Search: “deployment”

A Production-Ready RL Framework for Personalized Utility Tuning with Pareto Sweeping in Pinterest Recommender Systems

model-releasesarxiv-cs-lg

arXiv:2605.16344v1 Announce Type: cross Abstract: Large-scale recommenders encode multi-objective trade-offs by combining multiple predicted outcomes into a single utility score. Although this utility

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Safety

Ablating Safety: Mechanisms for Removing Alignment in Language Models for Security Applications

DGX agent

arXiv:2605.17413v1 Announce Type: cross Abstract: Safety-aligned language models often refuse cybersecurity requests whose wording resembles misuse, even when the task is authorized and defensive. Thi

safetyarxiv-cs-ai

19 May 2026

Adaptive Control in Autonomous Driving via Real-Time Recurrent RL

arXiv:2602.02236v4 Announce Type: replace-cross Abstract: We study online fine-tuning of pretrained control policies for autonomous driving using Real-Time Recurrent Reinforcement Learning (RTRRL), a

Adversarial Fragility and Language Vulnerability in Clinical AI: A Systematic Audit of Diagnostic Collapse Under Imperceptible Perturbations and Cross-Lingual Drift in Low-Resource Healthcare Settings

arXiv:2605.16993v1 Announce Type: cross Abstract: Current clinical artificial intelligence (AI) systems are evaluated almost exclusively on clean, standardised, English-language inputs, conditions tha

AI for Auto-Research: Roadmap & User Guide

arXiv:2605.18661v1 Announce Type: new Abstract: AI-assisted research is crossing a threshold: fully automated systems can now generate research papers for as little as $15, while long-horizon agents c

AMS-HD: Hyperdimensional Computing for Real-Time and Energy-Efficient Acute Mountain Sickness Detection

arXiv:2602.08916v2 Announce Type: replace-cross Abstract: Objective: Acute mountain sickness (AMS) is the most prevalent altitude illness, affecting unacclimatized individuals ascending above 2,500 m

researcharxiv-cs-lg

An Empirical Study of Privacy Leakage Chains via Prompt Injection in Black-Box Chatbot Environments

arXiv:2605.18133v1 Announce Type: cross Abstract: LLM-based chatbot agents increasingly process user requests by combining natural-language reasoning with external tools such as web browsing. These ca

ANNEAL: Adapting LLM Agents via Governed Symbolic Patch Learning

arXiv:2605.16309v1 Announce Type: new Abstract: LLM-based agents can recover from individual execution errors, yet they repeatedly fail on the same fault when the underlying process knowledge--operato

Anytime and Difficulty-Adaptive PAC-Bayes for Constrained Density-Ratio Network with Continual Learning Guarantees

arXiv:2605.17212v1 Announce Type: new Abstract: A unified framework for learning under covariate shift is presented, in which a constrained density-ratio network approximates the Radon-Nikodym derivat

Auditing Multimodal LLM Raters: Central Tendency Bias in Clinical Ordinal Scoring

model-releasesarxiv-cs-cv

arXiv:2605.16386v1 Announce Type: new Abstract: Multimodal large language models (LLMs) are increasingly explored as automated evaluators in clinical settings, yet their scoring behavior on ordinal cl

Augmenting Human Evaluation with LLM Judges: How Many Human Reviews Do You Need?

arXiv:2605.16354v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as automated evaluators of AI systems, including in high-stakes applications. In this role, LLMs ar

Beyond Scaling: Agents Are Heading to the Edge

arXiv:2605.18535v1 Announce Type: new Abstract: The bottleneck of useful agentic intelligence has shifted from compressing world knowledge into a single model to executing a coordinated system. This p

Beyond Square Roots: Explicit Memory-Efficient Factorization for Multi-Epoch Private Learning

arXiv:2605.18379v1 Announce Type: new Abstract: Correlated-noise mechanisms are among the most promising approaches for improving the utility of differentially private model training, but rigorous gua

researcharxiv-cs-lg

CATA: Continual Machine Unlearning via Conflict-Averse Task Arithmetic

arXiv:2605.18610v1 Announce Type: cross Abstract: Vision-language models (VLMs) have shown remarkable ability in aligning visual and textual representations, enabling a wide range of multimodal applic

CheckSupport: A Local LLM-Powered Tool for Automated Manuscript Submission Checklist Selection and Completion

arXiv:2605.16377v1 Announce Type: cross Abstract: Transparent and standardized reporting is essential for reproducible scientific research, yet adherence to reporting guidelines remains inconsistent b

