Search: “deployment”

When Personality Meets Quantization: A Layer-wise MBTI Analysis of Quantized LLMs

arXiv:2608.25977v1 Announce Type: new Abstract: Personality is increasingly important in large language models (LLMs), as it shapes users' trust, engagement, and emotional experiences. While the Myers

researcharxiv-cs-cl

27 Aug 2026

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

ADVERSA: Measuring Multi-Turn Guardrail Degradation and Judge Reliability in Large Language Models

DGX agent

arXiv:2603.10068v2 Announce Type: replace-cross Abstract: Most adversarial evaluations of large language model (LLM) safety assess single prompts and report binary pass/fail outcomes, which fails to c

model-releasesarxiv-cs-ai

26 Aug 2026

Causal Analysis for Time Series Foundation Models

arXiv:2608.24303v1 Announce Type: new Abstract: Transitioning from bespoke time series models towards time series foundation models changes the relationship of model and application from one-to-one to

CoDrift: Compositional Drifting for Offline Reinforcement Learning

arXiv:2608.23939v1 Announce Type: new Abstract: Offline reinforcement learning is intrinsically multi-objective: a policy must remain compatible with the behavioral support of a fixed dataset while pr

Constrained Hyperparameter Optimization for Streaming Data

arXiv:2608.24712v1 Announce Type: cross Abstract: Optimization of hyperparameters is a critical factor to obtain optimal model performance. While existing research has predominantly concentrated on ba

Data Leakage Inflates Generalizability of Power Outage Prediction Models

arXiv:2608.24665v1 Announce Type: new Abstract: Power outage prediction models are increasingly used in assessments of climate-driven infrastructure risk, yet current evaluation practices obscure whet

applicationsarxiv-cs-lg

Design-to-Plan: A Large Language Model-Based Multi-Agent Framework for Manufacturing Process Planning from 3D CAD Models and 2D Engineering Drawings

arXiv:2608.24039v1 Announce Type: cross Abstract: Manufacturing process planning transforms heterogeneous design information into coherent manufacturing decisions. However, existing approaches focus o

Eluna: An Agentic LLM System for Automating Warehouse Operations with Reasoning and Task Execution

arXiv:2607.08960v2 Announce Type: replace-cross Abstract: Warehouse operations are governed by Standard Operating Procedures (SOPs) that encode complex, multi-system decision logic, which must be exec

Example-based Robust Abnormality Detection with Minimal Annotations using Exemplar Med-DETR

arXiv:2608.24281v1 Announce Type: new Abstract: Reducing annotation requirements remains a key challenge in developing robust medical object detectors. To address this, Vision-Language (VL) object det

researcharxiv-cs-cv

(ext{DNN})^2: Doubly Non-Negative Relaxations for Deep Neural Networks

arXiv:2608.24743v1 Announce Type: new Abstract: Existing linear program (LP) and semidefinite program (SDP) relaxations for rectified linear unit (ReLU) neural network (NN) verification yield overly-c

Local Ai

Finite-Sample Metric Non-Collapse for Geometrically Supervised Latent World Models in Control

arXiv:2608.07265v2 Announce Type: cross Abstract: We establish a finite-sample learning-to-control theory for geometrically supervised latent models of nonlinear deterministic systems. Geometric super

local-aiarxiv-cs-lg

FLARE: A Systematic, Uncertainty-Aware Framework for Evidence-Based Adoption of Artificial Intelligence in Healthcare

arXiv:2608.23643v1 Announce Type: new Abstract: Artificial intelligence is increasingly being introduced into healthcare workflows, yet most evaluations emphasize model accuracy rather than whether ad

applicationsarxiv-cs-ai

FraudBench: Protocol-Sensitive Benchmarking of Adversarial Robustness for Financial Risk Assessment

arXiv:2608.24551v1 Announce Type: cross Abstract: Machine learning models are widely used in financial fraud and credit-risk detection, yet their adversarial robustness remains difficult to evaluate b

Local Ai

GaussianWAM: Distilling Geometry and Semantics from 3D Gaussian Fields into World-Action Models

arXiv:2608.24714v1 Announce Type: new Abstract: World-Action Models (WAMs) jointly learn future visual prediction and action generation, using video dynamics as a representation-learning signal for ro

local-aiarxiv-cs-ro

Highway Congestion Reduction through Reinforcement Learning Based Eulerian Headway Control

arXiv:2412.02520v4 Announce Type: replace-cross Abstract: Connected automated vehicles (CAVs) equipped with adaptive cruise control (ACC) create new opportunities for highway congestion mitigation. Tr

Holographic Invariant Storage: Design-Time Safety Contracts via Vector Symbolic Architectures

arXiv:2603.13558v2 Announce Type: replace-cross Abstract: We introduce Holographic Invariant Storage (HIS), a protocol that assembles known properties of bipolar Vector Symbolic Architectures into a d

