Search: “deployment”

Social-WM: Safety-Aware Latent World Models for Robot Social Navigation

arXiv:2609.40177v1 Announce Type: new Abstract: Safe social navigation requires a robot to anticipate not only the future consequences of its actions, but also whether a nominal action can actually be

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SOLAR: SVD-Optimized Lifelong Attention for Recommendation

DGX agent

arXiv:2603.02561v2 Announce Type: replace-cross Abstract: Attention mechanism remains the defining operator in Transformers since it provides expressive global credit assignment, yet its quadratic cos

applicationsarxiv-cs-cv

1 Oct 2026

Hardware

SparLeak: Privacy Leakage from Sparse Attention in LLM Inference on Shared GPUs

arXiv:2609.38830v1 Announce Type: new Abstract: Sparse attention is widely used to accelerate long-context inference in modern large language models (LLMs), but its input-dependent execution behavior

hardwarearxiv-cs-lg

Spherical Interpolation for Backward-Compatible Multimodal Representations

arXiv:2609.39836v1 Announce Type: new Abstract: Contrastive vision-language models map visual and textual representations into a shared normalized embedding space, making cosine similarity the natural

local-aiarxiv-cs-cv

Research

Spike-driven Vision-Language-Action Model

arXiv:2609.39514v1 Announce Type: new Abstract: Vision-language-action (VLA) models bridge multimodal understanding and robotic control, advancing the dominant paradigm for embodied intelligence. Howe

researcharxiv-cs-cl

SplineWAM: Adaptive Action Horizons for World Action Models via B-Spline Representations

model-releasesarxiv-cs-ro

arXiv:2609.39873v1 Announce Type: new Abstract: World action models (WAMs) are large embodied policies that jointly predict future video and the actions to execute, emitting a fixed-length action chun

SteerQuant: Steering Quantization Error with Action-Guided Scaling in World-Action Models

model-releasesarxiv-cs-ro

arXiv:2609.39056v1 Announce Type: new Abstract: World-action models (WAMs) jointly generate future world states and actions through iterative denoising, using shared weights to process heterogeneous s

Towards More Efficient, Robust, Instance-adaptive, and Generalizable Sequential Decision making

arXiv:2504.09192v5 Announce Type: replace Abstract: The primary goal of my Ph.D. study is to develop provably efficient and practical algorithms for data-driven sequential decision-making under uncert

applicationsarxiv-cs-lg

TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements

arXiv:2609.32923v2 Announce Type: replace Abstract: Wireless digital twins (DTs) rely on 3D environment models to predict radio propagation and support wireless-network decisions, yet these models are

TrafficSignBench: Rule-Centric Closed-Loop Evaluation of Traffic-Sign Compliance in Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2609.38463v1 Announce Type: cross Abstract: Autonomous driving planners are typically evaluated using aggregate metrics such as driving score, destination rate, and collision rate, which do not

Trust Is Not a Score: Runtime Assurance Contracts for High-Risk AI Agents

arXiv:2609.39717v1 Announce Type: new Abstract: Benchmarks, audits, and agent protocols describe performance, permissions, and repair, but not how observed evidence should change an agent's authority

Turbo Harness: Instance-Adaptive Harness Optimization

arXiv:2609.40330v1 Announce Type: new Abstract: Automating the search for effective harnesses is an important step toward enabling agents to recursively self-improve. Existing harness optimizations ty

UniST-Pred: A Robust Unified Framework for Spatio-Temporal Traffic Forecasting in Transportation Networks Under Disruptions

arXiv:2602.14049v2 Announce Type: replace-cross Abstract: Spatio-temporal traffic forecasting is a core component of intelligent transportation systems, supporting various downstream tasks such as sig

What Can Component-Replacement Evidence Establish? A Critical Scoping Review of Local Decisions in LLM Agents

arXiv:2609.39989v1 Announce Type: new Abstract: Background. A component replacement in a language-model agent changes an execution trajectory, potentially altering later observations, resource use, an

local-aiarxiv-cs-ai

Where the Evidence Lives: Auditing AI Companions' Self-Descriptions

arXiv:2609.38753v1 Announce Type: cross Abstract: Companion agents describe themselves: they remember, they understand their users, the relationship has changed them. We argue that such accounts, and

A Comprehensive View of Fairness through Distributional Stability

arXiv:2609.37061v1 Announce Type: cross Abstract: We view fairness as a property of distributional stability. Rather than assessing a predictor under a fixed data distribution, we study how its predic

