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RideBench: A Large-Scale Exogenous-Aware Benchmark for Ride-Hailing Time Series Forecasting

arXiv:2610.11164v1 Announce Type: new Abstract: We release Ride-Hailing, a large-scale ride-hailing time series dataset synthesized from DiDi's marketplace data across 200 spatial areas. Ride-Hailing

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RIFT: Relative Isolation From Trees For Anomaly Detection

DGX agent

arXiv:2610.12244v1 Announce Type: new Abstract: Isolation Forest (IF) is a widely used baseline for unsupervised anomaly detection. Recent studies provide a closed-form expression for the infinite-for

model-releasesarxiv-cs-lg

9 Oct 2026

Right Screen, Wrong Transition: World Models as Verifiers for GUI Agents

arXiv:2610.11942v1 Announce Type: new Abstract: A login screen that appears after a tap on Sign in is expected; the same screen after a tap on View order is an attack. For GUI agents, safety is theref

safetyarxiv-cs-cv

RISR: Residual-Informed Scientific Equation Discovery with Large Language Models

arXiv:2610.11387v1 Announce Type: cross Abstract: Symbolic regression combines structural search with numerical fitting, but aggregate fit scores do not describe how the remaining error varies across

tutorialsarxiv-cs-ai

RIT-RAG: Navigating Document Corpora with Retrieval-Induced Trees

arXiv:2610.11370v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) grounds language models in external corpora. Agentic RAG enables iterative search, yet exposes the model to isolate

RL-ARC: Calibrating Large Reasoning Models via Reasoning-guided Uncertainty

arXiv:2610.11352v1 Announce Type: new Abstract: Language models (LMs) are commonly trained with Reinforcement Learning with Verifiable Rewards (RLVR) to enhance their reasoning capabilities. However,

researcharxiv-cs-ai

RoboAug: One Annotation to Hundreds of Scenes via Region-Contrastive Data Augmentation for Robotic Manipulation

arXiv:2602.14032v2 Announce Type: replace Abstract: Enhancing the generalization of robotic learning in diverse unseen environments remains a fundamental challenge. Existing approaches often rely on l

tutorialsarxiv-cs-ro

RoboAware: Learning to Coordinate Embodied Skills from Counterfactual Outcomes

arXiv:2610.11480v1 Announce Type: cross Abstract: Embodied coding agents can combine modular robot skills with frozen end-to-end policies, yet effective composition requires anticipating which policy

safetyarxiv-cs-ai

RoboRSI: Stable, efficient, and reusable robot self-evolution in complex real-world environments

arXiv:2610.12424v1 Announce Type: cross Abstract: A generalist robot should not only perform diverse tasks but also improve through experience, turning what it learns during execution into capabilitie

applicationsarxiv-cs-ai

RobustLDS: Learning linear dynamical systems under adversarial corruptions

arXiv:2610.11906v1 Announce Type: cross Abstract: We consider the problem of learning linear dynamical systems under adversarial contamination from a single trajectory of length T. While identificatio

Rounding in Preconditioner Space: Redesigning 4-bit AdamW Optimizer-State Quantization

arXiv:2610.12444v1 Announce Type: new Abstract: Quantizing AdamW's optimizer states reduces persistent storage, but quantization errors propagate through the moment recurrences and perturb subsequent

RouterInterp: Understanding Superposed Specialisation in Mixture of Experts Routing

arXiv:2610.11775v1 Announce Type: new Abstract: Sparse Mixture of Experts (MoE) models scale more efficiently than dense models by routing tokens to modular expert networks that are only active for pr

researcharxiv-cs-ai

RT-DETRv4: Painlessly Furthering Real-Time Object Detection with Vision Foundation Models

model-releasesarxiv-cs-cv

arXiv:2510.25257v2 Announce Type: replace Abstract: Real-time object detection has achieved substantial progress through meticulously designed architectures and optimization strategies. However, the p

Rubric-CEPR: Self-Evolving Image Editing via Reward-Verified Self-Distillation

model-releasesarxiv-cs-cv

arXiv:2610.12469v1 Announce Type: new Abstract: Instruction-guided image editors have become highly capable, yet improving them further still depends on human-edited training pairs or external reward

Agents

Runnable Commit Untangling for Coding Agents

arXiv:2610.11593v1 Announce Type: cross Abstract: Coding agents produce large, tangled patches that mix multiple development purposes, making the code hard to review and maintain. Commit untangling of

agentsarxiv-cs-ai

S^3Geo: Structure-Semantic Synergistic Learning for Cross-View Geo-Localization

arXiv:2610.11608v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL) aims to estimate geographic locations by matching images captured from different viewpoints, such as drone and satell

local-aiarxiv-cs-cv

S4oP: Operator-level Pruning of Structured State Space Models for Resource-Constrained Devices

arXiv:2606.18096v2 Announce Type: replace-cross Abstract: Structured State Space Models (SSMs), including the S4 and S4D architectures, have recently emerged as powerful alternatives to attention-base

