Search: “deployment”

DBpedia-Enriched Company Representation for B2B Lead Recommendation

arXiv:2606.28355v1 Announce Type: cross Abstract: Selecting which companies to approach is a central challenge in business-to-business (B2B) sales, where decisions are often based on manual research a

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Deciphering Region-Level Signatures from Latency Measurements in LEO Satellite Internet

DGX agent

arXiv:2606.29324v1 Announce Type: new Abstract: Low-Earth orbit (LEO) satellite Internet has become an indispensable infrastructure that provide growing coverage for global users. Despite extensive me

researcharxiv-cs-lg

30 Jun 2026

DistilledGemma: Balanced Efficiency-Accuracy for Person-Place Relation Extraction from Multilingual Historical Articles

arXiv:2606.29130v1 Announce Type: new Abstract: We present DistilledGemma, an efficient and accurate system for the HIPE-2026 shared task on person-place relation extraction from multilingual historic

DLR: Zero-Inference-Cost Latent Residuals for Low-Rank Pre-Training

arXiv:2606.28932v1 Announce Type: cross Abstract: Large language models have driven recent progress in language and multimodal AI, yet pre-training them at scale is prohibitively expensive. Low-rank p

DRIVE-Nav: Directional Reasoning, Inspection, and Verification for Efficient Open-Vocabulary Navigation

arXiv:2603.28691v2 Announce Type: replace Abstract: Open-Vocabulary Object Navigation (OVON) requires an embodied agent to locate a language-specified target in unknown environments. Many zero-shot me

agentsarxiv-cs-ro

Early Warning Signals for OpenVLA Failure under Visual Distribution Shift

arXiv:2606.29699v1 Announce Type: cross Abstract: Vision Language Action models combine perception, language grounding, and control in a single policy, but their failures are hard to diagnose once vis

Envisage: Diffusion-Based Rhinoplasty Goal Visualization with Mask-Decomposed Evaluation

model-releasesarxiv-cs-cv

arXiv:2606.28628v1 Announce Type: cross Abstract: Localized generative editing needs localized evaluation: full-image identity metrics are structurally confounded under hard-composited edits. We prese

Applications

Event-VLA: Action-Conditioned Event Fusion for Robust Vision-Language-Action Model

arXiv:2606.29384v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become an important paradigm of embodied AI. However, existing VLA models typically assume well-lit and stable

applicationsarxiv-cs-cv

Evolutionary Hyperparameter Optimization to Find Lightweight CNN Models for Autonomous Steering

arXiv:2606.29684v1 Announce Type: cross Abstract: This research investigates the optimization of Convolutional and Dense Neural Networks (CNNs and DNNs) for autonomous steering using the (N+M) Evoluti

agentsarxiv-cs-cv

Industry

Excited to be working with MIXI in Japan as we continue to grow our partnership.

industrycristobal-valenzuela--x

Excited to be working with MIXI in Japan as we continue to grow our partnership. Today, we're announcing a strategic partnership with MIXI, one of Japan's largest gaming, sports and entertainment comp

Exploration and Online Transfer with Behavioral Foundation Models

arXiv:2606.29980v1 Announce Type: new Abstract: Zero-shot Transfer in Reinforcement Learning (RL) aims to train an agent that can generate optimal policies for any reward function, without additional

safetyarxiv-cs-ai

Falsifying Discriminant Validity of Predictive Algorithms

arXiv:2601.17146v2 Announce Type: replace-cross Abstract: Empirical investigations into unintended model behavior often show that the algorithm is predicting another outcome than what was intended. Th

Fast Enough to Act: Spatio-Temporal Visual Token Merging for Low-Latency Robotic VLMs and VLAs

arXiv:2606.29350v1 Announce Type: cross Abstract: Vision-language models and vision-language action models endow the robot with unprecedented capabilities. However, the input of video and high-resolut

safetyarxiv-cs-ai

Fast Wireless Foundation Models with Early-Exits

arXiv:2606.29640v1 Announce Type: cross Abstract: While wireless foundation models (FMs) are demonstrating strong potential to enable AI-Native 6G networks, their high computational cost remains a cri

researcharxiv-cs-ai

Few-class Fidelity: Evaluating Explanations of Real-conditions CNN classifiers with Optimized Perturbations

arXiv:2606.28391v1 Announce Type: cross Abstract: The wide use of Convolutional Neural Networks (CNN) in numerous domains and real-world classification applications is justified by their high precisio

local-aiarxiv-cs-ai

From Failure Taxonomy to Intervention: A Diagnostic Methodology for Industry-Scale AVLM in Video and Live-Streaming Platform Moderation

model-releasesarxiv-cs-lg

arXiv:2606.30059v1 Announce Type: new Abstract: Industry-scale video and live-streaming moderation imposes requirements that are difficult to satisfy with generic pretrained public models or external

