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arXiv:2609.23875v1 Announce Type: new Abstract: The rapid growth of resident space objects is increasing the complexity of space situational awareness sensor tasking, challenging classical optimizatio

agentsarxiv-cs-lg

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Safety

VLPSA: Vision-Language-Poisson-Safe Actions for Full-Body Safety of Learned Policies

DGX agent

arXiv:2609.22462v1 Announce Type: new Abstract: Vision-language-action (VLA) models enable increasingly general-purpose robotic manipulation, but such learned policies do not provide safety guarantees

safetyarxiv-cs-ro

22 Sept 2026

VPRune: Efficient Training-free Pre-LLM Visual Token Pruning

arXiv:2609.24485v1 Announce Type: new Abstract: Visual token pruning is a promising approach to reducing the inference cost of large vision-language models (LVLMs), yet aggressive token reduction ofte

safetyarxiv-cs-cv

WaveFront Decoding: Parallelized Self-Speculative Decoding for Looped Language Models

model-releasesarxiv-cs-lg

arXiv:2609.23033v1 Announce Type: new Abstract: Looped language models repeatedly apply a weight-shared block to increase effective depth without increasing parameter count, but the resulting T sequen

Weak Ties, Strong Signals: Efficient Training Data Detection in Diffusion LLMs via Independent Token Sampling

arXiv:2609.22145v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a compelling alternative to autoregressive models, yet they may expose sensitive training data during de

researcharxiv-cs-cl

WebMRIQC: A Web-Based Implementation of MRIQC for Accessible MRI Image Quality Assessment in Resource-Constrained Settings

arXiv:2609.24014v1 Announce Type: new Abstract: Reliable quality control (QC) of magnetic resonance imaging (MRI) is essential for reliable diagnostic neuroimaging, yet standard manual assessment is s

What Can a Recurrent State Safely Forget?

arXiv:2609.23366v1 Announce Type: new Abstract: Recurrent models must preserve information that changes future behavior while suppressing hidden-state error. These objectives conflict: contraction imp

safetyarxiv-cs-lg

When and Why Do Linear Bias Probes Fail? A Geometric and Statistical Theory of Bias Detectability in Large Language Model Representations

arXiv:2609.22337v1 Announce Type: cross Abstract: Linear probing is the standard instrument for detecting social biases in the hidden representations of large language models. Yet reported probe accur

safetyarxiv-cs-lg

When Does Adversarial Refinement Help? A Negative Result and Open Problem in Adapting R3GAN to Time Series Imputation

arXiv:2609.23102v1 Announce Type: new Abstract: Diffusion models and transformers have supplanted GANs for multivariate time series imputation, largely on grounds of GAN training instability. R3GAN (N

researcharxiv-cs-lg

Why Ghost Outputs Teach: A Kernel-Based Understanding of Subliminal Learning

arXiv:2609.23260v1 Announce Type: new Abstract: Subliminal Learning (SL) is a recently identified phenomenon in which a student model acquires downstream task capabilities by matching seemingly unrela

researcharxiv-cs-lg

Local Ai

WOLF: World Model Guided LiDAR Exploration with Predictive Frontiers

arXiv:2609.23656v1 Announce Type: new Abstract: LiDAR-based unmanned aerial vehicle (UAV) exploration builds maps by continually selecting where to observe next. However, decisions based on the measur

local-aiarxiv-cs-ro

XYEval: Agents say yes to bad advice

model-releasesarxiv-cs-cl

arXiv:2609.23939v1 Announce Type: new Abstract: Effective communication between users and AI agents is essential for human-AI collaboration. The XY problem is a well-known communication pitfall where

Yarn tracking of large-scale 3D textile reinforcements using topological material features

arXiv:2609.22315v1 Announce Type: new Abstract: Automated segmentation of CT images has become increasingly important to enhance the reliability of simulations through the generation of high fidelity

Zeva-Ego: Egocentric Mid-Training with In-Context Causal Learning for Robot Manipulation

arXiv:2609.24411v1 Announce Type: new Abstract: Egocentric video offers a scalable source of physical interaction experience, yet translating it into robot-executable knowledge and enabling continual

2D GauSS-MI: Efficient Active Scene Reconstruction with Balanced Visual and Geometric Quality

arXiv:2609.21516v1 Announce Type: new Abstract: Active reconstruction requires efficient active view selection to achieve high-quality reconstruction within limited onboard computational resources. Ex

4DGS-Fixer: Generative Sparse-View 4D Gaussian Splatting with Iterative Refinement Guided by Video Diffusion Priors

model-releasesarxiv-cs-cv

arXiv:2609.21176v1 Announce Type: new Abstract: This paper addresses the challenges of dynamic scene synthesis from sparse-view videos. Existing methods employ geometric priors, adaptive optimization,

