Search: “context”

Digital Twin for Pre-Deployment Validation of AI-Driven Safety-Critical Industrial Edge Control Loops

arXiv:2610.11934v1 Announce Type: cross Abstract: Industrial environments are increasingly characterized by the tight interaction among physical processes, communication infrastructures, and intellige

safetyarxiv-cs-ro

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Safety

Distilling Routed 3D Privilege for Spatial Reasoning in Vision-Language Models

DGX agent

arXiv:2610.12355v1 Announce Type: cross Abstract: Spatial reasoning remains a persistent weakness of vision-language models (VLMs), because RGB inputs do not directly provide geometric evidence. Exist

safetyarxiv-cs-ai

9 Oct 2026

DORS: Dynamic Attention Routing for Diffusion-based Object Removal in Dense Scenes

model-releasesarxiv-cs-cv

arXiv:2607.16656v2 Announce Type: replace Abstract: Object removal aims to eliminate target objects specified by a mask while preserving visual consistency with the surrounding regions. Existing metho

DVLA-RL++: Dual-Level Vision-Language Alignment with Reinforcement Learning Gating for Few-Shot Learning

arXiv:2610.12095v1 Announce Type: new Abstract: Few-shot learning aims to recognize novel categories from limited labeled examples. Recent studies incorporate textual semantics to compensate for limit

safetyarxiv-cs-cv

Easy to anticipate, hard to compute: boundary dependence finds the computed outputs that entropy patching misses

arXiv:2610.11790v1 Announce Type: new Abstract: Byte-level language models such as the Byte Latent Transformer (BLT) group bytes into patches and run their large global model once per patch. BLT start

researcharxiv-cs-cl

Environmental Feedback Modeling Matters: Rethinking Feedback Treatment in Agentic Hindsight Self-Distillation

arXiv:2610.11384v1 Announce Type: new Abstract: Reinforcement learning is commonly used to train language agents in interactive environments, but cannot be directly applied when rewards are unavailabl

Local Ai

Event-Centric Memory with Query-Aware Graph Augmentation for Long-Term Conversational Agents

arXiv:2610.11920v1 Announce Type: new Abstract: For persistent and personalized conversational agents, memory systems can enable them to remember, update, and reason over long histories by storing pas

local-aiarxiv-cs-cl

Tutorials

Evi-VN: Hard Region Guided Virtual Node Evidence Injection for GNN-Based Fraud Detection

arXiv:2610.11665v1 Announce Type: new Abstract: Online platforms contain growing numbers of bots, deceptive reviewers, and scam accounts that imitate legitimate users. Such camouflage blurs graph neig

tutorialsarxiv-cs-lg

FastBench: Can Streaming VLMs Perceive High-Dynamic Real-World Streams?

arXiv:2610.12427v1 Announce Type: cross Abstract: Streaming Video Large Language Models (VLMs) enable continuous video understanding, yet existing benchmarks focus on low-dynamic scenarios. Under boun

FreshMem: Brain-Inspired Frequency-Space Hybrid Memory for Streaming Video Understanding

arXiv:2602.01683v2 Announce Type: replace-cross Abstract: Transitioning Multimodal Large Language Models (MLLMs) from offline to online streaming video understanding is essential for continuous percep

researcharxiv-cs-ai

From Retrieval to Reconstruction: Constructing Evolvable Cognitive Memory for Long-Term Dialogue

arXiv:2610.11314v1 Announce Type: new Abstract: Large Language Models (LLMs) serving as long-term dialogue agents require memory systems that support reliable reasoning over extended interactions. How

agentsarxiv-cs-cl

From What to Which: Decoding Modifier Grounding in Frozen MLLMs

arXiv:2610.12305v1 Announce Type: new Abstract: As Multimodal Large Language Models (MLLMs) can describe increasingly complex visual scenes, token-level grounding becomes crucial. Yet, when an MLLM ge

GameCommBench: A Unified Benchmark and Type-Aware Evaluation for AI-Generated Game Commentary

arXiv:2610.11129v1 Announce Type: new Abstract: Game commentary is an open-ended generation task requiring multimodal perception, strategic reasoning, and contextual knowledge. Existing AI-Generated G