A Dual-Track Curation-and-Classification Framework for Resolving Ground-Truth Label Noise in Operational Sentinel-2 Wheat Area Estimation

model-releasesarxiv-cs-cv

arXiv:2609.36975v1 Announce Type: new Abstract: Operational estimation of wheat-cultivated area is persistently constrained by discordance between administrative record-keeping and remotely sensed cla

ActiveSAM: Fast and Accurate Open-Vocabulary Semantic Segmentation with Frozen SAM 3

arXiv:2606.16996v2 Announce Type: replace-cross Abstract: Segment Anything Model 3 (SAM 3) provides a strong frozen backbone for concept-prompted segmentation, but applying it directly to open-vocabul

Adversarial Defense in Cybersecurity: A Systematic Review of GANs for Threat Detection and Mitigation

arXiv:2509.20411v3 Announce Type: replace-cross Abstract: Machine learning-based cybersecurity systems are highly vulnerable to adversarial attacks, while Generative Adversarial Networks (GANs) act as

applicationsarxiv-cs-ai

AeroManip-VLA: Scalable Vision-Language-Action Learning for Aerial Manipulation with RL-Generated Demonstrations

arXiv:2609.36915v1 Announce Type: cross Abstract: Aerial manipulators extend robotic manipulation into 3D workspaces that are difficult for ground-based robots to access, creating new opportunities fo

Agentic AI for Scalable and Robust Optical Systems Control

arXiv:2602.20144v2 Announce Type: replace-cross Abstract: We present AgentOptics, an agentic AI framework for high-fidelity, autonomous optical system control built on the Model Context Protocol (MCP)

Agentic Commerce Bench: Measuring Fraud Detection for Agents That Spend Money

arXiv:2609.35886v1 Announce Type: cross Abstract: AI agents now hold spend authority and settle payments without per-action human confirmation. The resulting loss is often not a security failure: a co

All You Need Is Low Fidelity: Zero-Shot Sim-to-Real of Learned Robotic Fish Control

arXiv:2609.36993v1 Announce Type: new Abstract: Complex tasks for underwater robots remain limited by the capabilities of their controllers. Learning a better one for a soft, underactuated robotic fis

Altered Thoughts, Altered Actions: Reasoning Chain as Control Surface for a Vision-Language-Action Policy

arXiv:2603.12717v2 Announce Type: replace-cross Abstract: Vision-language-action policies map camera images and natural-language instructions to a robot's motor actions. Some of these policies are des

Tutorials

Amadeus: When Models of People Meet

arXiv:2609.35835v1 Announce Type: cross Abstract: With the sheer constant advancements raining down in the field of Artificial Intelligence, one particular possibility that may cross our mind is wheth

tutorialsarxiv-cs-lg

Research

Aperture: Merge-Consistent Rotary States for Compressed Tokens

arXiv:2609.36781v1 Announce Type: new Abstract: Token compression combines content from several positions, yet rotary position embeddings usually assign the merged token one coordinate. We ask what po

researcharxiv-cs-ai

ASCEND: Personal AI Agents for Autonomous Scientific Computing Across HPC Clusters and GPU Workstations

arXiv:2609.32868v2 Announce Type: replace-cross Abstract: Traditional scientific computing requires researchers to translate computational intent into environment configuration, resource requests, and

Asymmetric Scout-Worker Reconnaissance for Route Validation in Unknown Environments

arXiv:2609.36537v1 Announce Type: new Abstract: This paper studies asymmetric scout-worker reconnaissance in unknown environments, where a small, agile autonomous scout explores routes for a larger wo

agentsarxiv-cs-ro

Back2Struct: Making Structured Images Editable Again

arXiv:2609.37016v1 Announce Type: new Abstract: Structured images, such as diagrams, charts, and flowcharts, are inherently symbolic and can be compactly represented in an editable format, yet in prac

safetyarxiv-cs-cv

Backdoor in the Loop: Compromising Agentic Search via Malicious Retrievers

arXiv:2609.37468v1 Announce Type: cross Abstract: Agentic retrieval-augmented generation (RAG) interleaves reasoning with repeated retrieval, giving the retriever influence over both the evidence an a

Battery-Aware Reinforcement Learning for Aggressive Quadrotor Flight

arXiv:2609.37316v1 Announce Type: new Abstract: Agile flight tasks such as drone racing and pursuit-evasion require strong acceleration and precise turns, but the available thrust changes as the batte

BCNav: Bearing-Conditioned Depth Policies for Sound Source Navigation

arXiv:2609.37084v1 Announce Type: new Abstract: The ability to navigate toward sound sources extends a robot's reach beyond its visual field, enabling response to auditory events in unknown environmen

