Search: “deployment”

UniSim-SLAM: Feed-Forward SLAM with Unified Sim(3) Optimization

arXiv:2608.01706v1 Announce Type: new Abstract: Recent geometric foundation models enable feed-forward inference for SLAM, but their predictions are strongly dependent on the input view set, which lea

researcharxiv-cs-cv

4 Aug 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Why Does Action Chunking Improve Behavioral Cloning Performance in Robotic Control?

DGX agent

arXiv:2608.02547v1 Announce Type: new Abstract: Action chunking---predicting and executing multiple actions instead of a single action---has proven to be a critical component for learning effective ro

safetyarxiv-cs-ro

4 Aug 2026

Tutorials

A user's guide to PINNs in geometric analysis: lessons from the asymptotic Plateau problem

arXiv:2607.28733v1 Announce Type: cross Abstract: This proceedings contribution elaborates on the findings of arXiv:2605.26234v2: a joint work with Marco Usula, where we introduced a machine learning

tutorialsarxiv-cs-ai

Benchmarking Frontier Large Language Models Against Official Crash Database Coding Using Police Crash Narratives

arXiv:2607.29064v1 Announce Type: cross Abstract: Police crash narratives contain information that may supplement structured crash databases, but manual review is labor-intensive and it remains unclea

Beyond Component Testing: Validating Agentic AI Systems

arXiv:2607.29405v1 Announce Type: new Abstract: Agentic AI systems act through multi-step trajectories that combine planning, tool use, memory, interaction, and adaptation. This behavior stretches val

Can Zero-Shot LLMs Predict Child Malnutrition? A Fairness and Temporal Robustness Study

arXiv:2607.29082v1 Announce Type: new Abstract: Child malnutrition remains a major public health challenge in low- and middle-income countries, particularly in South Asia, where early identification o

safetyarxiv-cs-cl

ConnectED: A Curriculum-Aligned AI System for Vietnamese Instructional Lesson Planning and Student Learning

arXiv:2607.28647v1 Announce Type: cross Abstract: This paper presents ConnectED, a human-centered AI system that supports the full instructional lifecycle in Vietnamese education by linking curriculum

DASH-OPD: Discrepancy-Aware Switching with Hysteresis for On-Policy Distillation

arXiv:2607.29078v1 Announce Type: new Abstract: On-policy distillation (OPD) trains student models on their own rollouts to reduce exposure bias. However, in multi-turn agent scenarios, early student

Development of FDD-ON: an Ontology for VAV HVAC System Fault Detection and Diagnostics

arXiv:2607.29657v1 Announce Type: new Abstract: Fault detection and diagnosis (FDD) technology is essential for improving HVAC system reliability, energy efficiency, and maintenance effectiveness. How

Distilling Knowledge from Large Language Models into Lightweight Reinforcement Learning Agents for Autonomous Cyber Operations

arXiv:2607.28826v1 Announce Type: new Abstract: Autonomous Cyber Operations (ACO) are increasingly important for defending enterprise networks as cyber threats continue to evolve in sophistication. AC

Do Medical Foundation Models Generalize on the African Brain?

arXiv:2607.28771v1 Announce Type: new Abstract: Medical foundation models (FMs) are increasingly used for brain MRI analysis. However, their evaluation remains dominated by high-resource datasets, lea

safetyarxiv-cs-cv

Domain-Adaptive Deep Joint Source-Channel Coding for Image Classification

arXiv:2607.28907v1 Announce Type: cross Abstract: Deep joint source--channel coding (Deep JSCC) enables visual semantic transmission by mapping inputs directly to channel symbols and task outputs, but

safetyarxiv-cs-cv

Applications

Don't Contrast the Impossible: Region-Constrained Batching for Contrastive User Modeling on a Local Community Platform

arXiv:2607.28971v1 Announce Type: cross Abstract: Contrastive learning is widely used for user modeling in large-scale recommender systems, where standard in-batch negatives implicitly assume universa

applicationsarxiv-cs-lg

Applications

DragonCrawl: A Generative, Intent-Based Framework for Scalable Mobile End-to-End Testing

arXiv:2607.28750v1 Announce Type: cross Abstract: As mobile applications grow in complexity, traditional End-to-End (E2E) testing frameworks struggle with UI volatility, maintenance overhead, and cros

applicationsarxiv-cs-ai

Empowering Cross-Domain Sequential Recommendation with Hybrid Tokenization and Serial-Parallel Decoding

arXiv:2607.28659v1 Announce Type: new Abstract: Cross-domain sequential recommendation (CDSR) aims to model users' dynamic interest transitions and sequential patterns across multiple domains. Recentl

