Search: “deployment”

LeAP: Learnable Adaptive Permutation for Feature Selection in Heterogeneous and Sparse Recommender Systems

model-releasesarxiv-cs-lg

arXiv:2606.01111v1 Announce Type: new Abstract: Modern industrial recommender systems rely on thousands of heterogeneous features -- ranging from low-dimensional scalars (e.g., statistical value) to h

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Safety

LEGS: Fine-Tuning Teleop-Free VLAs for Humanoid Loco-manipulation in an Embodied Gaussian Splatting World

DGX agent

arXiv:2606.01458v1 Announce Type: new Abstract: Training vision-language-action (VLA) policies for humanoid loco-manipulation is constrained by the high cost and complexity of collecting human teleope

safetyarxiv-cs-ro

2 Jun 2026

LFA: Layer Feature Attention for Run-Time Introspection of 2D Object Detectors in Automated Driving

arXiv:2606.00372v1 Announce Type: new Abstract: Reliable object detection is critical for automated driving, yet even state-of-the-art detectors inevitably make errors that can compromise safety. Intr

safetyarxiv-cs-cv

Research

Logit Distillation on Manifolds: Mapping by Learning

arXiv:2606.00771v1 Announce Type: cross Abstract: A simple way to improve the performance of almost any machine learning model is not to train a single but several models with diverse algorithms which

researcharxiv-cs-ai

Lost in Delusion: Examining LLM Safety Under User Delusions and Distress

arXiv:2606.00975v1 Announce Type: new Abstract: LLM chatbots increasingly serve as a first source of support for people in psychological distress, including those whose distress is entangled with delu

safetyarxiv-cs-cl

MCPDepth: Omnidirectional Depth Estimation via Stereo Matching from Multi-Cylindrical Panoramas

arXiv:2408.01653v4 Announce Type: replace Abstract: Omnidirectional depth estimation presents a significant challenge due to the inherent distortions in panoramic images. Despite notable advancements,

applicationsarxiv-cs-cv

Med-HEAL: Analyzing and Mitigating Hallucinations in Medical LLMs with Hallucination-Aware In-Context Learning

model-releasesarxiv-cs-cl

arXiv:2606.01301v1 Announce Type: new Abstract: Hallucinations in medical large language models (LLMs) pose serious risks for clinical decision support, particularly when models must reason over compl

MedGym:A Unified Continuous-Time Benchmark for Dynamic Medical Treatment Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2606.01028v1 Announce Type: new Abstract: Medical treatment recommendation poses several challenges to reinforcement learning (RL): patient physiology evolves in continuous time, measurements an

MemPro: Agentic Memory Systems as Evolvable Programs

arXiv:2606.00619v1 Announce Type: cross Abstract: Long-horizon autonomous agents require memory systems to retain historical information, track evolving states, and reuse relevant knowledge beyond fin

agentsarxiv-cs-ai

Microsoft debuts an expansion of its model families and agentic AI intelligence for developers

Microsoft Corp. announced an expansion to its artificial intelligence models and agentic AI infrastructure today that brings more data and context into the hands of developers and business users as th

agentssiliconangle

Microsoft launches Rayfin to let developers and agents build app backends on Fabric

model-releasessiliconangle

Microsoft Corp. today introduced Rayfin, an open-source software development kit and command-line interface that lets developers and coding agents define an entire application backend in code and depl

MiCU: End-to-End Smart Home Command Understanding with Large Language Model

arXiv:2606.01099v1 Announce Type: cross Abstract: Command understanding systems in smart home ecosystems can automate device control and substantially improve user experience. However, while they perf

applicationsarxiv-cs-ai

Modeling Distinct Human Interaction in Web Agents

arXiv:2602.17588v3 Announce Type: replace Abstract: Despite rapid progress in autonomous web agents, human involvement remains essential for shaping preferences and correcting agent behavior as tasks

agentsarxiv-cs-cl

Monitoring Agentic Systems Before They're Reliable

arXiv:2606.02494v1 Announce Type: cross Abstract: Agentic systems entering production typically operate as partially integrated assemblies where structural defects, not task-level errors, dominate the

agentsarxiv-cs-ai

Move from test to production by running high-performance inference directly on Foundry. At #MSBuild, we demoed an end-to-end workflow showin…

applicationsfireworks-ai--x

Move from test to production by running high-performance inference directly on Foundry. At #MSBuild, we demoed an end-to-end workflow showing how unified infrastructure improves latency, reduces cost,

Network Distributed Multi-Agent Reinforcement Learning for Consensus Control of Quadcopters

arXiv:2606.02107v1 Announce Type: cross Abstract: This paper proposes a Network Distributed Multi-Agent Reinforcement Learning (ND-MARL) framework for quadcopter consensus control. Compared to convent