Is the Hard-Label Cryptanalytic Model Extraction Really Polynomial?

arXiv:2510.06692v3 Announce Type: replace Abstract: Deep Neural Networks (DNNs) have attracted significant attention, and their internal models are now considered valuable intellectual assets. Extract

researcharxiv-cs-lg

Knowing When to Ask for Help: Bayesian Self-Escalation in Hierarchical LLM Agents

arXiv:2608.24087v1 Announce Type: cross Abstract: Current LLM agent systems decide delegation before reasoning begins (a router picks a model) or after a response is complete (a verifier scores it and

safetyarxiv-cs-ai

LG-GER: Language-Guided Group Emotion Recognition via Multimodal Evidence Distillation

model-releasesarxiv-cs-cv

arXiv:2608.23880v1 Announce Type: new Abstract: Inferring the collective emotional state of a group of people from a single image, a task known as group emotion recognition (GER), requires integrating

MaST: Motion-aware Sparse Pipeline for Lightweight Object Tracking

arXiv:2608.24365v1 Announce Type: new Abstract: Transformer-based object trackers are renowned for their strong performance, yet dense token processing often leads to prohibitive computational cost, l

researcharxiv-cs-cv

Mind the Student: Behavioral and Contextual Cues for Automated Engagement Prediction in Online Learning

arXiv:2608.24340v1 Announce Type: cross Abstract: The prediction of student engagement from the online tutoring videos is difficult because engagement is a multidimensional construct comprising distin

Hardware

Minima-KV: Retention-Preserving KV Cache Compression with Mixed-Format Paged Attention

arXiv:2608.23834v1 Announce Type: new Abstract: The key-value (KV) cache is a primary capacity and bandwidth bottleneck in long-context LLM serving. We present Minima-KV, a retention-preserving hierar

hardwarearxiv-cs-ai

More Rejective, Not More Discriminative: The Unit of Verification in Pre-Execution LLM Oversight

arXiv:2608.23941v1 Announce Type: new Abstract: Pre-execution oversight is core to trusted monitoring in AI control: a fallible LLM monitor vets planned actions before irreversible execution. Over-blo

safetyarxiv-cs-ai

MoRF-AST: Calibrated Probabilistic Virtual Sensing for Structural Monitoring under Changing Operating Conditions

arXiv:2608.24531v1 Announce Type: cross Abstract: Probabilistic full-field reconstruction provides uncertainty-aware response evidence for structural reliability assessment, yet inference from sparse

NeuronGuard: Robust LLM Safety Alignment via Ablation-Aware Safety Signal Redistribution

arXiv:2608.23959v1 Announce Type: cross Abstract: Safety alignment in large language models (LLMs) remains brittle against a growing spectrum of attacks. Jailbreak attacks bypass safety mechanisms thr

safetyarxiv-cs-ai

Neurosymbolic Alignment for Physiologically-Safe Clinical Language Models

arXiv:2608.24534v1 Announce Type: new Abstract: Clinical LLMs can generate recommendations that are factually plausible yet physiologically unsafe. We investigate whether safety alignment can be impro

NVIDIA Cosmos-H-Dreams: Real-Time Generative Physics Simulation for Surgical Robotics

arXiv:2608.24199v1 Announce Type: new Abstract: Generative simulation for surgical robotics still lacks real-time interaction. Physical-robot experiments, often involving animal or cadaver labs, are t

safetyarxiv-cs-ro

Parameter-Efficient Self-Supervised Adaptation for EEG-FM under Fixed Computational Budgets

arXiv:2608.24727v1 Announce Type: cross Abstract: EEG foundation models pretrained via self-supervised learning promise transferable representations, but their generalization remains limited, especial

Place, Slice and Schedule: Hierarchical O-RAN Control of a Tethered mmWave UAV-gNB

arXiv:2608.23824v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV)-mounted 5G New Radio base stations (gNBs) can augment terrestrial networks with an on-demand, repositionable Frequency R

Agents

Poisoning Agentic Alpha: Adversarial Vulnerabilities Across Roles and Architectures in Multi-Agent Trading Systems

arXiv:2608.24069v1 Announce Type: new Abstract: LLM-based multi-agent trading systems, in which specialized agents collaborate through structured communication to produce trading decisions, are moving

agentsarxiv-cs-ai

RENDER: Controlling Reader-Facing Evidence in LLM Memory Evaluation

arXiv:2608.23568v1 Announce Type: new Abstract: Memory and RAG evaluations often treat the answering model's input as an implementation detail, even though systems may render the same history as a mem

Restoring Without Forgetting: Continual Learning Across Image Degradations

arXiv:2608.23799v1 Announce Type: cross Abstract: Recent progress in image restoration has converged on all-in-one architectures that jointly handle multiple degradations within a single network. Thes