Ability-Residual Decoupled Modeling for Affective Cognitive Diagnosis

arXiv:2609.21214v1 Announce Type: new Abstract: Cognitive diagnosis infers students' concept mastery from response logs. However, students' responses are not determined by mastery alone: non-cognitive

safetyarxiv-cs-ai

AcousticDiffusion: Semantically Conditioned Audio-Guided Diffusion Policy for Search-and-Rescue Assistance

arXiv:2609.21792v1 Announce Type: new Abstract: Navigating toward human callers is an important capability for rescue robots operating where visual contact is degraded or occluded. We present Acoustic

Agents

AgenticSwarm: Semantic Perception and Adaptive Task Allocation for Heterogeneous Multi-UAV Missions

arXiv:2609.21716v1 Announce Type: new Abstract: Multi UAV missions in complex environments require the system to understand both the surrounding scene and the intent of a human operator while maintain

agentsarxiv-cs-ro

Aligning with Lived Experience: Heterogeneous Benefits of Fine Tuning in Mental Health Support Generation

arXiv:2609.21075v1 Announce Type: cross Abstract: As access to professional mental healthcare remains limited, many individuals turn to online platforms such as Reddit to seek peer support situated wi

safetyarxiv-cs-ai

ALINA: Advanced Line Identification and Notation Algorithm

arXiv:2406.08775v2 Announce Type: replace Abstract: Labels are the cornerstone of supervised machine learning algorithms. Most visual recognition methods are fully supervised, using bounding boxes or

An Introduction to Compression-Based Machine Learning

arXiv:2609.21309v1 Announce Type: new Abstract: Any lossless compression algorithm (like gzip) may be converted into a machine learning method, via either Normalized Compression Distance or the Minimu

researcharxiv-cs-lg

ArenaFlow: From Trajectory Ranking to Hierarchical Credit Propagation for Open-Ended Agent RL

arXiv:2609.21378v1 Announce Type: new Abstract: Reinforcement learning has substantially improved large language model (LLM) agents in verifiable domains, but remains difficult to apply to open-ended

safetyarxiv-cs-cl

Auditing a KB Elicitation of Frontier LLM Knowledge: A Multi-dimensional Analysis of GPTKB v1.5

arXiv:2510.07024v3 Announce Type: replace-cross Abstract: LLMs are remarkable artifacts that have revolutionized a range of knowledge-intensive tasks. A significant contributor is their factual knowle

Tutorials

AutoViewMem: Self-Configuring Orthogonal Views for Conversational Long-Term Memory

arXiv:2609.21940v1 Announce Type: new Abstract: Long-term memory is essential for large language model (LLM) agents to maintain consistency and personalization over extended interactions. Existing mem

tutorialsarxiv-cs-ai

Backup-Based Safety Filters: A Comparative Review of Backup CBF, Model Predictive Shielding, and gatekeeper

arXiv:2604.02401v2 Announce Type: replace Abstract: This paper revisits three backup-based safety filters -- Backup Control Barrier Functions (Backup CBF), Model Predictive Shielding (MPS), and gateke

BEAT-Net: Injecting Biomimetic Spatio-Temporal Priors for Interpretable ECG Diagnosis

arXiv:2601.07316v2 Announce Type: replace-cross Abstract: Automated electrocardiogram diagnosis using deep learning remains limited by signal-agnostic representations that treat multi-lead recordings

Beyond Reference-Based Evaluation: Reward Models for Meta-Evaluation of Grammatical Error Correction

arXiv:2609.21231v1 Announce Type: new Abstract: Reference-based metrics for Grammatical Error Correction (GEC) such as M^2 and ERRANT assume that the reference set enumerates all valid edits, and ther

researcharxiv-cs-cl

BI-Agent and BI-Bench: Towards Automating End-to-End Business Intelligence

arXiv:2609.20886v1 Announce Type: cross Abstract: Business intelligence (BI) is a cornerstone of enterprise decision-making and is widely used by enterprise users in software such as Power BI and Tabl

Hardware

Bio-MF: Low-Latency and High-Fidelity EEG-to-fNIRS Cross-Modal Generation for Hybrid Motor-Imagery Brain--Computer Interfaces

arXiv:2609.20904v1 Announce Type: cross Abstract: Hybrid motor-imagery brain-computer interfaces (MI-BCIs) combining EEG and fNIRS can outperform EEG-only systems by exploiting complementary electroph

hardwarearxiv-cs-ai

BrainWideBench: Benchmarking large-scale pretraining and across-animal transfer in multi-region neural recordings

model-releasesarxiv-cs-lg

arXiv:2609.22064v1 Announce Type: new Abstract: Advances in large-scale neural recording have made it possible to collect data across many animals and distributed brain regions, raising the question o