Neural Low-Discrepancy Sequences

arXiv:2510.03745v2 Announce Type: replace Abstract: Low-discrepancy points are designed to efficiently fill the space in a uniform manner. This uniformity is highly advantageous in many problems in sc

applicationsarxiv-cs-lg

OmniEEG-Bench: A Standardized Evaluation Benchmark for EEG Foundation Models

model-releasesarxiv-cs-lg

arXiv:2606.00815v1 Announce Type: new Abstract: Electroencephalography (EEG) supports a variety of brain-computer interface (BCI) tasks ranging from brain-state monitoring to human-LLM interactions. E

Hardware

Open by Design: How NVIDIA and DigitalOcean Are Building the Stack for the Always-On Agentic Era

NVIDIA and DigitalOcean are collaborating to develop an open infrastructure stack designed to support autonomous AI agents that operate continuously. The initiative emphasizes open-source principles a

hardwaredigitalocean

OSCAR: Obstacle Survival Curves for Adaptive Robot Navigation

arXiv:2606.00990v1 Announce Type: new Abstract: A mobile robot following a graph of known routes can make costly navigation errors when a temporary obstacle blocks a critical edge: waiting too long be

safetyarxiv-cs-ro

PaCo-VLA: Passivity-Shielded Compliance Prior for Contact-Rich Vision-Language-Action Manipulation

arXiv:2606.00515v1 Announce Type: cross Abstract: Contact-rich manipulation demands both high-level semantic reasoning and the safe regulation of high-frequency contact dynamics. While Vision-Language

applicationsarxiv-cs-ai

Parameter Alignment Mitigates Catastrophic Forgetting in Multilingual Expert Language Models

model-releasesarxiv-cs-cl

arXiv:2606.00284v1 Announce Type: new Abstract: While continual pretraining~(CPT) is a practical way to extend large language models to new languages, naive finetuning on targeted data erodes existing

Permissive Safety Through Trusted Inference: Verifiable Belief-Space Neural Safety Filters for Assured Interactive Robotics

arXiv:2606.02562v1 Announce Type: cross Abstract: Autonomous robots that interact with people must make safe and efficient decisions under human-induced uncertainty, such as their preferences, goals,

Perspective on Bias in Biomedical AI: Preventing Downstream Healthcare Disparities

arXiv:2604.14514v2 Announce Type: replace Abstract: Healthcare disparities persist across socioeconomic boundaries, often attributed to unequal access to screening, diagnostics, and therapeutics. Howe

PlatonicNav: Unveiling Semantic Correspondence in Navigation with Platonic Topological Maps

arXiv:2606.01788v1 Announce Type: new Abstract: Embodied visual navigation, where an agent perceives a complex environment and acts to reach a goal from raw sensory input, underpins a wide range of ap

agentsarxiv-cs-cv

POIROT: Interrogating Agents for Failure Detection in Multi-Agent Systems

arXiv:2606.02282v1 Announce Type: new Abstract: Orchestrating Large Language Models into Multi-Agent Systems (LLM-MAS) has unlocked remarkable reasoning capabilities, yet emergent failures and halluci

Hardware

PortBERT: Navigating the Depths of Portuguese Language Models

arXiv:2606.02100v1 Announce Type: new Abstract: Transformer models dominate modern NLP, but efficient, language-specific models remain scarce. In Portuguese, most focus on scale or accuracy, often neg

hardwarearxiv-cs-cl

Hardware

Predicting Future Utility: Global Combinatorial Optimization for Task-Agnostic KV Cache Eviction

arXiv:2602.08585v2 Announce Type: replace-cross Abstract: Given the quadratic complexity of attention, KV cache eviction is vital to accelerate model inference. Current KV cache eviction methods typic

hardwarearxiv-cs-ai

Probabilistic Performance Guarantees for Multi-Task Reinforcement Learning

arXiv:2602.02098v2 Announce Type: replace-cross Abstract: Multi-task reinforcement learning trains generalist policies that can execute multiple tasks. While recent years have seen significant progres

ProbeScale: Probing Analysis to Optimize Neural Scaling Laws for Efficient Small Language Model Inference

arXiv:2606.01806v1 Announce Type: cross Abstract: Small Language Models (SLMs) offer a balance between capability and computational feasibility. Neural scaling laws inform their optimal training, sugg

Local Ai

Project SPARROW and the Future of Conservation Technology

arXiv:2606.00108v1 Announce Type: cross Abstract: Global biodiversity is declining at unprecedented rates, yet the tools available to monitor and protect ecosystems remain limited by constraints in po

local-aiarxiv-cs-ai

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video

arXiv:2606.02301v1 Announce Type: cross Abstract: Chronic pain diminishes quality of life by decreasing functional ability, yet objectively measuring this functional impact remains challenging in real