Robust Data-Collection Policy Learning for Low-Variance Online Policy Evaluation

arXiv:2608.24146v1 Announce Type: new Abstract: In reinforcement learning policy evaluation, classic on-policy methods often suffer from high variance when estimating policy performance. To mitigate t

SeisMamba: Low-Latency Single-Station Seismic Magnitude Estimation for Spatially Distributed Earthquake Early Warning

arXiv:2608.24561v1 Announce Type: new Abstract: Rapid earthquake magnitude estimation is central to earthquake early warning, yet many operational systems depend on dense regional seismic networks and

Hardware

ShardMeter: Sharded and Geo-Distributed Training Without the Guesswork

arXiv:2608.23840v1 Announce Type: cross Abstract: Training large-scale AI models often outgrows a single data center, demanding sharded, multi-cluster, and decentralized training. However, the huge sp

hardwarearxiv-cs-ai

The Empire, Long Divided, Must Unite: Architectural Convergence in Three LLM Agent Harnesses

arXiv:2608.23953v1 Announce Type: cross Abstract: An agent harness is what turns a language model into an autonomous agent: the surrounding code that builds the model's context, mediates its tools, ru

Agents

TrustShiftProbe: Characterizing, Benchmarking, and Defending Staged Trust Attacks on MCP Servers

arXiv:2608.23763v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) has emerged as the standard layer connecting Large Language Model agents to external tool backends. This openness int

agentsarxiv-cs-ai

TurboT2VA: Fast Large-Scale Text-to-Video-Audio Generation via Score-Regularized Consistency Distillation

model-releasesarxiv-cs-cv

arXiv:2608.24674v1 Announce Type: new Abstract: Joint text-to-video-audio generation produces synchronized visual and acoustic content, but the long sampling trajectories and heterogeneous multimodal

WarpSAC: Towards the Pinnacle of Scalable Off-policy RL by Rethinking Exploration and Exploitation

arXiv:2608.24479v1 Announce Type: new Abstract: Massively parallel simulation changes the data regime in which off-policy reinforcement learning (RL) is trained, challenging stabilizers designed for d

WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report

model-releasesarxiv-cs-cv

arXiv:2608.24053v1 Announce Type: new Abstract: Universal multimodal embeddings are becoming a core component of modern AI systems, enabling heterogeneous content to be represented in a shared space f

Local Ai

What Guides the Agent? Adjudicating Unauthorized Behavior via Localizing Behavior-Guiding Instructions

arXiv:2608.24022v1 Announce Type: cross Abstract: LLM agents integrated with external resources gain complex task capabilities, yet the unified natural-language context channel makes them vulnerable t

local-aiarxiv-cs-ai

XP-JEPA: Cross-Predictive Physics Grounding for Forecastable Latent Dynamics

arXiv:2608.24044v1 Announce Type: new Abstract: Latent world models plan by predicting how candidate actions transform learned representations. In self-predictive models, however, the encoder and pred

researcharxiv-cs-lg

A Query-Time Framework for Transient 2D Pore-Scale Flow Prediction and Generative Design

arXiv:2608.22235v1 Announce Type: new Abstract: Pore-scale flow governs transport and permeability behaviour in porous media engineering applications, yet repeated lattice Boltzmann method (LBM) simul

A Social Media Analysis of Discourse on the Israel--Palestine Conflict on Telegram

arXiv:2608.21385v1 Announce Type: cross Abstract: Social media has become a central arena in which armed conflicts are contested, yet the pro-Israel and pro-Palestine communities on Telegram, whose br

applicationsarxiv-cs-ai

A Unified Neural-Aided Alignment and Calibration Method for AUVs

arXiv:2608.22496v1 Announce Type: new Abstract: Autonomous underwater vehicles (AUVs) rely on the fusion of inertial navigation systems (INS) and Doppler velocity logs (DVL) for accurate navigation. B

safetyarxiv-cs-ro

Act with Intent: Distilling Behavior Intent for Vision-Language-Action Models

arXiv:2608.23478v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models can turn multimodal context into robot actions, but their action decoders are still trained largely by behavior cl

applicationsarxiv-cs-ai

ADMIL: Attention-Distilled Multiple Instance Learning for Selective Foundation Model Inference in Pathology

arXiv:2608.22066v1 Announce Type: cross Abstract: Attention-based multiple instance learning (ABMIL) using pathology foundation model embeddings is effective for slide-level tasks, but exhaustive infe

Agentic-Kube: A Graph-Enhanced Multi-Agent Reinforcement Learning Framework for Multi-Objective Kubernetes Scheduling

arXiv:2603.12031v3 Announce Type: replace-cross Abstract: Cloud-native container orchestration requires resource schedulers capable of balancing infrastructure expenditure, fault resilience, and node