Expert-Data Alignment Governs Generation Quality in Decentralized Diffusion Models

arXiv:2602.02685v3 Announce Type: replace Abstract: Decentralized Diffusion Models (DDMs) route denoising through experts trained independently on disjoint data clusters, which can strongly disagree i

safetyarxiv-cs-lg

GALA: Generative Aligned Learning for Adaptive Multimodal Representation in the Taobao Shangou Recommender System

arXiv:2607.29213v1 Announce Type: cross Abstract: Modern recommender systems in food delivery increasingly leverage multimodal signals, including images, text, and user interaction histories, to enhan

safetyarxiv-cs-lg

Agents

Generative AI in Action: Field Experimental Evidence from Alibaba's Customer Service Operations

arXiv:2603.29888v2 Announce Type: replace-cross Abstract: In collaboration with Alibaba, we study how a generative AI assistant affects service performance in e-commerce after-sales operations. In a l

agentsarxiv-cs-ai

GPA-RAM: Grasp-Pretraining Augmented Robotic Attention Mamba for Spatial Task Learning

arXiv:2504.19683v4 Announce Type: replace Abstract: Fine-grained robotic manipulation often fails when inaccurate initial grasps propagate errors and necessitate complex pose correction. We propose Gr

researcharxiv-cs-ro

Have I Seen You? Embedding Behavior Signals Synthetic Face Dataset Membership

arXiv:2607.29144v1 Announce Type: cross Abstract: Synthetic face datasets are increasingly used to reduce privacy exposure and data access constraints in biometric recognition. Yet the generators that

HenTwin: A Multimodal Digital Twin Framework for Longitudinal Biological State Monitoring in Laying Hens

arXiv:2607.28652v1 Announce Type: cross Abstract: Early-life monitoring in laying hens remains constrained by fragmented single-modality sensing and the absence of formal system-level state representa

Homotopy-Aware Corridor Generation without Predefined Reference Paths

arXiv:2607.29513v1 Announce Type: new Abstract: Generating safe corridors is essential for collision-free robotic motion planning, yet most existing methods rely on predefined reference paths, which b

safetyarxiv-cs-ro

Agents

MerchantBench: Benchmarking LLM Agents for Long-Term Coherence in E-Commerce Operations

arXiv:2607.28956v1 Announce Type: new Abstract: Large language model agents are increasingly evaluated as autonomous tool users, yet most benchmarks focus on bounded tasks with immediate success crite

agentsarxiv-cs-ai

On the Efficacy of Self-Supervised Point Cloud Encoders for Efficient 3D Large Language Models

arXiv:2607.29136v1 Announce Type: new Abstract: 3D point cloud-language models (3D-LLMs) enable 3D understanding by pairing point cloud encoders with large language models, but existing methods rely o

safetyarxiv-cs-cv

OpenClaw and Ollama in Agentic AI: Toward Fully Autonomous and Scalable AI Agent Systems

arXiv:2607.28629v1 Announce Type: new Abstract: The rapid transition from reactive large language models (LLMs) to persistent, action-capable systems has exposed critical gaps in the architectural und

Agents

Outcome-Guided Distillation: A Teacher-Student Framework to Advance VLM Reasoning in Autonomous Driving

arXiv:2607.29052v1 Announce Type: new Abstract: End-to-end (E2E) autonomous driving aims to learn a direct mapping from visual observations to control actions. However, these E2E models often act as b

agentsarxiv-cs-ro

PARALLEL: A Prefrontal-Aligned Reinforcement inspired Approach for Language-Model Learning under Explicit Limits

arXiv:2607.28982v1 Announce Type: cross Abstract: Recent language models achieve strong performance across a variety of tasks, but conventional adaptation applies updates uniformly across training sam

Receding-Horizon Next-Best-View Planner for Autonomous Leaf Surface Reconstruction

model-releasesarxiv-cs-ro

arXiv:2607.28995v1 Announce Type: new Abstract: Accurate plant leaf modeling is fundamental to downstream tasks such as plant growth monitoring, and phenotyping for yield estimation. Autonomous roboti

RynnBrain 1.1: Towards More Capable and Generalizable Embodied Foundation Model

model-releasesarxiv-cs-ro

arXiv:2607.17977v2 Announce Type: replace Abstract: We present RynnBrain 1.1, a family of embodied foundation models spanning 2B, 9B, and 122B-A10B scales. Trained with a unified spatio-temporal and p

SEDR-Seq2P: A Lightweight Dilated Residual Sequence-to-Point Network for Multi-Task Industrial NILM

arXiv:2607.28693v1 Announce Type: cross Abstract: Industrial NILM remains challenging because measurement noise and widespread concurrent machine operation reduce the generalization of models tuned on

SeekBrain: An Autonomous Multi-Agent System for Accelerating Neuroscience Discovery

arXiv:2607.29347v1 Announce Type: cross Abstract: Modern neuroscience relies on integrating multi-scale, multimodal datasets to uncover the neural principles underlying intelligence. However, analytic

Self-Play Meets Skill Evolution: Self-Evolving Search Agents that Pose, Solve, and Remember

arXiv:2607.29468v1 Announce Type: new Abstract: Self-play agents can generate training problems without questions from target benchmarks, but their curricula lack persistent state: failures affect gra