Quick explainer of our managed deepagents offering

This post likely provides a brief explanation of a managed deepagents offering, describing what deepagents are, how the managed service works, and its key benefits or use cases. As a post from Harriso

agentsharrison-chase--x

Recursive Vision Transformer with Dynamic Depth and Width Adjustment for Resource-Efficient Image Semantic Communication

model-releasesarxiv-cs-cv

arXiv:2606.00114v1 Announce Type: new Abstract: Image semantic communication is a critical component in next-generation wireless communication systems. However, such systems typically suffer from larg

Tutorials

Repair Before Veto: Repair-Augmented Constraint Learning for Contextual Decisions

arXiv:2606.02326v1 Announce Type: new Abstract: Hard constraints are usually treated as terminal vetoes: once a candidate violates a requirement, the learned rule rejects it and any repair is handled

tutorialsarxiv-cs-ai

RESBev: Making BEV Perception More Robust

arXiv:2603.09529v2 Announce Type: replace Abstract: Bird's-eye-view (BEV) perception has emerged as a cornerstone of autonomous driving systems, providing a structured, ego-centric representation crit

safetyarxiv-cs-cv

Retrieval-aligned Tabular Foundation Models Enable Robust Clinical Risk Prediction in Electronic Health Records Under Real-world Constraints

arXiv:2604.01841v2 Announce Type: replace Abstract: Clinical prediction from structured electronic health records (EHRs) is challenging due to high dimensionality, heterogeneity, class imbalance, and

Robust Integrated Planning and Control for Quadrotors in Dynamic Environments via NMPC with CBF Penalties

arXiv:2606.01038v1 Announce Type: new Abstract: This paper presents a new robust integrated planning and control (IPC) strategy for multirotor uncrewed aerial vehicles. We propose a nonlinear model pr

safetyarxiv-cs-ro

Safety Alignment of LMs via Non-cooperative Games

arXiv:2512.20806v3 Announce Type: replace Abstract: Ensuring the safety of language models (LMs) while maintaining their usefulness remains a critical challenge in AI alignment. Current approaches rel

Self-Imitated Diffusion Policy for Efficient and Robust Visual Navigation

model-releasesarxiv-cs-ro

arXiv:2601.22965v2 Announce Type: replace Abstract: Diffusion policies (DP) have demonstrated significant potential in visual navigation by capturing diverse multi-modal trajectory distributions. Howe

Research

Semantic-Geometric Task Representations for Bimanual Manipulation from Human Demonstrations to Robot Action Planning

arXiv:2601.11460v2 Announce Type: replace-cross Abstract: Learning structured task representations from human demonstrations is essential for bimanual manipulation, where action ordering, object invol

researcharxiv-cs-lg

Semantic Retrieval for Product Search in E-Commerce

arXiv:2606.01504v1 Announce Type: cross Abstract: Semantic retrieval in e-commerce must handle short, noisy, and colloquial queries over large product catalogs with fine-grained attribute distinctions

safetyarxiv-cs-lg

Seq-DeepIPC: Sequential Sensing for End-to-End Control in Legged Robot Navigation

arXiv:2510.23057v2 Announce Type: replace-cross Abstract: We present Seq-DeepIPC, a sequential end-to-end perception-to-control model for legged robot navigation in real-world environments. Seq-DeepIP

agentsarxiv-cs-cv

Tools

Serving MiniMax-M3 for efficient inference: Unlocking 1M-Token Context and Multimodality Without Regrets

MiniMax-M3 is a large language model capable of handling 1 million token contexts and multimodal inputs while maintaining efficient inference performance. Together AI's blog post discusses techniques

toolstogether-ai-blog

Set-Supervised Diffusion Policy: Learning Action-Chunking Diffusion through Corrections

arXiv:2606.01865v1 Announce Type: new Abstract: Diffusion policies have recently emerged as a powerful framework for robotic manipulation. However, like other behavior cloning methods, they remain vul

safetyarxiv-cs-ro

SHERLOCK: Towards Dynamic Knowledge Adaptation in LLM-enhanced E-commerce Risk Management

arXiv:2510.08948v4 Announce Type: replace-cross Abstract: Effective e-commerce risk management requires in-depth case investigations to identify emerging fraud patterns in highly adversarial environme

Shortcut to Nowhere: Demystifying Deep Spurious Regression

arXiv:2606.01723v1 Announce Type: cross Abstract: Real-world regression often exhibits shortcuts: attributes that are spuriously correlated with continuous targets in training, yet unreliable under de

applicationsarxiv-cs-ai

Single-Channel Tissue Segmentation via Cross-Modal Distillation from Foundation Models

model-releasesarxiv-cs-cv

arXiv:2606.00928v1 Announce Type: new Abstract: Multiplexed fluorescence microscopy improves tissue segmentation by providing complementary channels including nuclear (DAPI) and membrane (E-cadherin),