Search: “deployment”

Reliable LLM-Based Edge-Cloud-Expert Cascades for Telecom Knowledge Systems

model-releasesarxiv-cs-lg

arXiv:2512.20012v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are emerging as key enablers of automation in domains such as telecommunications, assisting with tasks including

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Safety

RePO-VLA: Recovery-Driven Policy Optimization for Vision-Language-Action Models

DGX agent

arXiv:2605.09410v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models remain brittle in long-horizon, contact-rich manipulation because success-only imitation provides little supervisi

safetyarxiv-cs-ai

12 May 2026

Resource-Aware Evolutionary Neural Architecture Search for Cardiac MRI Segmentation

arXiv:2605.08238v1 Announce Type: cross Abstract: Cardiac magnetic resonance (CMR) segmentation underpins quantitative assessment of ventricular structure and function, yet reliable delineation remain

Applications

Rethinking Evaluation of Multiple Sclerosis (MS) Lesion Segmentation Models

arXiv:2605.09666v1 Announce Type: cross Abstract: Multiple Sclerosis (MS) is a chronic autoimmune disease that can significantly reduce the quality of life of a patient. Existing treatment options can

applicationsarxiv-cs-ai

Rethinking Random Transformers as Adaptive Sequence Smoothers for Sleep Staging

arXiv:2605.09905v1 Announce Type: cross Abstract: Automatic sleep staging commonly adopts Transformers under the assumption that they learn complex long-range dependencies. We challenge this view by r

Reward-Conditioned Reinforcement Learning

arXiv:2603.05066v2 Announce Type: replace Abstract: Single-task RL agents are typically trained under a fixed reward function, which limits their robustness to reward misspecification and their abilit

Applications

RIR-Former: Coordinate-Guided Transformer for Continuous Reconstruction of Room Impulse Responses

arXiv:2602.01861v3 Announce Type: replace-cross Abstract: Room impulse responses (RIRs) are essential for many acoustic signal processing tasks, yet measuring them densely across space is often imprac

applicationsarxiv-cs-lg

Robust Building Damage Detection in Cross-Disaster Settings Using Domain Adaptation

arXiv:2603.14694v2 Announce Type: replace-cross Abstract: Rapid structural damage assessment from remote sensing imagery is essential for timely disaster response. Within human-machine systems (HMS) f

Route Before Retrieve: Activating Latent Routing Abilities of LLMs for RAG vs. Long-Context Selection

arXiv:2605.10235v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have expanded the context window to beyond 128K tokens, enabling long-document understanding and multi-s

SAFA-SNN: Sparsity-Aware On-Device Few-Shot Class-Incremental Learning with Fast-Adaptive Structure of Spiking Neural Network

model-releasesarxiv-cs-lg

arXiv:2510.03648v2 Announce Type: replace Abstract: Continuous learning of novel classes is crucial for edge devices to preserve data privacy and maintain reliable performance in dynamic environments.

SAID: Safety-Aware Intent Defense via Prefix Probing for Large Language Models

arXiv:2510.20129v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) remain vulnerable to jailbreak attacks, where adversarially crafted prompts induce policy-violating responses des

Scaling Vision Models Does Not Consistently Improve Localisation-Based Explanation Quality

arXiv:2605.10142v1 Announce Type: cross Abstract: Artificial intelligence models are increasingly scaled to improve predictive accuracy, yet it remains unclear whether scale improves the quality of po

Agents

ScholarPeer: A Context-Aware Multi-Agent Framework for Automated Peer Review

arXiv:2601.22638v2 Announce Type: replace-cross Abstract: The exponential growth of machine learning submissions has strained the traditional peer review process, resulting in slow feedback loops for

agentsarxiv-cs-ai

Seed Hijacking of LLM Sampling and Quantum Random Number Defense

arXiv:2605.08313v1 Announce Type: cross Abstract: Large language models (LLMs) rely on deterministic pseudorandom number generators (PRNGs) for autoregressive sampling, creating a critical supply-chai

Selective Deficits in LLM Mental Self-Modeling in a Behavior-Based Test of Theory of Mind

arXiv:2603.26089v2 Announce Type: replace-cross Abstract: The ability to represent oneself and others as agents with knowledge, intentions, and belief states that guide their behavior - Theory of Mind