Hardware

GATOR: Generative and Agentic 3D Object Reconstruction From Casual Images

arXiv:2610.11215v1 Announce Type: new Abstract: Reconstructing complete, scene-aligned 3D objects from casual images requires integrating sparse, uncertain observations and inferring surfaces hidden b

hardwarearxiv-cs-cv

GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness

arXiv:2510.00536v2 Announce Type: replace Abstract: Graphical user interface (GUI) agents built on vision-language models have emerged as a promising approach to automate human-computer workflows. How

iAm.md: Robot Skill Self-Assessment through Agentic Introspection for Unknown Open-Vocabulary Domains

arXiv:2610.10962v1 Announce Type: cross Abstract: Agentic AI based on Large Language Model generalization capabilities offers a wide range of potential applications, including planning for embodied ta

Just Weather Scoring: Efficient End-to-end Nowcasting with Distributional Diffusion

arXiv:2610.12189v1 Announce Type: cross Abstract: Generative diffusion models are well-suited for probabilistic precipitation nowcasting, but existing approaches often rely on separately trained compr

Local Ai

Large Language Model-Assisted Preparation of Transportation Management Plans: A Case Study with WisDOT WisTMP System

arXiv:2610.10650v1 Announce Type: new Abstract: Work zones are critical yet hazardous components of transportation infrastructure, requiring carefully designed Transportation Management Plans (TMPs) t

local-aiarxiv-cs-cl

Large Language Models for Machine Translation Quality Annotation: Humans and Models Are Both Challenged

arXiv:2610.10918v1 Announce Type: new Abstract: Large Language Models (LLMs) are considered to be a more efficient and cost-effective alternative to human judgment for Machine Translation (MT) evaluat

researcharxiv-cs-cl

Applications

Learned Image Compression for Vision-Language-Action Models

arXiv:2606.16253v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models increasingly rely on high-frequency multi-camera observations, making visual communication a major bottlen

applicationsarxiv-cs-ai

LR-V2X: Loss-Resilient Collaborative Perception under Low-Bandwidth Communication

model-releasesarxiv-cs-cv

arXiv:2610.11264v1 Announce Type: new Abstract: Given the inherent unpredictability of packet loss in vehicular wireless communications, V2X collaborative perception can yield practical benefits only

Marformer: A Transformer for Predicting Missing Data Distributions

arXiv:2610.12379v1 Announce Type: new Abstract: Real decisions are made under incomplete information. If we observe only some of the random variables we need, we can predict the others. The extbf{cond

researcharxiv-cs-lg

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL

arXiv:2607.16204v2 Announce Type: replace Abstract: Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environments. Hand-curated environments with fixe

MATE4D: Matrix-Guided Editable 4D Generation from a Single Image

arXiv:2610.11181v1 Announce Type: new Abstract: Generative models have rapidly pushed content creation be-yond 2D imagery toward dynamic 3D and 4D scene synthesis. Yet pro-ducing realistic and tempora

MiMo-V2.6: Scaling Reinforcement Learning Towards Self-Improvement

arXiv:2610.11959v1 Announce Type: new Abstract: Reinforcement learning (RL) is the central training paradigm for advancing large foundation models towards self-improvement. This report introduces the

agentsarxiv-cs-cl

Mooncake: A KVCache-centric Disaggregated Architecture for LLM Serving

arXiv:2407.00079v5 Announce Type: replace-cross Abstract: Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI. It features a KVCache-centric disaggregated architec

MotherTree: Meta-learning on synthetic data improves decision tree training

arXiv:2610.10832v1 Announce Type: new Abstract: Conventional decision tree algorithms produce effective, transparent models that can be audited, communicated, and deployed independently of the trainin

researcharxiv-cs-lg

OpenProblemBench: Benchmarking AI on Open Problems in the Foundational Theoretical Sciences

arXiv:2610.11118v1 Announce Type: new Abstract: The next frontier for artificial general intelligence is tackling unresolved scientific problems, calling for benchmarks that assess progress beyond est