ChronoSC: Task-Oriented Semantic Communication via Temporal-to-Color Encoding

arXiv:2605.16388v1 Announce Type: new Abstract: Semantic communication (SC) aims to reduce transmission overhead by conveying task-relevant information rather than raw data. However, existing SC appro

researcharxiv-cs-cv

CompassAD: Intent-Driven 3D Affordance Grounding in Functionally Competing Objects

model-releasesarxiv-cs-cv

arXiv:2604.02060v2 Announce Type: replace Abstract: When told to 'cut the cake,' a robot must choose the knife over nearby scissors, despite both objects affording the same cutting function. In real-w

Could Large Language Models work as Post-hoc Explainability Tools in Credit Risk Models?

model-releasesarxiv-cs-lg

arXiv:2602.18895v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown promise in translating model-based explanations into human-readable narratives. This study evaluates w

Cracks in the Foundation: A Civil Infrastructure Dataset to Challenge Vision Foundation Models

arXiv:2605.18413v1 Announce Type: new Abstract: Automated structural health monitoring is essential to prevent catastrophic infrastructure failures. Precise, pixel-level defect segmentation is needed

safetyarxiv-cs-cv

Cross-modal Affinity-aligned Multimodal Learning Analytics for Predicting Student Collaboration Satisfaction in Game-Based Learning

arXiv:2605.16806v1 Announce Type: cross Abstract: Collaborative game-based learning environments offer rich opportunities for small-group knowledge construction, yet automatically predicting student c

Cross-Source Supervision for Bone Infection Segmentation in Dual-Modality PET-CT

arXiv:2605.16373v1 Announce Type: cross Abstract: Early and accurate diagnosis and lesion localization of bone infections are crucial for clinical treatment. PET-CT integrates anatomical information f

DARC: Disagreement-Aware Alignment via Risk-Constrained Decoding

arXiv:2603.08145v2 Announce Type: replace-cross Abstract: Preference-based alignment methods (e.g., RLHF, DPO) typically optimize a single scalar objective, implicitly averaging over heterogeneous hum

Data Presentation Over Architecture: Resampling Strategies for Credit Risk Prediction with Tabular Foundation Models

arXiv:2605.18635v1 Announce Type: cross Abstract: Credit default prediction is a tabular learning problem with severe class imbalance, heterogeneous features, and tight latency budgets. Tabular Founda

DCFold: Efficient Protein Structure Generation with Single Forward Pass

arXiv:2605.17899v1 Announce Type: cross Abstract: AlphaFold3 introduces a diffusion-based architecture that elevates protein structure prediction to all-atom resolution with improved accuracy. This st

Hardware

Dell’s CFO sees the enterprise AI buildout as a generational opportunity still in its opening act

AI factory momentum has reached a critical inflection point as capital joins silicon and energy as key constraints in the race to build enterprise AI infrastructure. That dynamic is playing out in rea

hardwaresiliconangle

DeMa: Dual-Path Delay-Aware Mamba for Efficient Multivariate Time Series Analysis

arXiv:2601.05527v2 Announce Type: replace-cross Abstract: Accurate and efficient multivariate time series (MTS) analysis is increasingly critical for a wide range of intelligent applications. Within t

DevBench: A Realistic, Developer-Informed Benchmark for Code Generation Models

arXiv:2601.11895v3 Announce Type: replace-cross Abstract: DevBench is a telemetry-driven benchmark designed to evaluate Large Language Models (LLMs) on realistic code completion tasks. It includes 1,8

DexHoldem: Playing Texas Hold'em with Dexterous Embodied System

arXiv:2605.18727v1 Announce Type: cross Abstract: Evaluating embodied systems on real dexterous hardware requires more than isolated primitive skills: an agent must perceive a changing tabletop scene,

Distributed Perceptron under Bounded Staleness, Partial Participation, and Noisy Communication

model-releasesarxiv-cs-lg

arXiv:2601.10705v3 Announce Type: replace Abstract: We study a semi-asynchronous client-server perceptron trained via iterative parameter mixing (IPM-style averaging): clients run local perceptron upd

Divergence-Suppressing Couplings for Rectified Flow

arXiv:2605.17733v1 Announce Type: new Abstract: The promise of Rectified Flow rests on producing self-generated couplings whose trajectories are straight, or nearly so. In practice, trajectories gener

Agents

DSPR: Dual-Stream Physics-Residual Networks for Trustworthy Industrial Time Series Forecasting

arXiv:2604.07393v2 Announce Type: replace-cross Abstract: Accurate forecasting of industrial time series requires balancing predictive accuracy with physical plausibility under non-stationary operatin

agentsarxiv-cs-ai

DuIVRS-2: An LLM-based Interactive Voice Response System for Large-scale POI Attribute Acquisition

arXiv:2605.17900v1 Announce Type: new Abstract: Accurate Point of Interest (POI) attribute acquisition is essential for location-based services, yet traditional modular Interactive Voice Response (IVR

