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arXiv:2602.05145v2 Announce Type: replace-cross Abstract: Speculative decoding can substantially accelerate LLM inference, but realizing its benefits in practice is challenging due to evolving workloa

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TOLA: Text-aware One-Step Latent Adaptation for Diffusion-based Text Image Super-Resolution

DGX agent

arXiv:2609.29240v1 Announce Type: cross Abstract: Text image super-resolution (TSR) aims to recover visually faithful and readable text under unknown degradations. Existing diffusion-based methods typ

researcharxiv-cs-ai

25 Sept 2026

Towards Practical Compression of 3D Gaussian Splatting

arXiv:2609.30245v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) enables high-quality novel-view synthesis but requires substantial storage. Existing compression methods often rely on spat

UCON: Uncertainty-aware Navigation with Historical Re-association in Dynamic Environments

arXiv:2609.29419v1 Announce Type: new Abstract: Autonomous navigation in dynamic environments is hindered by two fundamental challenges: perception instability and uncertainty-optimization mismatch. T

agentsarxiv-cs-ro

Understanding and Exploiting Initialization Anchoring Weakness in Feedback-Based Agent Planning

arXiv:2609.29697v1 Announce Type: cross Abstract: Feedback-based planning improves agent reliability by incorporating tool observations and corrective feedback. However, its protection may not be dist

Unlock 3x QPS and microsecond latency with Memorystore for Valkey 9.1

At Google Cloud, we are committed to delivering the best managed experience backed by open source software. Today, we’re announcing the general availability of Memorystore for Valkey 9.1, which achiev

safetygoogle-cloud-ai

VG-TIE: An interpretable tabular-to-image encoding method based on visibility graphs

arXiv:2609.29650v1 Announce Type: new Abstract: Tabular-to-image encoding methods enable the application of models based on both convolutional neural networks and vision transformers to tabular data,

Visual Representation and History Modeling for Navigation World Models

arXiv:2609.29555v1 Announce Type: new Abstract: Navigation World Models (NWMs) predict action-conditioned visual futures for planning. Two practical challenges are central to their design: selecting a

When Explanations Cannot Be Read: Measuring and Correcting SHAP and LIME Rendering for Right-to-Left Languages

arXiv:2609.28565v1 Announce Type: cross Abstract: Post hoc explanation methods such as SHAP and LIME are widely used to interpret text classifiers, but their visualizations are mainly designed for lef

researcharxiv-cs-ai

Hardware

A Scaling Study for fMRI Foundation Models

arXiv:2609.27232v1 Announce Type: new Abstract: Scaling laws have guided large-model development in computer vision and natural language processing, but the relationships among data, model size, and c

hardwarearxiv-cs-lg

AeRSoM: An Aerial Rigid-Soft Integrated Manipulator for Contact-Rich Manipulation

arXiv:2609.28044v1 Announce Type: new Abstract: Contact-rich aerial manipulation remains fundamentally challenging because interaction forces are directly transmitted to the aerial platform, often lea

safetyarxiv-cs-ro

Local Ai

Agentic Governance and Adversarial Verification for Policy-Constrained LLM Healthcare Appeal Generation

arXiv:2609.27844v1 Announce Type: new Abstract: Claim denial management costs U.S. healthcare approximately $260 billion annually in administrative overhead. Large Language Models (LLMs) and Retrieval

local-aiarxiv-cs-ai

Alignment Inertia: Auditing the Durability of Training Data Influence Through Policy Override Resistance

arXiv:2609.27333v1 Announce Type: new Abstract: Platform operators increasingly rely on system prompts and fine-tuning to govern model behavior, yet it remains unclear how reliably these interventions

Amplify: A Lightweight Library for Reproducible Nonlinear Programming Problems in Robotics

model-releasesarxiv-cs-ro

arXiv:2609.28377v1 Announce Type: new Abstract: Optimization problems (OPs) are key to solving many challenging research problems in robotics. However, reproducibility still remains a major issue. In

Anomaly-Free Self-Optimization via AUC Bounds

model-releasesarxiv-cs-lg

arXiv:2609.27362v1 Announce Type: new Abstract: Anomalies are rare, and anomalous data are often unavailable during development, making it difficult to determine which anomaly detection models and con

Artificial intelligence surrogates for treatment effect estimation with before-and-after data

arXiv:2609.27180v1 Announce Type: cross Abstract: Estimating the causal effects of medical treatments is difficult when clinically important outcomes are costly to measure or require long follow-up. S

safetyarxiv-cs-lg

AstraLOD3: Zero-shot multimodal agentic reconstruction of LOD3 building models

model-releasesarxiv-cs-cv

arXiv:2609.28061v1 Announce Type: new Abstract: Automated LOD3 building modeling typically relies on purpose-built geometric or learning-based pipelines, limiting flexibility across heterogeneous buil