From Tool Connection to Execution Control: Benchmarking Security Invariants in MCP-Style Agent Runtimes

arXiv:2606.29073v1 Announce Type: cross Abstract: Model Context Protocol (MCP)-style ecosystems give language-model applications a practical connection layer for tools, resources, prompts, and transpo

Good Enough? An Investigation on the Impact of Label Quality in Large-Scale Medical Datasets

arXiv:2505.20928v2 Announce Type: replace Abstract: Manually refining radiological segmentation masks is highly resource-intensive. To determine when this expert commitment is truly justified for the

researcharxiv-cs-cv

Governance Decay: How Context Compaction Silently Erases Safety Constraints in Long-Horizon LLM Agents

arXiv:2606.22528v2 Announce Type: replace Abstract: Modern LLM agents increasingly rely on context compaction, summarization, or eviction to keep long-running sessions within a token budget. We show t

GraphChase: A Platform and Benchmark for Urban Network Security Games

arXiv:2501.17559v2 Announce Type: replace Abstract: After the achievement of solving two-player zero-sum games, more AI researchers focus on solving multiplayer games. Urban Network Security Games (ex

Guided Unconditional and Conditional Generative Models for Super-Resolution and Inference of Quasi-Geostrophic Turbulence

arXiv:2507.00719v3 Announce Type: replace-cross Abstract: Typically, numerical simulations of Earth systems are coarse, and Earth observations are sparse and gappy. We apply four generative diffusion

Harvesting AI Computation at the Edge via Generic Approximation

arXiv:2606.29518v1 Announce Type: cross Abstract: With the widespread adoption of AI in various IoT scenarios such as smart sensing and processing, AI chips have become a common component at the edge.

How Schrödinger sped up molecular discovery by 4x with Alphaevolve

model-releasesgoogle-cloud-ai

Computational chemistry researchers have traditionally faced a frustrating trade-off when simulating molecular interactions: use fast classical force fields that sacrifice precision or rely on accurat

Applications

HUMEMBR: Learning Human Routines for Predictive Embodied Navigation

arXiv:2606.30404v1 Announce Type: new Abstract: Understanding and navigating human-centered environments over extended periods of time while considering human behavior and routines remains a fundament

applicationsarxiv-cs-ro

HyphaeDB: A Living Knowledge Topology for Agent-First Memory

arXiv:2606.28781v1 Announce Type: new Abstract: Every existing vector database and agent memory framework treats memory as passive storage that agents query explicitly. No system propagates knowledge

agentsarxiv-cs-ai

In-Vehicle Digital Twin-Based Collision Warning Framework with Sybil Attack Detection

arXiv:2606.28625v1 Announce Type: cross Abstract: Connected Vehicles (CVs) rely extensively on communication technologies to enable data-driven predictive analyses for enhancing performance and safety

safetyarxiv-cs-lg

Applications

inference reliability has historically been a tax on devs that only large well-funded startups could afford: reserve GPUs in advance, sign a…

applicationsfireworks-ai--x

inference reliability has historically been a tax on devs that only large well-funded startups could afford: reserve GPUs in advance, sign a contract, guess your peak throughput requirements. everyone

Tutorials

Inoculation Adapters: Improved Selective Generalization of Capabilities with Fewer Surprising Backdoors

arXiv:2606.30252v1 Announce Type: new Abstract: Inoculation prompting is a selective generalization technique used against Emergent Misalignment. We introduce inoculation adapters (IA), which similarl

tutorialsarxiv-cs-ai

IREU: Identity-Related Encoder-Only Unlearning for Customized Portrait Generation

arXiv:2606.29880v1 Announce Type: new Abstract: Customized Portrait Generation (CPG) technologies have been widely used to generate high-fidelity person images given an input image indicating the iden

researcharxiv-cs-cv

JoyAI-Sim: A Simulation-Enabled Interconversion Toolchain for the Embodied Data Pyramid

arXiv:2606.16776v2 Announce Type: replace Abstract: Generalist robot policies require trustworthy evaluation and robot-usable training data, but both are difficult to scale with physical robots alone.

researcharxiv-cs-ro

KernelSight-LM: A Kernel-Level LLM Inference Simulator

arXiv:2606.28565v1 Announce Type: cross Abstract: As large language models (LLMs) move into production serving, practitioners must rapidly evaluate inference performance across diverse hardware, model

local-aiarxiv-cs-ai

Know Before You Fetch: Calibrated Retrieval-Budget Allocation for Retrieval-Augmented Generation

arXiv:2606.29959v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) typically retrieves a fixed number of passages for every query. This is wasteful when the reader already knows th