SACQ: Structured Decoding with Memory-Conditioned Refinement for Long-Horizon Forecasting

arXiv:2610.11170v1 Announce Type: new Abstract: Long-term time series forecasting (LTSF) models predominantly employ patch-based encoders terminated by a flatten readout head that maps the entire enco

safetyarxiv-cs-lg

Safe Actions Alone Do Not Ensure Safe Agents: Identifying Unfulfilled Obligations with Guard Models

arXiv:2610.11773v1 Announce Type: new Abstract: Guard models are increasingly used to safeguard LLM-based agents, primarily by identifying actions that agents are forbidden to perform. However, identi

Safe at One Loop, Risky at Another: Aligning Safety Across Recurrent Depths in Looped Language Models

arXiv:2610.10625v1 Announce Type: cross Abstract: Looped Language Models (LoopLMs) provide a parameter efficient approach to scaling model capabilities through repeated use of shared parameters across

Safe, Persistent, and Evolving Agent Harness for Understanding Partially Observable Worlds

arXiv:2610.11552v1 Announce Type: new Abstract: Large language model agents can invoke tools fluently, but enterprise workflows demand more than selecting the right tools: actions must strictly comply

SafeInferCom: Safe Inference-Time Compute via Verifier-Guided Mid-Generation Intervention for Robotic Task Planning

arXiv:2610.11223v1 Announce Type: cross Abstract: Large Reasoning Language Models (LRLMs) enable multi-step reasoning for robotic task planning, but continued reasoning can overwrite valid intermediat

applicationsarxiv-cs-ai

SAGE: Sink-Aware Guided Emphasis for Visual Grounding in Vision-Language Decoders

arXiv:2610.11469v1 Announce Type: cross Abstract: Recent large vision-language models (VLMs) pair a visual encoder with a large language model (LLM) and perform well on diverse image-text tasks, yet t

safetyarxiv-cs-cl

SAIL: Scientific Agentic Intelligence via a Science-Aware Loop

arXiv:2610.11451v1 Announce Type: new Abstract: We introduce SAIL, an open model with 35B total and 3B active parameters for literature research, scientific coding, and multi-step research workflows.

safetyarxiv-cs-cl

Same Action, Different Outcome: Variability in Dynamic Cloth Manipulation

arXiv:2610.10801v1 Announce Type: new Abstract: Although cloth is known to exhibit different outcomes under repeated fast dynamic motions, even when the same trajectory is applied, this variability ha

applicationsarxiv-cs-ro

Same Outcome, Different Evidence: Intent Recovery in LLM Safety Evaluation

arXiv:2610.11766v1 Announce Type: cross Abstract: Safety evaluations of large language models commonly summarize harmful-output behavior with attack success rate (ASR). Yet the same non-harmful outcom

safetyarxiv-cs-ai

Sample-Efficiency of Kolmogorov-Arnold Networks

arXiv:2610.10627v1 Announce Type: new Abstract: Deep reinforcement learning has achieved substantial performance gains over classical control approaches. Yet, a central challenge to learning in real-w

Sample-Efficient Generative Conformal Prediction

arXiv:2610.11349v1 Announce Type: new Abstract: Generative conformal prediction builds uncertainty sets from samples of a conditional generator, which are efficient only when the samples represent the

SatFix: Absolute Visual Localization of UAVs in Satellite Maps from a Single Oblique Image

arXiv:2610.11049v1 Announce Type: new Abstract: We study absolute metric UAV localization within a provided geo-referenced satellite region, recovering continuous map position and viewing heading from

local-aiarxiv-cs-cv

SAVU-BENCH: A Real-World Benchmark for Spatial Audio-Visual Understanding

arXiv:2610.10624v1 Announce Type: cross Abstract: Spatial audio-visual understanding requires models to recognize not only what is present, but also where events occur and how they relate across modal

