Search: “inference”

STAR-Pro: Stage-Wise Token Adaptive Reduction with Progressive Refinement for Efficient Large Vision-Language Models

arXiv:2609.05916v1 Announce Type: new Abstract: Large vision-language models (LVLMs) achieve strong multimodal understanding, but the hundreds to thousands of visual tokens they process impose substan

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Model Releases

STP-BENCH: A Unified Systematic Benchmark for Virtual Spatial Transcriptomics from Histopathology Images

DGX agent

arXiv:2609.05956v1 Announce Type: new Abstract: Spatial transcriptomics (ST) provides unprecedented insights into tumor heterogeneity by capturing spatially resolved gene expression, yet its high expe

model-releasesarxiv-cs-cv

9 Sept 2026

Subject-Relative Micro-Motion and Sleep Dynamics for Near-Infrared Video Sleep Staging

arXiv:2609.05550v1 Announce Type: new Abstract: Near-infrared (NIR) video is a promising modality for contactless sleep monitoring, but recent video-based sleep staging methods often use it as a route

Supervised Cross-Modal Feature Alignment for Zero-Wearable Freezing of Gait Detection in Parkinsonism

arXiv:2609.08317v1 Announce Type: new Abstract: Objective assessment of Freezing of Gait (FoG) in Parkinson's disease (PD) relies predominantly on wearable Inertial Measurement Units (IMUs). While IMU

safetyarxiv-cs-cv

Sustained Performance and Energy Accounting for Nonlinear Forecasting Across Classical and Simulated Quantum Models

arXiv:2510.25183v2 Announce Type: replace-cross Abstract: Energy-efficient AI should be evaluated across the full application pipeline, not only by lowest error or shortest training time. We study thi

Applications

SWE-Tester: Training Open-Source LLMs for Issue Reproduction in Real-World Repositories

arXiv:2601.13713v2 Announce Type: replace-cross Abstract: Software testing is crucial for ensuring the correctness and reliability of software systems. Automated generation of issue reproduction tests

applicationsarxiv-cs-lg

TBDub: Production-Oriented Visual Dubbing

arXiv:2609.06144v1 Announce Type: new Abstract: Visual dubbing must synchronize mouth motion with replacement speech while preserving identity, appearance, and temporal consistency. Although X-Dub pro

hardwarearxiv-cs-cv

The BatchNorm Illusion: Diagnosing Normalization Artifacts in Machine Unlearning Evaluation

arXiv:2609.08901v1 Announce Type: new Abstract: Approximate machine unlearning aims to remove the influence of specific training data from a trained model without retraining from scratch. We identify

safetyarxiv-cs-lg

Tutorials

The Rules-and-Facts Model for Simultaneous Generalization and Memorization in Neural Networks

arXiv:2603.25579v2 Announce Type: replace-cross Abstract: A key capability of modern neural networks is their capacity to simultaneously learn underlying rules and memorize specific facts or exception

tutorialsarxiv-cs-lg

Topology-induced Operators Reveal Complementary Graph Representations without Training

arXiv:2609.08152v1 Announce Type: new Abstract: Graph representation learning has largely focused on designing increasingly sophisticated models to transform graph topology into vector representations

researcharxiv-cs-lg

Transformers as In-Context Samplers: From Closed-Form Diffusion to Estimation-Free Sampling

arXiv:2609.08981v1 Announce Type: new Abstract: A growing body of work establishes that large language models are not mere statistical memorizers, but are capable of in-context learning: performing in

Uni-Light: An Ultra-Lightweight Framework via Uncertainty-Aware Knowledge Distillation for Brain Tumour Segmentation

arXiv:2609.06729v1 Announce Type: new Abstract: Accurate 3D brain tumour segmentation from multi-modal Magnetic Resonance Imaging (MRI) is essential for clinical diagnosis and treatment planning. Exis

Unified Long Video Inpainting and Outpainting via Overlapping High-Order Co-Denoising

arXiv:2511.03272v2 Announce Type: replace Abstract: Diffusion-based text-to-video models are increasingly capable, but mask-based editing over hundreds of frames remains challenging: naive long-video

safetyarxiv-cs-cv

Applications

Unified Multi-Layer Subspace Modeling for Cross-Domain OOD Detection

arXiv:2609.06785v1 Announce Type: new Abstract: Out-of-Distribution (OOD) detection remains a fundamental challenge for neural networks, whose predictions can be overconfident on inputs that deviate f

applicationsarxiv-cs-cv

Unsupervised Transfer Clustering for Mitigating Cold Start in Active Prompt Learning

arXiv:2609.05636v1 Announce Type: new Abstract: Vision-Language Models (VLMs) are able to achieve impressive zero-shot classification performance by aligning visual and textual representations, but ea