Automotive mmWave Spinning Radar Place Recognition with Spatially Gated Feature-Correlation Representation

arXiv:2609.27394v1 Announce Type: cross Abstract: Automotive spinning FMCW radar provides dense, 360^irc sensing and remains reliable under poor illumination and adverse weather, making it well-suited

AWM-VLA: AlignedWorld Modeling for Efficient and Explainable Vision-Language-Action Policies

arXiv:2609.27753v1 Announce Type: new Abstract: Vision-language-action (VLA) models have become a powerful paradigm for generalist robotic manipulation, yet they are often reactive: the policy maps th

BEE: Intervention-Adaptive Real-World Reinforcement Learning with Vision-Language-Action Models

arXiv:2609.27450v1 Announce Type: cross Abstract: Vision-language-action (VLA) models handle long-horizon manipulation, yet success hinges on a few precision-critical phases where millimeter-scale err

safetyarxiv-cs-ai

Beyond Overlap: Estimating the Causal Effect of Benchmark Exposure

model-releasesarxiv-cs-cl

arXiv:2609.27176v1 Announce Type: new Abstract: Evidence that evaluation material entered training does not reveal how much it affected evaluation. This distinction leaves a contaminated benchmark sco

Beyond Poetry: Can Large Language Models Generate Classical Arabic Maqamat?

arXiv:2609.28245v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong performance in creative text generation, yet their ability to produce culturally grounded and stylistic

Beyond Unsafe Detection: Counterfactually Anchored Evidence Attribution for Multi-Turn LLM Safety Failures

arXiv:2609.27773v1 Announce Type: cross Abstract: As Large Language Models (LLMs) move from conversational assistants to advanced agentic systems, guardrail failures can convert adversarial intents in

safetyarxiv-cs-ai

BiCFlow-MER: Orchestrating Discriminative and Generative Multimodal Emotion Recognition via Conditional Transport

arXiv:2609.27615v1 Announce Type: new Abstract: In multimodal emotion recognition (MER), human affective states are inferred by integrating complementary cues from multiple modalities. In audio-text M

Hardware

BladeMaster: Real-Time Robotic Cutting Simulation with Online-Generated Persistent Discontinuities

arXiv:2609.27342v1 Announce Type: new Abstract: Cutting changes both the shape and topology of deformable objects, making accurate simulation challenging for robotic manipulation. A simulator must tra

hardwarearxiv-cs-ro

BrickCraft-Duo: Efficient Dual-Arm Skill Learning and Refinement for Compositional Long-Horizon Assembly

arXiv:2609.28281v1 Announce Type: new Abstract: Interlocking brick assembly provides a representative testbed for evaluating real-world robotic manipulation capabilities, where diverse structural desi

safetyarxiv-cs-ro

CART: Closed-Loop Adaptive Red Teaming for Large Language Models

arXiv:2609.27336v1 Announce Type: new Abstract: Automated red teaming often replays a fixed set of prompts, which measures known risks but cannot learn from failures found during testing. We present C

CAST: Context- and Anomaly Structure-Conditioned Time Series Anomaly Generation

arXiv:2609.27825v1 Announce Type: new Abstract: Anomalous time series play a critical role in safety-critical domains, yet they are inherently scarce, heterogeneous, and costly to obtain. Existing tim

safetyarxiv-cs-lg

CereVLA: Cerebellum-Inspired Consequence-Aware Residual Governance for Efficient Vision-Language-Action Execution

arXiv:2609.27468v1 Announce Type: new Abstract: Action-chunked vision-language-action (VLA) policies improve inference efficiency, but limited feedback within committed action chunks can lead to accum

ChronoSteer: Bridging Large Language Model and Time Series Foundation Model via Synthetic Cross-Modal Alignment Dataset

model-releasesarxiv-cs-lg

arXiv:2505.10083v2 Announce Type: replace Abstract: Conventional forecasting methods are trained end-to-end on unimodal time series, which limits their ability to exploit textual information and under

Comparative Evaluation of Static Embedding Models for HTTP Request Anomaly Detection

arXiv:2609.26860v1 Announce Type: cross Abstract: Web applications are increasingly targeted by cyberattacks that exploit HTTP requests to evade security mechanisms. Traditional web application firewa

Copy-Move Forgery Detection and Question Answering for Remote Sensing Image

model-releasesarxiv-cs-cv

arXiv:2412.02575v3 Announce Type: replace Abstract: Driven by practical demands in land resource monitoring and national defense security, this paper introduces the Remote Sensing Copy-Move Question A