Agents

SimWorld Studio: Automatic Environment Generation with Evolving Coding Agent for Embodied Agent Learning

arXiv:2605.09423v1 Announce Type: new Abstract: LLM/VLM-based digital agents have advanced rapidly thanks to scalable sandboxes for coding, web navigation, and computer use, which provide rich interac

agentsarxiv-cs-ai

Sketch-and-Verify: Structured Inference-Time Scaling via Program Sketching

arXiv:2605.08658v1 Announce Type: cross Abstract: SKETCHVERIFY is a within-tier cost-performance policy, not a universal accuracy improvement. The operational question: a practitioner stuck with a sma

Agents

SoK: A Systematic Bidirectional Literature Review of AI & DLT Convergence

arXiv:2605.10515v1 Announce Type: cross Abstract: The integration of Artificial Intelligence (AI) with Distributed Ledger Technology (DLT) has become a growing research area, yet contributions tend to

agentsarxiv-cs-ai

Stable Long-Horizon PDE Forecasting via Latent Structured Spectral Propagators

arXiv:2605.10154v1 Announce Type: new Abstract: Long-horizon forecasting of time-dependent partial differential equations (PDEs) is critical for characterizing the sustained evolution of physical syst

Steerable but Not Decodable: Function Vectors Operate Beyond the Logit Lens

model-releasesarxiv-cs-lg

arXiv:2604.02608v2 Announce Type: replace Abstract: Activation steering presupposes that task-relevant behaviors correspond to linear directions in activation space -- directions that should both stee

Supervised Mixture-of-Experts for Surgical Grasping and Retraction

arXiv:2601.21971v2 Announce Type: replace-cross Abstract: Imitation learning has achieved remarkable success in robotic manipulation, yet its application to surgical robotics remains challenging due t

Survey-aware Machine Learning: A Guideline for Valid Population Health Inference based on Scoping Review

arXiv:2605.08963v1 Announce Type: cross Abstract: Machine Learning (ML) models trained on complex health surveys such as the National Health and Nutrition Examination Survey (NHANES) often ignore prim

Survey on Disaster Management Datasets for Remote Sensing Based Emergency Applications

arXiv:2605.08196v1 Announce Type: new Abstract: Recent natural disasters have highlighted the urgent need for efficient data-driven approaches to disaster management. Machine learning (ML) and deep le

researcharxiv-cs-cv

TAD: Temporal-Aware Trajectory Self-Distillation for Fast and Accurate Diffusion LLM

arXiv:2605.09536v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a promising paradigm for parallel text generation, but in practice they face an accuracy-parallelism tra

TELL-TALE: Task Efficient LLMs with Task Aware Layer Elimination

arXiv:2510.22767v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) typically come with a fixed architecture, despite growing evidence that not all layers contribute equally to ever

researcharxiv-cs-cl

The DSA's Blind Spot: Algorithmic Audit of Advertising and Minor Profiling on TikTok

arXiv:2603.05653v2 Announce Type: replace-cross Abstract: Adolescents spend an increasing amount of their time in digital environments where their still-developing cognitive capacities leave them unab

The Realignment Problem: When Right becomes Wrong in LLMs

arXiv:2511.02623v2 Announce Type: replace Abstract: Post-training alignment of large language models (LLMs) relies on large-scale human annotations guided by policy specifications that change over tim

The Trap of Trajectory: Towards Understanding and Mitigating Spurious Correlations in Agentic Memory

arXiv:2605.09330v1 Announce Type: cross Abstract: Agentic memory enables LLMs to persist information beyond a single context window and reuse it in later decisions, but it also introduces a new vulner

TileQ: Efficient Low-Rank Quantization of Mixture-of-Experts with 2D Tiling

arXiv:2605.09281v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models achieve remarkable performance by sparsely activating specialized experts, yet their massive parameters in experts pose

researcharxiv-cs-lg

TinySSL: Distilled Self-Supervised Pretraining for Sub-Megabyte MCU Models

arXiv:2605.08241v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has transformed representation learning for large models, yet remains unexplored for microcontroller (MCU)-class models

To Redact, or not to Redact? A Local LLM Approach to Deliberative Process Privilege Classification

arXiv:2605.10211v1 Announce Type: cross Abstract: Government transparency laws, like the Freedom of Information (FOIA) acts in the United States and United Kingdom, and the Woo (Open Government Act) i

TopoGeoScore: A Self-Supervised Source-Only Geometric Framework for OOD Checkpoint Selection

arXiv:2605.08870v1 Announce Type: new Abstract: Out-of-distribution (OOD) robustness is difficult to diagnose when target-domain labels are unavailable. We consider a more restrictive source-only vari

researcharxiv-cs-lg

Toward Reliable Sim-to-Real Predictability for MoE-based Robust Quadrupedal Locomotion

arXiv:2602.00678v4 Announce Type: replace Abstract: Reinforcement learning has shown strong promise for quadrupedal agile locomotion, even with proprioception-only sensing. In practice, however, sim-t

safetyarxiv-cs-ro

Towards Backdoor-Based Ownership Verification for Vision-Language-Action Models

arXiv:2605.09005v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) support generalist robotic control by enabling end-to-end decision policies directly from multi-modal inputs. As