VLA-Corrector: Stage-Aware Observable State Understanding for Prompt-Based Closed-Loop Recovery of Vision-Language-Action Policies

model-releasesarxiv-cs-ro

arXiv:2609.06508v1 Announce Type: new Abstract: Long-horizon robot manipulation with Vision-Language-Action (VLA) policies remains vulnerable to execution-time deviations, as final task success provid

A Removal Based Approach to Improve LLM Faithfulness at Test-Time

arXiv:2609.04343v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for consequential decisions, making their explanations an important tool for auditing model behavior.

safetyarxiv-cs-ai

A Schema Bounded Language Model for Refining Robot Policies Without Destabilizing Local Learning

arXiv:2609.05133v1 Announce Type: cross Abstract: This paper addresses navigation by composite heterogeneous robots in a decentralized system when policy reasoning and local control operate at differe

local-aiarxiv-cs-ai

A Systematic Evaluation of Cross-Lingual Consistency Enhancement Methods in Multilingual Language Models

model-releasesarxiv-cs-ai

arXiv:2609.04409v1 Announce Type: cross Abstract: Multilingual language models often produce inconsistent answers to semantically equivalent questions across languages, motivating methods to improve c

A Verifier-Guided Explainable Reasoning Framework with Gold-Anchored QLoRA, Task-Aware Mixture-of-Experts, and Group-Relative RLVR

arXiv:2609.05221v1 Announce Type: cross Abstract: Large language models (LLMs) show strong reasoning ability, but their explanations can remain inconsistent, weakly grounded, or difficult to verify. W

safetyarxiv-cs-ai

ACE: Adaptive Calibration-Free Expert Skipping for MoE-based LLMs

arXiv:2609.05228v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) architectures provide an efficient paradigm for scaling large language models (LLMs), yet fixed top-k routing activates the sam

researcharxiv-cs-ai

Agents

An Energy-Based Conservative-Dissipative Latent Neural Evolution Operator for Magnetization Dynamics

arXiv:2609.04530v1 Announce Type: new Abstract: We develop an energy-based reduced-order model for micromagnetic magnetization dynamics that couples a convolutional autoencoder to a structured latent

agentsarxiv-cs-lg

Aplaud: Adaptive Personalized Low-Rank Decomposition for User-Specific LLM

model-releasesarxiv-cs-ai

arXiv:2609.04738v1 Announce Type: new Abstract: In this paper, we study the problem of personalized survey response prediction using fine-tuned large language models (LLMs). This task poses unique cha

ARC-Loc: Leveraging Azimuthal Ray Convergence as a Geometric Cue for Direct Cross-View Localization

arXiv:2609.04965v1 Announce Type: new Abstract: Cross-view localization (CVL) estimates the pose of a ground image by matching it to a geo-referenced satellite image. To bridge the extreme viewpoint g

local-aiarxiv-cs-cv

Auditing Bias and Safety in Voice AI Customer Care

arXiv:2609.04206v1 Announce Type: cross Abstract: Voice AI systems increasingly mediate customer care interactions where caller presentation cues such as accent, affect, fluency, and urgency are avail

safetyarxiv-cs-cl

AVENUE: Audio-Video EditiNg Understanding and Evaluation

model-releasesarxiv-cs-cv

arXiv:2609.04253v1 Announce Type: cross Abstract: Audio-video (AV) editing aims to modify audio and video content according to a target prompt. Unlike single-modality editing, AV editing requires mode

CLON: Cue-Calibrated Linguistic Object Onboarding for Zero-Shot 6D Pose Front-Ends

arXiv:2609.04784v1 Announce Type: new Abstract: Zero-shot 6D pose estimation pipelines increasingly rely on strong downstream pose solvers, but their performance is often limited by the front-end: obj

Agents

Constructing and Evaluating Clinical Reasoning Trajectories for Medical Agent

arXiv:2609.05090v1 Announce Type: new Abstract: Evaluation of medical artificial intelligence agents remains predominantly answer-centric, assessing only the correctness of final outputs while overloo

agentsarxiv-cs-ai

CPR-IE:A Compression-Prediction-Resource Intelligence Efficiency Metric

arXiv:2609.04809v1 Announce Type: new Abstract: Comparing intelligent systems under deployment constraints requires more than predictiveaccuracy.This paper develops Compression-Prediction-Resource Int

researcharxiv-cs-ai

Agents

CrossDepth: Geometry-Constrained Attention for Generalizable Multi-View Surround Depth Estimation

arXiv:2609.05397v1 Announce Type: new Abstract: Reliable 3D understanding of the surrounding environment is a core requirement for autonomous driving. Multi-view surround camera rigs provide broad sce

agentsarxiv-cs-cv

Distilled Continuous Diffusion Language Models Can Write Code in Few Steps---or One

arXiv:2609.04531v1 Announce Type: new Abstract: Language generation is almost universally treated as a sequential process: autoregressive models emit one token at a time, while diffusion language mode

researcharxiv-cs-lg

Encore: Infinite Audio-Video Generation with Adaptive Signal Routing

arXiv:2609.04249v1 Announce Type: cross Abstract: Existing audio-video generation methods produce well-synchronized clips but are limited to short durations, while long-video generation methods extend

local-aiarxiv-cs-cv

From Deep to Shallow: Unconstrained and Efficient Layer Merging Strategy

arXiv:2609.04881v1 Announce Type: new Abstract: Although Deep Neural Networks have become foundational in many areas of Machine Learning, high computational demands limit their application in resource