LaVPR: Benchmarking Language and Vision for Place Recognition

model-releasesarxiv-cs-cv

arXiv:2602.03253v2 Announce Type: replace Abstract: Visual Place Recognition (VPR) often fails under extreme environmental changes and perceptual aliasing. Beyond these limitations, standard systems c

Learning to Route and Schedule LLMs from User Retrials via Contextual Queueing Bandits

model-releasesarxiv-cs-lg

arXiv:2602.02061v2 Announce Type: replace Abstract: Explosive demands for LLMs often cause user queries to accumulate in server queues, requiring efficient routing (query-LLM matching) and scheduling

Learning Where and When: Patch-Based Spatiotemporal Localization in Weakly Supervised Video Anomaly Detection

arXiv:2606.29498v1 Announce Type: new Abstract: Weakly supervised video anomaly detection (WSVAD) has predominantly focused on temporal localization, identifying when anomalies occur while largely neg

local-aiarxiv-cs-cv

Looking Is Not Picking: An Attention-Segment Account of Tool-Selection Failures in LLM Agents

arXiv:2606.16364v2 Announce Type: replace Abstract: LLM agents mis-call tools, and the natural guess is that the model failed to see the right tool in a crowded harness. We show the opposite through a

local-aiarxiv-cs-ai

mamabench and mamaretrieval: Benchmarks for Evaluating Medical Retrieval-Augmented Generation in Maternal, Neonatal, and Reproductive Health

arXiv:2606.29467v1 Announce Type: new Abstract: Medical question-answering benchmarks rarely cover the maternal, neonatal, child, and reproductive-health questions a nurse-midwife asks, and, to our kn

Manufactured Confidence: How Memory Consolidation Turns Hearsay into Confident Facts

arXiv:2606.29279v1 Announce Type: cross Abstract: LLM agents carry conclusions across steps and sessions in compressed memory, and memory products (e.g., mem0, LangMem) rewrite conversation into store

agentsarxiv-cs-ai

MESA: Prioritizing Vulnerable Communication Channels for Securing Multi-Agent Systems

arXiv:2606.30602v1 Announce Type: cross Abstract: Multi-agent systems (MAS) are increasingly used to automate complex, distributed workflows. However, their inter-agent communication channels introduc

ML-Powered LDAP Reconnaissance Detection using Weak Supervision

arXiv:2606.28917v1 Announce Type: new Abstract: Lightweight Directory Access Protocol (LDAP) is a protocol that allows users to query and modify Active Directory (AD) data. By default, all users have

MOPD: Multi-Teacher On-Policy Distillation for Capability Integration in LLM Post-Training

arXiv:2606.30406v1 Announce Type: new Abstract: Modern large language models (LLMs) rely on reinforcement learning during post-training to push specific capabilities, yet integrating multiple capabili

safetyarxiv-cs-cl

Multi-Agent DRL for QoS and Energy Optimization in RIS-Enabled Open-RAN Industrial 6G TN/NTN Networks

arXiv:2606.28339v1 Announce Type: cross Abstract: Industrial 6G networks require ultra-reliable, low-latency, and energy-efficient connectivity in dynamic and blockage-prone environments, where conven

agentsarxiv-cs-ai

Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models

arXiv:2603.18907v2 Announce Type: replace Abstract: We propose a new Neural Galerkin Normalizing Flow framework to approximate the transition probability density function of a diffusion process by sol

Neural Gate: Mitigating Privacy Risks in LVLMs via Neuron-Level Gradient Gating

arXiv:2603.12598v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) have shown remarkable potential across a wide array of vision-language tasks, leading to their adoption in crit

local-aiarxiv-cs-cv

OGM-CBF: Occupancy Grid Map-based Control Barrier Function for Safe Mobile Robot Control with Memory of out of View Obstacles

arXiv:2405.10703v4 Announce Type: replace Abstract: Safe control in unknown environments is a key challenge in mobile robotics. Control Barrier Functions (CBFs) provide a principled framework for guar

safetyarxiv-cs-ro

On Test-Time Scaling for Vision-Language Models

arXiv:2606.28864v1 Announce Type: new Abstract: Test-time scaling is a paradigm where large models use additional compute at inference to achieve better performance, without changing model weights. Wh

researcharxiv-cs-cv

Operating Regimes of Decentralized Learning Under Mobility and Bandwidth Constraints

arXiv:2606.28342v1 Announce Type: cross Abstract: Decentralized learning is a promising paradigm for collaborative training in mobile and pervasive systems, as it avoids a central coordinator and does

researcharxiv-cs-ai

Parametric Skills

arXiv:2606.30015v1 Announce Type: new Abstract: Since intelligence fundamentally relies on efficient skill acquisition (Chollet, 2019), the ability to leverage skills is critical. For LLMs, skills, ma