Towards Compact Sign Language Translation: Frame Rate and Model Size Trade-offs

arXiv:2605.09554v1 Announce Type: new Abstract: Sign Language Translation (SLT) converts sign language videos into spoken-language text, bridging communication between Deaf and hearing communities. Cu

Towards Generative Predictive Display for Vision-Based Teleoperation: A Zero-Shot Benchmark of Off-the-Shelf Video Models

model-releasesarxiv-cs-cv

arXiv:2605.09670v1 Announce Type: cross Abstract: Teleoperation systems are fundamentally limited by communication latency, which degrades situational awareness and control performance. Predictive dis

Two Ways to De-Bias an LLM-as-a-Judge: A Continuous-Score Comparison of Hierarchical Bayesian Calibration and Neural-ODE Score Transport

arXiv:2605.09227v1 Announce Type: new Abstract: [Abridged] Using a Large Language Model (LLM) as an automatic rater (LLM-as-a-judge) is cheap but potentially biased: some judges run lenient, others st

Upholding Epistemic Agency: A Brouwerian Assertibility Constraint for Responsible AI

arXiv:2603.03971v2 Announce Type: replace-cross Abstract: Generative AI can convert uncertainty into hypersuasive, authoritative-seeming verdicts, displacing the justificatory work on which democratic

Verification Mirage: Mapping the Reliability Boundary of Self-Verification in Medical VQA

arXiv:2605.10850v1 Announce Type: new Abstract: Self-verification, re-invoking the same vision language model (VLM) in a fresh context to check its own generated answer, is increasingly used as a defa

safetyarxiv-cs-cv

When (and How) to Trust the Expert: Diagnosing Query-Time Expert-Guided Reinforcement Learning

arXiv:2605.09109v1 Announce Type: new Abstract: Many continuous-control problems ship with a competent but suboptimal controller (a tuned PID, a hand-designed gait). A growing family of methods uses s

When More Parameters Hurt: Foundation Model Priors Amplify Worst-Client Disparity Under Extreme Federated Heterogeneity

arXiv:2605.08992v1 Announce Type: new Abstract: Federated learning (FL) is increasingly used to fine-tune foundation models (FMs) on distributed private data. The community largely assumes that large-

When Prompts Become Payloads: A Framework for Mitigating SQL Injection Attacks in Large Language Model-Driven Applications

arXiv:2605.10176v1 Announce Type: cross Abstract: Natural language interfaces to structured databases are becoming increasingly common, largely due to advances in large language models (LLMs) that ena

When Reviews Disagree: Fine-Grained Contradiction Analysis in Scientific Peer Reviews

arXiv:2605.10171v1 Announce Type: cross Abstract: Scientific peer reviews frequently contain conflicting expert judgments, and the increasing scale of conference submissions makes it challenging for A

WildClawBench: A Benchmark for Real-World, Long-Horizon Agent Evaluation

arXiv:2605.10912v1 Announce Type: new Abstract: Large language and vision-language models increasingly power agents that act on a user's behalf through command-line interface (CLI) harnesses. However,

WindINR: Latent-State INR for Fast Local Wind Query and Correction in Complex Terrain

arXiv:2605.09511v1 Announce Type: new Abstract: Many downstream decisions in complex terrain require fast wind estimates at a small number of user-specified locations and heights for a given forecast

A Flexible Adaptive Stable Clustering Algorithm for Archive-Scale Online Mass Spectrometry

arXiv:2605.07424v1 Announce Type: new Abstract: Modern online mass spectrometry generates multi-terabyte data streams critical for understanding Earth's environmental systems. However, extracting acti

researcharxiv-cs-lg

11 May 2026

A Marine Debris Detection Framework for Ocean Robots via Self-Attention Enhancement and Feature Interaction Optimization

model-releasesarxiv-cs-cv

arXiv:2605.07388v1 Announce Type: new Abstract: Marine debris detection for ocean robot is crucial for ecological protection, yet performance is often degraded by low-quality images with blur, complex

11 May 2026

A Systematic Investigation of The RL-Jailbreaker in LLMs

arXiv:2605.07032v1 Announce Type: cross Abstract: The evolution of generative models from next-token predictors to autonomous engines of complex systems necessitates rigorous safety hardening. Adversa