Local Ai

CaLR: Causal Latent Revision for Robust Diffusion Reasoning

arXiv:2609.20981v1 Announce Type: new Abstract: Autoregressive (AR) models suffer from local greediness, while diffusion language models (DLMs) often lack the strict causal structure required for reas

local-aiarxiv-cs-ai

CARF: Contrastive Attraction-Repulsion of Failure-Guided Flow Matching

arXiv:2609.21982v1 Announce Type: new Abstract: Robot demonstration collection often produces imperfect or failed trajectories in addition to successful demonstrations. Existing methods typically expl

CASCADE Against Jailbreaks: Combination Across Stages with Controlled Attack-Defense Evaluation

arXiv:2609.21793v1 Announce Type: cross Abstract: Defenses against jailbreak attacks on Large Language Models (LLMs) operate at different pipeline stages, such as input modification or output guard, b

safetyarxiv-cs-cl

Applications

COAL-SQL: Coverage-Guided Augmentation and Failure-Driven Learning for Text-to-SQL Post-Training

arXiv:2609.20842v1 Announce Type: new Abstract: Text-to-SQL translates natural-language questions into executable SQL queries, but open-source large language models still require task-specific post-tr

applicationsarxiv-cs-cl

CommitFlow: Semantic Commitment Verification and Local Correction for Long-Horizon Robot Manipulation VLA Execution

arXiv:2609.21908v1 Announce Type: new Abstract: Although vision-language-action (VLA) policies have advanced rapidly, long-horizon execution may still progress to the next task stage before the requir

Applications

CompAdapt: Adaptable Composite Motion Modeling for Physics-Consistent Text-to-Video Generation

arXiv:2609.21455v1 Announce Type: new Abstract: While diffusion-based text-to-video (T2V) models have demonstrated impressive capability in generating realistic and temporally coherent videos, they of

applicationsarxiv-cs-cv

Applications

Continuous Spiking Graph Neural Networks

arXiv:2404.01897v3 Announce Type: replace-cross Abstract: Continuous graph neural networks (CGNNs) have garnered significant attention due to their ability to generalize existing discrete graph neural

applicationsarxiv-cs-ai

Cube-Splat: High-Fidelity 360{eg} Gaussian Splatting SLAM via Cubemap Factorization and Adjoint-Consistent Optimization

arXiv:2609.21347v1 Announce Type: new Abstract: Recent progress in 3D Gaussian Splatting (3DGS) has enabled dense visual SLAM with pinhole cameras, yet most pipelines are not designed for panoramic im

Deep Reinforcement Learning with Buffered Quantile Objectives

arXiv:2609.21327v1 Announce Type: cross Abstract: Quantile-based reinforcement learning provides an interpretable approach to risk-sensitive decision-making by optimizing a prescribed quantile of the

safetyarxiv-cs-ai

Design of Adaptive PID Controller Based On Asynchronous Advantage Actor Critic Learning Method for QuadCopter Control

arXiv:2609.21082v1 Announce Type: new Abstract: Quadcopters offer great utility in many applications, but their nonlinear nature and disturbance sensitivity present great control challenges. Basic PID

Designer-RSI: Evolving Procedural Memory from User Traffic for Agentic Graphic Design

arXiv:2609.22086v1 Announce Type: new Abstract: Professional graphic design is a long-horizon agentic task in which structured, editable artifacts emerge from many interdependent actions, yet outcomes

DEXTERA: From a Single Image to Deployable Dexterous Manipulation via Real-to-Sim-to-Real

arXiv:2609.21045v1 Announce Type: new Abstract: Collecting real-world robot data for dexterous manipulation is costly and time-consuming. While high-fidelity physics simulators enable scalable data sy

Diagonalized Attention for Individualized Regression: Latent-Row Localization and Prediction

model-releasesarxiv-cs-lg

arXiv:2609.21320v1 Announce Type: cross Abstract: Modern text and image representations are often matrix-valued, with rows corresponding to tokens, patches, or other local feature vectors. Predictive

DiaVLo: Diagnosing Behaviours of Vision-Language Models

arXiv:2609.22008v1 Announce Type: cross Abstract: Vision-language models (VLMs) rely on storing and transferring appropriate information across their sub-components. Verifying that the VLMs exhibit de

researcharxiv-cs-ai

Diffusion-Based Tumor Inpainting for Renal Segmentation under Clinical Data Scarcity

arXiv:2609.21698v1 Announce Type: new Abstract: Deep learning segmentation of renal tumors requires large annotated datasets, yet clinical deployments typically offer only a handful of tumor-positive

DRT: Dense Reasoning Trace for Efficient and Grounded Multimodal Reasoning

arXiv:2609.21675v1 Announce Type: new Abstract: Despite the remarkable progress in Multimodal Large Language Models (MLLMs), prevailing Chain-of-Thought (CoT) paradigms remain confined to the natural-

Duty Factor Predicts Robust Constrained Quadrupedal Locomotion Across Gait Types

arXiv:2609.22073v1 Announce Type: new Abstract: Quadrupedal robots are increasingly deployed in environments where locomotion must remain robust to disturbances and constrained terrain. Gait type, suc