Search: “deployment”

Merlin's Whisper: Enabling Efficient Reasoning in Large Language Models via Black-box Persuasive Prompting

arXiv:2510.10528v3 Announce Type: replace Abstract: Large reasoning models (LRMs) have demonstrated remarkable proficiency in tackling complex tasks through step-by-step thinking. However, this length

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Multi-Mode Quantum Annealing for Generative Representation Learning with Boltzmann Priors

DGX agent

arXiv:2604.00919v2 Announce Type: replace-cross Abstract: Energy-based models provide a natural bridge between statistical physics and machine learning by representing data through structured energy l

researcharxiv-cs-lg

19 May 2026

Multi-Paradigm Agent Interaction in Practice:A Systematic Analysis of Generator-Evaluator, ReAct Loop,and Adversarial Evaluation in the buddyMe Framework

arXiv:2605.16821v1 Announce Type: new Abstract: The rapid evolution of Large Language Model (LLM) agents has produced diverse interaction paradigms, yet few production systems integrate multiple parad

NanoQuant: Efficient Sub-1-Bit Quantization of Large Language Models

arXiv:2602.06694v2 Announce Type: replace Abstract: Weight-only quantization has become a standard approach for efficiently serving large language models (LLMs). However, existing methods fail to effi

hardwarearxiv-cs-lg

Offline Contextual Bandits in the Presence of New Actions

model-releasesarxiv-cs-lg

arXiv:2605.18509v1 Announce Type: new Abstract: Automated decision-making algorithms drive applications such as recommendation systems and search engines. These algorithms often rely on off-policy con

On-Device Interpretable Tsetlin Machine-Based Intrusion Detection for Secure IoMT

arXiv:2605.16707v1 Announce Type: cross Abstract: The rapid evolution of digital health technologies is redefining healthcare services worldwide. The integration of wireless communication and Internet

local-aiarxiv-cs-lg

On Improving Multimodal Pedestrian Trajectory Prediction with CVAE: A Study on Benchmark and Robot Data

model-releasesarxiv-cs-ro

arXiv:2605.18262v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction is crucial for autonomous systems operating in complex environments, such as modular buses and delivery robots

On the Adversarial Robustness of Large Vision-Language Models under Visual Token Compression

arXiv:2601.21531v2 Announce Type: replace-cross Abstract: Visual token compression is widely used to accelerate large vision-language models (LVLMs) by pruning or merging visual tokens, yet its advers

Optimising CSRNet with parameter-free attention mechanisms for crowd counting in public transport

arXiv:2605.18349v1 Announce Type: cross Abstract: Occupancy estimation and crowd counting are critical tasks in designing smart and efficient public transport vehicles. Given that public transport loa

OxyGen: Unified KV Cache Management for VLA Inference under Multi-Task Parallelism

arXiv:2603.14371v2 Announce Type: replace-cross Abstract: Embodied AI agents increasingly require parallel execution of multiple tasks, such as manipulation, conversation, and memory construction, fro

PARALLAX: Separating Genuine Hallucination Detection from Benchmark Construction Artifacts

arXiv:2605.17028v1 Announce Type: cross Abstract: Large language models (LLMs) hallucinate with confidence: their outputs can be fluent, authoritative, and simply wrong. In medical, legal, and scienti

Progressive Generalization Augmentation with Deeply Coupled RND-PPO and Domain-Prioritized Noise Injection for Robust Crop Management Reinforcement Learning

arXiv:2605.17428v1 Announce Type: cross Abstract: Our preliminary experiments on gym-DSSAT maize irrigation tasks revealed that +/-2 degrees C temperature noise causes an 11.9% reduction in economic r

hardwarearxiv-cs-ai

Prompts Don't Protect: Architectural Enforcement via MCP Proxy for LLM Tool Access Control

arXiv:2605.18414v1 Announce Type: cross Abstract: Large language models increasingly operate as autonomous agents that select and invoke tools from large registries. We identify a critical gap: when u

Proof-Carrying Certificates for LLM Pipelines: A Trust-Boundary Architecture

arXiv:2605.16407v1 Announce Type: cross Abstract: We present a framework for verifying the deterministic structured computations surrounding a large language model rather than the model itself, extend

agentsarxiv-cs-cl

Q-LocalAdam: Memory-Efficient Client-Side Adaptive Optimization for Edge Federated Learning

arXiv:2605.17552v1 Announce Type: new Abstract: Federated learning on edge devices must cope with non-IID client data and tight memory budgets. Adaptive optimizers like Adam stabilize training under d

local-aiarxiv-cs-lg

RAGA: Reading-And-Graph-building-Agent for Autonomous Knowledge Graph Construction and Retrieval-Augmented Generation

arXiv:2605.17072v1 Announce Type: new Abstract: Existing LLM-driven knowledge graph (KG) construction methods predominantly employ stateless batch processing pipelines, exhibiting structural deficienc

