arXiv:2605.19532v1 Announce Type: new Abstract: Text-to-image diffusion models can synthesize high-quality images, yet the outcome is notoriously sensitive to the random seed: different initial seeds

safetyarxiv-cs-cv

BrainDyn: A Sheaf Neural ODE for Generative Brain Dynamics

arXiv:2605.19324v1 Announce Type: new Abstract: Efficient neural network models that generate brain-like dynamic activity can be a valuable resource for generating synthetic data, analyzing difference

researcharxiv-cs-lg

Tutorials

CANINE: Coaching Visually Impaired Users for Interactive Navigation with a Robot Guide Dog

arXiv:2605.19501v1 Announce Type: cross Abstract: Robot guide dogs offer navigation assistance that greatly expands the independent mobility of the visually impaired, but their effective use requires

tutorialsarxiv-cs-ai

Causal Evidence for Attention Head Imbalance in Modality Conflict Hallucination

model-releasesarxiv-cs-ai

arXiv:2605.19250v1 Announce Type: new Abstract: Modality-conflict hallucination occurs when multimodal large language models (MLLMs) prioritize erroneous textual premises over contradictory visual evi

Agents

CMAD: Cooperative Multi-Agent Diffusion via Stochastic Optimal Control

arXiv:2602.10933v2 Announce Type: replace Abstract: Continuous-time generative models have achieved remarkable success in image restoration and synthesis. However, controlling the composition of multi

agentsarxiv-cs-lg

Code-Guided Reasoning for Small Language Models: Evaluating Executable MCQA Scaffolds

arXiv:2605.18827v1 Announce Type: cross Abstract: Multiple-choice QA benchmarks usually evaluate small language models (SLMs) as direct answerers, but deployed language-model systems increasingly rely

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models in Mathematical Reasoning

arXiv:2507.15698v2 Announce Type: replace-cross Abstract: Process Reward Models (PRMs) play a central role in evaluating and guiding multi-step reasoning in large language models (LLMs), especially fo

safetyarxiv-cs-ai

CompoSE: Compositional Synthesis and Editing of 3D Shapes via Part-Aware Control

arXiv:2605.19350v1 Announce Type: cross Abstract: Creating and editing high-quality 3D content remains a central challenge in computer graphics. We address this challenge by introducing CompoSE, a nov

CopT: Contrastive On-Policy Thinking with Continuous Spaces for General and Agentic Reasoning

arXiv:2605.20075v1 Announce Type: cross Abstract: Chain-of-thought (CoT) is a standard approach for eliciting reasoning capabilities from large language models (LLMs). However, the common CoT paradigm

safetyarxiv-cs-ai

D^3-Subsidy: Online and Sequential Driver Subsidy Decision-Making for Large-Scale Ride-Hailing Market

model-releasesarxiv-cs-lg

arXiv:2605.20036v1 Announce Type: new Abstract: Ride-hailing platforms like DiDi Chuxing operate in highly dynamic environments where balancing driver supply and passenger demand is critical. Although

Descriptive versus Regulatory Uncertainty in Bounded Predictive Systems

arXiv:2605.18909v1 Announce Type: new Abstract: Any system that models the world under finite representational capacity must compress; any compression entails a prior; and the prior is the system's bi

Disentangling generalization and memorization in large language models using chess

model-releasesarxiv-cs-ai

arXiv:2601.16823v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) exhibit remarkable capabilities, yet it remains unclear to what extent these reflect sophisticated recall or genu

Dual-Channel Tensor Neural Networks: Finite-Sample Theory and Conformal Structure Selection

arXiv:2605.19122v1 Announce Type: cross Abstract: Tensor-valued data arise naturally in neuroimaging, genomics, climate science, and spatiotemporal networks, where multilinear dependencies across mode

Dual-Gated Epistemic Time-Dilation: Autonomous Compute Modulation in Asynchronous MARL

arXiv:2603.23722v2 Announce Type: replace-cross Abstract: While Multi-Agent Reinforcement Learning (MARL) algorithms achieve unprecedented successes across complex continuous domains, their standard d

safetyarxiv-cs-lg

EmbGen: Teaching with Reassembled Corpora

arXiv:2605.19394v1 Announce Type: cross Abstract: Adapting small instruction-tuned models to specialized domains often relies on supervised fine-tuning (SFT) on curated instruction-response examples,

researcharxiv-cs-ai

EventPrune: Cascaded Event-Assisted Token Pruning for Efficient First-Person Dynamic Spatial Reasoning

arXiv:2605.19506v1 Announce Type: new Abstract: First-person dynamic spatial reasoning requires models to track continuous motion and precise geometric structure, but the quadratic attention cost of T

Applications

Exploiting Non-Negativity in DAG Structure Learning

arXiv:2605.19947v1 Announce Type: new Abstract: This work addresses the problem of learning directed acyclic graphs (DAGs) from nodal observations generated by a linear structural equation model. DAG

applicationsarxiv-cs-lg

Exposing Functional Fusion: A New Class of Strategic Backdoor in Dynamic Prompt Architectures

arXiv:2605.19478v1 Announce Type: cross Abstract: Existing ViT backdoor attacks based on backbone-overwriting full-tuning are computationally expensive and inflict performance degradation. This has fo

FedMental: Evaluating Federated Learning for Mental Health Detection from Social Media Data

arXiv:2605.18936v1 Announce Type: cross Abstract: Social media text data are often used to train Machine Learning (ML) models to identify users exhibiting high-risk mental health behaviors. However, s

FGSVQA: Frequency-Guided Short-form Video Quality Assessment

arXiv:2605.20016v1 Announce Type: cross Abstract: Short-form video poses new challenges to the quality assessment of user-generated content (UGC) due to its complex generation pipeline, rapid content

researcharxiv-cs-cv