Scalable AI Uncertainty Quantification via Generalized Laplace Active Subspaces

arXiv:2610.11738v1 Announce Type: new Abstract: Reliable uncertainty quantification (UQ) is essential for deploying neural networks in scientific and high-stakes applications, but full Bayesian infere

local-aiarxiv-cs-ai

Scalable Hierarchical Graph Generation via Soft Community Structure

arXiv:2610.12163v1 Announce Type: cross Abstract: Generating large attributed graphs requires reproducing the topology, generating attributes jointly with the structure, and remaining scalable. Many r

local-aiarxiv-cs-ai

Scalable LEO Conjunction Screening using Adaptive Synthetic-Covariance Thresholds

arXiv:2610.11645v1 Announce Type: new Abstract: As orbital populations grow, conjunction screening must search more object pairs for potential collision risks. Existing pipelines use early-stage filte

researcharxiv-cs-ro

Scaling to Tens of Thousands of Test-Time Iterations with Loop-Native Attention Residuals

arXiv:2610.11570v1 Announce Type: new Abstract: In this paper, we argue that looped Transformers need their own residual connections to prevent performance degradation as the number of iterations grow

Agents

Scaling Verifiable Environments for Long-horizon Work Agents

arXiv:2610.04906v2 Announce Type: replace-cross Abstract: Work agents operate over digital artifacts to execute professional knowledge-intensive work, requiring training environments that support long

agentsarxiv-cs-ai

SciTBERT: A family of chronologically consistent language models for scientific and technological language processing

model-releasesarxiv-cs-cl

arXiv:2610.12207v1 Announce Type: new Abstract: Pre-trained transformer models are increasingly being used to study scientific and technological progress. Encoders tuned to paper or patent text outper

Score-Based Learning of Cluster DAGs from Interventions

arXiv:2610.11947v1 Announce Type: cross Abstract: Graphical approaches to causal abstraction transform a low-level causal directed acyclic graph (DAG) over many measured variables into a smaller, high

tutorialsarxiv-cs-lg

SCORE: Spectral Correlation Estimation for Multivariate Gaussians

arXiv:2610.12096v1 Announce Type: new Abstract: Neural network-based predictive modeling with high-dimensional structured Gaussian targets requires an efficient and numerically stable, yet expressive

SDPAD: A Fully Spike-Driven Pipeline for End-to-End Autonomous Driving

arXiv:2610.11583v1 Announce Type: cross Abstract: End-to-end autonomous driving demands trajectory planners that are both highly accurate and cheap enough for edge deployment. State-of-the-art artific

Searching for 'Harmful Refusal': A Psychometric Audit of an AI Safety Benchmark

arXiv:2610.12409v1 Announce Type: new Abstract: Safety benchmarks typically report one overall score for a suite of datasets, each of which may target one or more safety-related attributes, so models

Seed2Scale: A Self-Evolving Data Engine with Parallel Worlds Expansion for Scalable Robot Learning

arXiv:2603.08260v2 Announce Type: replace Abstract: Existing data generation methods for robot learning suffer from limited exploration, embodiment gaps, low signal-to-noise ratios, and domain shifts,

applicationsarxiv-cs-ro

Seeing Through the Glare: A Multi-Source Benchmark and Ocular-Adaptive Pixel MeanFlow for Eyeglass Reflection Removal

model-releasesarxiv-cs-cv

arXiv:2610.10703v1 Announce Type: new Abstract: Eyeglass reflection removal is important across smartphone imaging, video conferencing, and other face-centric visual applications. The task is challeng

Seek-and-View Reasoning for Multi-View Spatial Understanding

arXiv:2610.11810v1 Announce Type: new Abstract: Existing approaches to multi-view spatial reasoning operate largely on sparse input views. Vision-language models (VLMs) are thus restricted to understa

safetyarxiv-cs-cv

Selective Listening: Mechanism-Guided Control of Audio Influence in Large Audio-Language Models

arXiv:2610.11196v1 Announce Type: cross Abstract: Large audio-language models (LALMs) exploit multimodal evidence, yet task-irrelevant audio can alter text-reasoning decisions when listening is unnece

researcharxiv-cs-cl

Self-Organization from Constrained Geometric Radiation

arXiv:2610.10621v1 Announce Type: new Abstract: How does dynamic order emerge spontaneously in closed systems without external driving? Existing paradigms all require external energy flows, temperatur

Self-sufficient Independent Component Analysis for Demixing Flows

arXiv:2512.00665v2 Announce Type: replace-cross Abstract: We study the problem of learning disentangled signals from data using non-linear Independent Component Analysis (ICA). Motivated by advances i

tutorialsarxiv-cs-lg

Self-Supervised Keyframe Discovery for Horizon-Invariant Behavior Cloning

arXiv:2610.10857v1 Announce Type: new Abstract: Behavior cloning (BC) in non-Markovian environments is a challenging problem because policies have to reason over contextual information over long horiz

Self-Supervised Speech Representations for Cross-Speaker Dysarthria Detection During Awake Craniotomy

arXiv:2610.11825v1 Announce Type: new Abstract: Detecting intra-operative speech impairment during awake craniotomy is essential for preserving language function. However, automated detection remains