RAP: Runtime Adaptive Pruning for LLM Inference

arXiv:2505.17138v5 Announce Type: replace-cross Abstract: Large language models (LLMs) excel at language understanding and generation, but their enormous computational and memory requirements hinder d

Rapid Vibration Suppression and Trajectory Tracking of a Serial Manipulator with Multi-Flexible Links

arXiv:2605.17477v1 Announce Type: new Abstract: Flexible robotic manipulators (FRMs) offer advantages in lightweight design and large workspace, but their structural flexibility induces vibrations, ac

researcharxiv-cs-ro

RAPT: Retrieval-Augmented Post-hoc Thresholding for Multi-Label Classification

arXiv:2605.16535v1 Announce Type: cross Abstract: Industrial multi-label document understanding pipelines score candidate labels and threshold or rank them to form a label set per document. This early

Responsible Federated LLMs via Safety Filtering and Constitutional AI

arXiv:2502.16691v2 Announce Type: replace Abstract: Recent research has increasingly focused on training large language models (LLMs) using federated learning, known as FedLLM. However, responsible AI

safetyarxiv-cs-cl

Retrieval-Based Multi-Label Legal Annotation: Extensible, Data-Efficient and Hallucination-Free

arXiv:2605.16767v1 Announce Type: new Abstract: Multi-label legal annotation requires assigning multiple labels from large, evolving taxonomies to long, fact-intensive documents, often under limited s

RGB-only Active 3D Scene Graph Generation for Indoor Mobile Robots

arXiv:2605.18197v1 Announce Type: cross Abstract: Current approaches to 3D scene graph generation rely on dedicated depth sensors, such as LiDAR or RGB-D cameras, for metric 3D reconstruction. This li

researcharxiv-cs-ai

SAFE-SVD: Sensitivity-Aware Fidelity-Enforcing SVD for Physics Foundation Models

arXiv:2605.17985v1 Announce Type: cross Abstract: We propose a new method for compressing physics foundation models (PFMs) which is a new trend in AI for Science. While model compression is essential

researcharxiv-cs-ai

SafeLens: Deliberate and Efficient Video Guardrails with Fast-and-Slow Screening

arXiv:2605.17610v1 Announce Type: cross Abstract: The rapid growth of online video platforms and AI-generated content has made reliable video guardrails a key challenge for safety and real-world deplo

SAME: A Semantically-Aligned Music Autoencoder

arXiv:2605.18613v1 Announce Type: cross Abstract: Latent representations are at the heart of the majority of modern generative models. In the audio domain they are typically produced by a neural-audio

SAMRI: Segment Any MRI

arXiv:2510.26635v3 Announce Type: replace-cross Abstract: Summary: SAMRI is an MRI-specialized adaptation of the Segment Anything Model achieving superior whole-body MRI segmentation, particularly for

local-aiarxiv-cs-cv

Scheduling That Speaks: An Interpretable Programmatic Reinforcement Learning Framework

arXiv:2605.18454v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) has recently emerged as a promising approach to solve combinatorial optimization problems such as job shop schedulin

SGSoft: Learning Fused Semantic-Geometric Features for 3D Shape Correspondence via Template-Guided Soft Signals

arXiv:2605.18039v1 Announce Type: new Abstract: Learning dense correspondences across deformable 3D shapes remains a long-standing challenge due to structural variability, non-isometric deformation, a

safetyarxiv-cs-cv

SLEIGHT-Bench: A Benchmark of Evasion Attacks Against Agent Monitors

arXiv:2605.16626v1 Announce Type: cross Abstract: Since autonomous coding agents generate complex behaviors at high-volume, we may want to use other LLMs to monitor actions to reduce the risk from dan

Some[Body] Must Receive That Pain for Agent Accountability

arXiv:2605.16872v1 Announce Type: cross Abstract: AI agents increasingly act consequentially in the real world. This creates a problem we call consequence reception: harm occurs, the producing system

Spatially Aware Linear Transformer (SAL-T) for Particle Jet Tagging

arXiv:2510.23641v2 Announce Type: replace-cross Abstract: Transformers are very effective in capturing both global and local correlations within high-energy particle collisions, but they present deplo