Hardware

PageWeaver: KV-Guided Query Unions for Sparse Attention

arXiv:2610.11201v1 Announce Type: cross Abstract: Dynamic sparse attention limits the KV pages selected by each query, but a small support does not necessarily yield efficient GPU work. Query unions s

hardwarearxiv-cs-lg

PIER: An Evidence-Gated Execution Interface for Robotic Manipulation

arXiv:2610.12123v1 Announce Type: new Abstract: Generating a plausible robot action does not establish that current observations justify its execution. Motivated by exploratory observations of high-co

safetyarxiv-cs-ro

PlanWAM: Planning-Shaped Future Representations for End-to-End Autonomous Driving

arXiv:2610.11382v1 Announce Type: cross Abstract: World models in end-to-end autonomous driving predict future scene evolution to provide foresight for trajectory planning. Existing methods mainly stu

agentsarxiv-cs-lg

Pose-Free Feed-Forward 3D Inpainting via Learnable Mask Attention and Support Token Refinement

arXiv:2610.11857v1 Announce Type: new Abstract: 3D scene inpainting aims to recover missing or occluded regions in edited 3D scenes, while ensuring geometric and textural consistency. Existing approac

REACT: Rolling Denoising and Dual Decoupling for Reactive Robot Control with VLA Models

arXiv:2610.12007v1 Announce Type: cross Abstract: Flow-based vision-language-action (VLA) models generate action chunks for temporally coherent robot motion, but chunked control creates a fundamental

Recurrent Self-Improvement: Dynamic Cross-Loop On-Policy Distillation for Looped Language Models

arXiv:2610.10623v1 Announce Type: cross Abstract: Looped Language Models (LoopLMs) offer a parameter efficient approach to scaling reasoning by reusing shared parameters across recurrent computation s

Revisiting Identity and Spectra Dispersion in Media-Bridged Time Series Forecasting: Linking Multivariate Signals and Narrative Flows

arXiv:2610.11924v1 Announce Type: new Abstract: Media-bridged time series forecasting is expanding to encompass traditional 'multivariate' and emerging 'multimodal' (e.g., through textual assistance).

safetyarxiv-cs-cv

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

model-releasesarxiv-cs-lg

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

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

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

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

Local 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

SignRAG: Unified Retrieval-Augmented Gloss-Free Sign Language Translation

arXiv:2610.11371v1 Announce Type: new Abstract: Contemporary decoder-only large language models (LLMs) have demonstrated strong capabilities across a wide range of domains. However, existing pretraini

Simultaneous Computation with Multiple Prioritizations in Multi-Agent Motion Planning

arXiv:2501.10781v2 Announce Type: replace-cross Abstract: Multi-agent path finding (MAPF) in large networks is computationally challenging. An approach for MAPF is prioritized planning (PP), in which

Skill-SLM: Agent Skill-driven Small Language Models for Reliable Robot Operation

arXiv:2610.10812v1 Announce Type: new Abstract: Small language models (SLMs) have been increasingly adopted for onboard robot operation because they enable intelligent decision-making. However, existi

agentsarxiv-cs-ro

Tutorials

Softmax Attention on Gaussian Mixtures: Linear When It Can, Selective When It Must

arXiv:2610.11798v1 Announce Type: cross Abstract: Softmax attention, at the heart of Transformers, has demonstrated remarkable capabilities. Yet its underlying mechanisms remain only partially underst

tutorialsarxiv-cs-lg

SuperNav: An Agentic Navigation System for Any Task in Any Scene

arXiv:2610.12126v1 Announce Type: cross Abstract: General-purpose service robots need navigation systems that can handle diverse human requests in unfamiliar environments, combining task generality wi

agentsarxiv-cs-cv

TaReD: Tool-Aware Recursive Decomposition for Long-Horizon Tasks

arXiv:2610.11268v1 Announce Type: new Abstract: Agents combine reasoning with tools to interact with external systems and complete real-world tasks. Early agents typically interleave reasoning and act

Applications

Timer-M1: A Multivariate Time Series Foundation Model via Learning Primitives

arXiv:2610.11734v1 Announce Type: cross Abstract: We introduce Timer-M1, a pretrained multivariate time series foundation model that learns with primitives for zero-shot forecasting. Across domains, t

applicationsarxiv-cs-ai

VAMR: Multi-Question Agentic Reasoning for Efficient Long-Form Video Understanding

arXiv:2610.11171v1 Announce Type: cross Abstract: Long-form video understanding often involves multiple questions about different aspects of the same recording. Yet existing video agents typically pro