SULAND v2: A Refined RGB Dataset and Deep Learning Object Detection Benchmark for UAV/UGV-Based SUrface LANDmine Detection Under Domain Shift

model-releasesarxiv-cs-cv

arXiv:2607.28996v1 Announce Type: new Abstract: RGB imagery offers a practical, low-cost option for Unmanned Aerial/Ground Vehicle (UAV/UGV) survey support in surface-landmine detection, but object de

Technological Advances in Detecting and Managing Cognitive Impairment in Older Adults: Trends, Challenges, and Future Directions

arXiv:2607.28687v1 Announce Type: cross Abstract: As populations age, cognitive decline from mild cognitive impairment (MCI) to dementia is a defining health challenge of the coming decades, yet routi

Tool Specifications Matter: Uncovering and Mitigating Safety Risks in AI Agents

arXiv:2607.29254v1 Announce Type: new Abstract: AI agents extend large language models (LLMs) with external tools, enabling them to perform complex tasks and translate model outputs into consequential

Towards bridging the gap: Systematic sim-to-real transfer for diverse legged robots

model-releasesarxiv-cs-ro

arXiv:2509.06342v2 Announce Type: replace Abstract: Legged robots must achieve both robust locomotion and energy efficiency to be practical in real-world environments. Yet controllers trained in simul

Uncertainty-Aware Deepfake Detection via Multi-View Structural Learning

arXiv:2607.28769v1 Announce Type: new Abstract: Security-critical biometric and forensic applications require accurate predictions and reliable confidence estimates, particularly under distribution sh

researcharxiv-cs-cv

WCM: A World Critic Model for Vision-Language-Action Reinforcement Learning

arXiv:2607.29613v1 Announce Type: cross Abstract: Reinforcement learning (RL) post-training of Vision-Language-Action (VLA) models has shown strong promise for robotic manipulation. Among RL methods,

safetyarxiv-cs-cl

A Physics-Informed Framework for PID Tuning of Chemical Processes Using Large Language Model Agents

arXiv:2607.26594v1 Announce Type: cross Abstract: PID tuning for chemical processes commonly relies on identified process models, whereas plant engineers often retune loops iteratively by observing re

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

arXiv:2607.28617v1 Announce Type: cross Abstract: System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout com

researcharxiv-cs-cl

Beyond the Bidirectional Promise: Re-evaluating the Robustness of Diffusion Language Models

arXiv:2607.27386v1 Announce Type: cross Abstract: Diffusion Language Models (DLMs) offer a compelling alternative to autoregressive (AR) generation by enabling bidirectional context and iterative refi

Applications

CLAM: Continuous Latent Action Models for Robot Learning from Unlabeled Demonstrations

arXiv:2505.04999v2 Announce Type: replace-cross Abstract: Learning robot control policies from demonstrations typically requires action-labeled expert data, which is expensive to collect through teleo

applicationsarxiv-cs-lg

Exposure is not manifestation: measurement target and output resolution jointly determine which behavioural-faithfulness evaluator wins

model-releasesarxiv-cs-cl

arXiv:2607.09306v3 Announce Type: replace Abstract: Behavioural auditing asks whether a language model behaves as it claims, but detection scores are reported without separating two targets: whether a

Fidelity Is Not Safety: Gently-Compressed LLMs Pass Every Data-Free Quality Guard Yet Invent Procedure Steps in Agentic Execution

arXiv:2607.28196v1 Announce Type: new Abstract: Practitioners accept a compressed language model once it clears a stack of data-cheap quality guards: perplexity within a small factor of the original,

safetyarxiv-cs-cl

Local Ai

First-order Constrained Trilevel Optimization Over Distributed Networks for Robust Coreset Selection

arXiv:2607.27632v1 Announce Type: new Abstract: With the rapid advancement of the Internet of Things (IoT), massive amounts of data are generated across distributed edge networks. Training models on f

local-aiarxiv-cs-lg

From Expert Reduction to Behavioral Divergence: Tracing Numerical State through Sparse MoE Inference

arXiv:2607.28097v1 Announce Type: new Abstract: Mathematically equivalent expert-reduction orders can produce observably different sparse-MoE executions. We isolate this effect in native DeepSeek-V4-F

Gradient-free Task-Conditioned Retrieval for On-Device In-Context Learning

model-releasesarxiv-cs-cl

arXiv:2607.27766v1 Announce Type: new Abstract: On-device in-context learning (ICL) relies on pre-inference retrieval to select demonstrations for useful context before downstream model inference. Thi

GyRot: Leveraging Hidden Synergy between Rotation and Fine-grained Group Quantization for Low-bit LLM Inference

arXiv:2607.27694v1 Announce Type: cross Abstract: Low-bit quantization is essential for efficient LLM inference, and both rotation and fine-grained group quantization have shown individual promise. Ho