State Contamination in Memory-Augmented LLM Agents

arXiv:2605.16746v1 Announce Type: new Abstract: LLM agents increasingly rely on persistent state, including transcripts, summaries, retrieved context, and memory buffers, to support long-horizon inter

Stop rogue AI: How Unity Catalog secures your agent actions

Unity Catalog is a Databricks governance solution that helps secure AI agent actions by managing access controls and permissions across agent operations. It prevents unauthorized or 'rogue' AI behavio

agentsdatabricks

StreamingEffect: Real-Time Human-Centric Video Effect Generation

arXiv:2605.17019v1 Announce Type: new Abstract: Streaming video effect generation is highly desirable for live human-centric applications such as e-commerce streaming, entertainment, and vlogging, yet

hardwarearxiv-cs-cv

Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving

arXiv:2506.05442v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) offer a promising approach to end-to-end autonomous driving due to their human-like reasoning capabilities. Howe

Supervising the search process produces reliable and generalizable information-seeking agents

arXiv:2502.13957v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are transforming web search by shifting from document ranking to synthesizing answers, and are increasingly deplo

Sustainable Intelligence for the Wild: Democratizing Ecological Monitoring via Knowledge-Adaptive Edge Expert Agents

arXiv:2605.16671v1 Announce Type: new Abstract: Rapid biodiversity loss underscore the urgency of effective monitoring, yet manual surveys remain resource-intensive. While on-device AI offers a scalab

Systematic Evaluation of Vision Transformers for Automated Cervical Cancer Classification: Optimization, Statistical Validation, and Clinical Interpretability

arXiv:2605.17236v1 Announce Type: cross Abstract: Manual Pap smear analysis for cervical cancer screening is limited by inter-observer variability, time constraints, and restricted expert availability

researcharxiv-cs-ai

TAME: Test-Time Adversarial Prompt Tuning via Mixture-of-Experts for Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.17577v1 Announce Type: new Abstract: Large-scale pre-trained Vision-Language models (VLMs), such as CLIP, exhibit strong zero-shot generalization, yet remain highly vulnerable to impercepti

Task-Level AI Readiness Assessment for Business Process Management:The T-IPO Model and LARA Matrix in Financial-Services IT Operations

arXiv:2605.16297v1 Announce Type: cross Abstract: Which tasks inside an enterprise workflow can a large-language-model agent reliably handle, and under what conditions? Most business process modeling

TeleRAG: Efficient Retrieval-Augmented Generation Inference with Lookahead Retrieval

arXiv:2502.20969v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) extends large language models (LLMs) with external data sources to enhance factual correctness and domain

hardwarearxiv-cs-lg

The End of Trust: How Agentic AI Breaks Security Assumptions

arXiv:2605.16436v1 Announce Type: cross Abstract: For decades, the security of digital interaction has rested on an unacknowledged economic constraint. Attackers faced a tradeoff between the fidelity

The future of agentic development: Redefining the data practitioner lifecycle with Data Agent Kit

model-releasesgoogle-cloud-ai

The modern software development landscape isn’t happening just on one surface — it’s happening across an entire ecosystem of agentic tools. Agents are being developed at an unprecedented scale, and th

Token-Space Mask Prediction for Efficient Vision Transformer Segmentation

arXiv:2605.18177v1 Announce Type: new Abstract: Query-based Vision Transformer segmentation models typically reconstruct dense spatial feature maps to predict masks, inheriting design patterns from co

hardwarearxiv-cs-cv

Towards Sustainable Growth: A Multi-Value-Aware Retrieval Framework for E-Commerce Search

arXiv:2605.17994v1 Announce Type: cross Abstract: New item growth is critical for maintaining a healthy ecosystem in large-scale e-commerce platforms. However, existing systems tend to prioritize pres

Towards Universal Physical Adversarial Attacks via a Joint Multi-Objective and Multi-Model Optimization Framework

arXiv:2605.17772v1 Announce Type: new Abstract: Physical adversarial attacks often overfit single surrogate models and optimization objectives. While ensemble attacks can mitigate this, existing metho

safetyarxiv-cs-cv

Trust No Tool: Evaluating and Defending LLM Agents under Untrusted Tool Feedback

arXiv:2605.17453v1 Announce Type: cross Abstract: Tool-using LLM agents increasingly rely on external tools to make consequential decisions, yet most existing agent-security benchmarks and defenses im

Unleashing the Potential of Diffusion Models for End-to-End Autonomous Driving

arXiv:2602.22801v2 Announce Type: replace-cross Abstract: Diffusion models have become a popular choice for decision-making tasks in robotics, and more recently, are also being considered for solving