Beyond Interaction Capacity: Estimator Scaling with Recursive Models for CTR Prediction

arXiv:2609.37905v1 Announce Type: cross Abstract: Click-Through Rate prediction, a core task in recommendation and advertising systems, relies on modeling interactions among sparse categorical feature

Beyond Pixels: A Vector-to-Graph Framework for Reliable Schematic Auditing

arXiv:2602.11678v2 Announce Type: replace Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable progress in visual understanding, yet they suffer from a critical limitation: structu

Chinese-Jev: Bringing System One Model to Chinese-Language Tasks

arXiv:2609.36965v1 Announce Type: new Abstract: System One models such as Jev offer an efficient alternative to generative language models for tasks that require decisions rather than open-ended respo

local-aiarxiv-cs-cl

CIRCLE: A Framework for Evaluating AI from a Real-World Lens

arXiv:2602.24055v5 Announce Type: replace Abstract: This study proposes CIRCLE, a six-stage, lifecycle-based framework to bridge the reality gap between model-centric performance metrics and AI system

applicationsarxiv-cs-ai

Constitutional adapters: Inference-time interventions for misalignment and misuse

arXiv:2609.36657v1 Announce Type: cross Abstract: Training models to act in accordance with an explicitly defined set of principles, or 'constitution,' has shown promise as a robust and transparent me

CoRe-VLA: Preserving Cross-View Coordination in VLAs under Camera Shifts

arXiv:2609.37150v1 Announce Type: new Abstract: VLAs combine pretrained vision-language representations with action generation to enable language-guided control across diverse tasks, becoming a mainst

Counterfactual Video Generation Enables Scalable Humanoid Loco-Manipulation

arXiv:2609.38172v1 Announce Type: cross Abstract: Teaching humanoids loco-manipulation skills, such as carrying diverse objects, via visual imitation is a promising path toward generalist robots. Howe

safetyarxiv-cs-cv

Cumulative-Goodness Free-Riding in Forward-Forward Networks: Real, Repairable, but Not Accuracy-Dominant

arXiv:2605.06240v2 Announce Type: replace-cross Abstract: Forward-Forward (FF) training lets each layer learn from a local goodness criterion. In cumulative-goodness variants, later layers can inherit

local-aiarxiv-cs-ai

DecoyTrace: Toxic Decoys for Active Defense in Decentralized Federated Learning

arXiv:2609.36330v1 Announce Type: cross Abstract: Decentralized Federated Learning (DFL) eliminates the central aggregation server, reducing the single point of observation that traditional defenses a

Demistifying Data and Simulator Assumptions in Supervised Causal Discovery

arXiv:2609.37446v1 Announce Type: new Abstract: Supervised causal discovery learns to infer causal structure for a new dataset from training datasets paired with structural labels. These training pair

Hardware

DIET: Deletion-response Expert Trimming for Video Diffusion Transformers

arXiv:2609.37829v1 Announce Type: new Abstract: Video diffusion transformers (DiTs) increasingly adopt mixture-of-experts (MoE) architectures to reduce active computation, but their full expert storag

hardwarearxiv-cs-ai

Distilling Agentic Systems: A Roadmap across Models, Artifacts, and Harnesses

arXiv:2609.36630v1 Announce Type: new Abstract: Modern agents increasingly rely on memories, tools, and execution logic, so their competence extends beyond model parameters. This shift exposes a limit

Tutorials

DraftTrace: A Multi-View Analytics Environment for AI-Integrated Writing

arXiv:2609.36544v1 Announce Type: cross Abstract: Generative AI has changed how students produce writing assignments. The final artifact is no longer sufficient to understand the process through which

tutorialsarxiv-cs-ai

EASE: Behavior-Adaptive Skill Curation for Self-Evolving Agents

arXiv:2609.36746v1 Announce Type: new Abstract: Agent skills provide a lightweight mechanism for self-evolving agents to accumulate reusable procedural knowledge without updating model parameters. How

EgoAlign: Bridging the Human-Humanoid Gap for Long-Range Loco-Manipulation

arXiv:2609.38046v1 Announce Type: new Abstract: Egocentric human demonstrations offer an accessible source of task experience, but differences in body scale and controller response, together with miss

Evaluating Test-Time Scaling of General LLM Agents

arXiv:2602.18998v2 Announce Type: replace Abstract: LLM agents are increasingly expected to operate as general-purpose systems that resolve real-world user requests, yet their dynamic scaling behavior