From Interpretability Methods to Interpretable Models

arXiv:2609.05399v1 Announce Type: new Abstract: More than a decade in, explainable AI (XAI) for computer vision has assembled a mature toolbox: attribution, feature visualization, concept-based, and c

GEPARD - Generative, Prosody-aware, Autoregressive text-to-speech model for Realtime Dialogue

arXiv:2609.04222v1 Announce Type: cross Abstract: We present GEPARD (Generative, Prosody-aware, Autoregressive text-to-speech model for Realtime Dialogue), a streaming text-to-speech model for real-ti

hardwarearxiv-cs-cl

HaptiNet: Networked Haptic Robots Enable Physical Co-presence in Geographically-Unconstrained Rehabilitation

arXiv:2609.04799v1 Announce Type: new Abstract: Cooperative rehabilitation enhances engagement, task performance, and social-motor interaction, yet it demands physical co-presence: users must transmit

researcharxiv-cs-ro

Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models

arXiv:2503.24377v2 Announce Type: replace-cross Abstract: Recent advancements in Large Language Models (LLMs) have significantly enhanced their ability to perform complex reasoning tasks, transitionin

researcharxiv-cs-ai

Human-Human & Human-Robot Interaction Transformer (H2INT) for Robot Navigation in Dense and Uncertain Crowds

arXiv:2609.05300v1 Announce Type: new Abstract: Safe robot navigation in dense crowds requires reasoning about pedestrian motion and how it may change in response to a robot. However, many learning-ba

safetyarxiv-cs-ro

IPGeoAI: Transformer-Based Geolocation with LLM Semantic Fusion

arXiv:2609.04559v1 Announce Type: new Abstract: Accurate city-level IP Geolocation is an important enabler for the modern digital ecosystem, underpinning services ranging from local content delivery a

local-aiarxiv-cs-ai

Iris: Climbing to the Search Frontier

model-releasesarxiv-cs-ai

arXiv:2609.04304v1 Announce Type: new Abstract: We present Iris-mini and Iris-pro, two search agents trained at the 35B-A3B and 397B-A17B scales, together with the data pipeline and training recipe be

KVMem: Virtualizing Million-Token Agent Workspaces on a Consumer GPU

arXiv:2609.04852v1 Announce Type: new Abstract: Modern LLM agents operate in persistent workspaces whose accumulated history can exceed both GPU KV capacity and the model's native context window. Exis

LookThere! Sparse Vision by Reinforced Selection

arXiv:2609.04698v1 Announce Type: new Abstract: Vision transformers typically treat every image token as equally important, yet for most tasks in computer vision only a fraction are needed. Adaptive c

Low-Latency Spell Correction for Japanese Music Search Queries

arXiv:2609.04262v1 Announce Type: cross Abstract: Spell correction for Japanese search queries presents unique challenges due to the co-existence of four writing scripts (Latin/romaji, hiragana, katak

hardwarearxiv-cs-lg

MCPO: Modality-Contrastive Preference Optimization for Multimodal Chain-of-Thought Compression

arXiv:2609.04947v1 Announce Type: cross Abstract: Recently, multimodal large-scale reasoning models have demonstrated remarkable capabilities in solving complex tasks through long Chains-of-Thought (M

safetyarxiv-cs-ai

Measuring proximity to standard planes during fetal brain ultrasound scanning

arXiv:2404.07124v2 Announce Type: replace-cross Abstract: This paper presents a pipeline designed to bring ultrasound (US) plane pose estimation closer to clinical use, demonstrating the feasibility o

hardwarearxiv-cs-ai

MINT: A Unified Model for World-Space Camera and Hand Motion Estimation from Scalable Egocentric Pipeline Supervision

arXiv:2609.04958v1 Announce Type: new Abstract: Recovering camera and hand motion in world coordinates from egocentric video is a key capability for activity understanding, robot learning, and augment

Mitra-v2 Technical Report

arXiv:2609.04540v1 Announce Type: new Abstract: We introduce Mitra-v2, a tabular foundation model that delivers state-of-the-art performance on real-world classification and regression problems, from

Applications

MomentQuant: an even more minimalist interval method with linear time complexity for time series classification

arXiv:2609.05136v1 Announce Type: new Abstract: Time series data is very common in many real-world applications and in numerous domains, with increasing interest for automated information extraction u

applicationsarxiv-cs-lg