CRISP: Compositional Relations as Invariant Structural Priors for Domain Generalization

arXiv:2605.06043v2 Announce Type: replace Abstract: Domain generalization requires identifying stable representations that support reliable classification across domains. Domains may differ in low-lev

DCRL: Decoupling and Coupling Reinforcement Learning via Policy-Reward Manifold Alignment

arXiv:2609.27572v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as a key paradigm for improving the reasoning capabilities of large language models (LLMs). However, existing

safetyarxiv-cs-ai

DMM-Align: Closed-Loop Optimization for 2D-3D Registration with Dual-Role Diffusion

arXiv:2609.27794v1 Announce Type: new Abstract: 2D-3D registration remains brittle in challenging scenarios such as low overlap, occlusion, repetitive structures, and severe cross-modal ambiguity. A k

EmbodiedSWE: Coding Agents for Long Horizon Dexterous Robotics

model-releasesarxiv-cs-ro

arXiv:2609.27308v1 Announce Type: new Abstract: We study coding agents for long-horizon, dexterous robotics and ask whether their solutions can provide scalable supervision for learning general robot

EnComp: Lightweight Encoder-Only Context Compression for Retrieval-Augmented Question Answering

arXiv:2603.09222v2 Announce Type: replace Abstract: Efficient context compression is critical for retrieval-augmented question answering in resource-constrained settings, where long retrieved contexts

researcharxiv-cs-cl

Local Ai

Energy-guided Recursive Model

arXiv:2607.10128v3 Announce Type: replace Abstract: Recursive models show promise on reasoning and language tasks, yet their test-time scaling lacks a principled criterion for selecting trajectories o

local-aiarxiv-cs-lg

Evolutionary Stability Does Not Guarantee Learning Accessibility: A Multi-Agent Reinforcement Learning Perspective on Cooperation Emergence

arXiv:2609.27664v1 Announce Type: new Abstract: Cooperation emergence is a central problem in multi-agent systems because decentralized agents must coordinate while adapting to the changing behavior o

FedIncome: Federated Learning for Income Estimation in Digital Lending Under Data Sovereignty Constraints

model-releasesarxiv-cs-lg

arXiv:2609.27654v1 Announce Type: cross Abstract: Verified income is often unavailable in digital loan applications, forcing lenders to rely on reported income and potentially leading to over-lending,

Field-of-View Extension in Dental Cone-Beam CT via Implicit Neural Representations and Diffusion Model-Based Refinement

arXiv:2609.28110v1 Announce Type: cross Abstract: Dental cone-beam computed tomography (CBCT) systems often employ detector configurations that provide a truncated field of view (FOV) that only captur

researcharxiv-cs-ai

Forget who you Forgot: Speaker Unlearning to Prevent Re-Identification in Zero-Shot Text-to-Speech

arXiv:2609.27399v1 Announce Type: cross Abstract: Recent zero-shot text-to-speech (ZS-TTS) systems can reproduce a speaker's voice with high fidelity from only a few seconds of reference speech, raisi

researcharxiv-cs-ai

From Alignment to Fusion in 3D Vision-Language

arXiv:2609.28222v1 Announce Type: new Abstract: Unified 3D vision-language systems must combine complementary geometry, scale, and appearance cues while supporting tasks from instance segmentation to

From LiDAR Maps to Visual Localization: Unified Visual Association for Robust Point-Line-Plane Pose Estimation

model-releasesarxiv-cs-ro

arXiv:2609.27363v1 Announce Type: new Abstract: Camera localization in a prior LiDAR map provides a persistent geometric reference for long-term robotic navigation, yet remains challenging because of

Gender Bias in Vision-Language In-Context Learning

arXiv:2609.27682v1 Announce Type: new Abstract: In-context learning (ICL) enables large vision-language models (LVLMs) to perform tasks by following patterns from in-context examples, yet its potentia

Generalizable Robotic Insertion with World Models

arXiv:2609.28258v1 Announce Type: cross Abstract: Robotic assembly in high-mixture settings requires adaptable systems that can handle diverse parts, yet current approaches typically rely on policies

Geometry-anchored PET-aware multimodal pseudo-CT synthesis for whole-body attenuation correction: the BIC-MAC Challenge

arXiv:2609.27848v1 Announce Type: new Abstract: The BIC-MAC challenge targets whole-body pseudo-CT synthesis from NAC-PET, Dixon MRI, and a 2D topogram for CT-less PET attenuation correction. We propo

GLOW: Global Illumination-Aware Inverse Rendering of Indoor Scenes Captured with Dynamic Co-Located Light & Camera

arXiv:2511.22857v2 Announce Type: replace Abstract: Inverse rendering of indoor scenes remains challenging due to the ambiguity between reflectance and lighting, exacerbated by inter-reflections among