DyDiff: Long-Horizon Rollout via Dynamics Diffusion for Offline Reinforcement Learning

arXiv:2405.19189v3 Announce Type: replace Abstract: With the great success of diffusion models (DMs) in generating realistic synthetic vision data, many researchers have investigated their potential i

Embedded ConvNet Ensembles: A Lightweight Approach to Recognize Arabic Handwritten Characters

arXiv:2605.18060v1 Announce Type: new Abstract: Arabic Handwritten Character Recognition (AHCR) has recently advanced significantly with deep Convolutional Neural Networks (ConvNets). However, many mo

researcharxiv-cs-cv

Enhancing Cloud Network Resilience via a Robust LLM-Empowered Multi-Agent Reinforcement Learning Framework

arXiv:2601.07122v2 Announce Type: replace-cross Abstract: While virtualization and resource pooling empower cloud networks with structural flexibility and elastic scalability, they inevitably expand t

Enhancing the Code Reasoning Capabilities of LLMs via Consistency-based Reinforcement Learning

arXiv:2605.17958v1 Announce Type: new Abstract: Code reasoning refers to the task of predicting the output of a program given its source code and specific inputs. It can measure the reasoning capabili

researcharxiv-cs-lg

Episodic-Semantic Memory Architecture for Long-Horizon Scientific Agents

arXiv:2605.17625v1 Announce Type: new Abstract: As Large Language Models (LLMs) evolve into persistent scientific collaborators, context window saturation has emerged as a critical bottleneck. Scienti

ESI-Bench: Towards Embodied Spatial Intelligence that Closes the Perception-Action Loop

arXiv:2605.18746v1 Announce Type: cross Abstract: Spatial intelligence unfolds through a perception-action loop: agents act to acquire observations, and reason about how observations vary as a functio

Ethical Hyper-Velocity (EHV): A Provably Deterministic Governance-Aware JIT Compiler Architecture for Agentic Systems

arXiv:2605.17909v1 Announce Type: new Abstract: As autonomous agentic systems scale across regulated critical infrastructures, the lack of mechanistic, hardware-rooted enforcement for high-frequency p

Evaluating AI Alignment in LLMs: Output Analysis of Value Priorities Across 75 Models with Human Benchmarking

arXiv:2506.12617v4 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in human-AI interaction research and practice, yet existing capability and safety benchmarks reve

Event-Grounded Sparse Autoencoders for Vision-Language-Action Policies

arXiv:2605.17204v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies translate language and visual inputs into robot actions, where their hidden representations directly shape close

Evo-Memory: Benchmarking LLM Agent Test-time Learning with Self-Evolving Memory

arXiv:2511.20857v2 Announce Type: replace-cross Abstract: Statefulness is essential for large language model (LLM) agents to perform long-term planning and problem-solving. This makes memory a critica

Applications

Excited for this conversation with @hwchase17 , Co-Founder & CEO of @LangChain , on June 2 at the @traversal_ai office in NYC. We’ll be talk…

applicationsharrison-chase--x

Excited for this conversation with @hwchase17 , Co-Founder & CEO of @LangChain , on June 2 at the @traversal_ai office in NYC. We’ll be talking about what it actually takes to operate AI agents in pro

Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks

arXiv:2603.11689v2 Announce Type: replace Abstract: Frontier Multimodal Large Language Models (MLLMs) exhibit remarkable capabilities in Visual-Language Comprehension (VLC) tasks. However, they are of

Agents

extsc{MasFACT}: Continual Multi-Agent Topology Learning via Geometry-Aware Posterior Transfer

arXiv:2605.17361v1 Announce Type: cross Abstract: Multi-agent systems (MAS) powered by large language models (LLMs) have emerged as a powerful paradigm for complex problem solving, where performance c

agentsarxiv-cs-ai

Applications

Federated Distillation on Edge Devices: Efficient Client-Side Filtering for Non-IID Data

arXiv:2508.14769v2 Announce Type: replace Abstract: Federated distillation has emerged as a promising collaborative machine learning approach, offering enhanced privacy protection and reduced communic

applicationsarxiv-cs-lg

FediLoRA: Practical Federated Fine-Tuning of Foundation Models Under Missing-Modality Constraints

arXiv:2509.06984v3 Announce Type: replace-cross Abstract: Federated Learning with LoRA fine-tuning offers an efficient and privacy-aware solution for institutions to collaboratively leverage their lar

Fix the Structural Bottleneck: Context Compression via Explicit Information Transmission

model-releasesarxiv-cs-cl

arXiv:2602.03784v2 Announce Type: replace Abstract: Long-context LLM agents often struggle with growing token, memory, and latency costs, making efficient context compression essential for practical d