Search: “meta”

Artificial Adaptive Intelligence: The Missing Stage Between Narrow and General Intelligence

arXiv:2605.16844v1 Announce Type: new Abstract: Between the narrow systems we deploy and the general intelligence we speculate about lies an entire regime of machine behavior that has never received i

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Automatic Unsupervised Ensemble Outlier Model Selection--Extended Version

DGX agent

arXiv:2605.16567v1 Announce Type: cross Abstract: Unsupervised outlier detection is attractive because it eliminates the need for labeled data. Moreover, forming multi-model ensembles can improve dete

applicationsarxiv-cs-ai

19 May 2026

CooT: Learning to Coordinate In-Context with Coordination Transformers

arXiv:2506.23549v3 Announce Type: replace Abstract: Effective coordination among unfamiliar partners remains a major challenge in multi-agent systems. Existing approaches, such as population-based met

Cost-aware Duration Prediction for Software Upgrades in Datacenters

arXiv:2212.05155v2 Announce Type: replace-cross Abstract: Software upgrades are critical to maintaining server reliability in datacenters. While job duration prediction and scheduling have been extens

Equilibrium Selection in Multi-Agent Policy Gradients via Opponent-Aware Basin Entry

arXiv:2605.18078v1 Announce Type: new Abstract: Multi-agent policy-gradient methods have been shown to converge locally near stable Nash equilibria. Local convergence, however, does not determine whic

safetyarxiv-cs-lg

FAM-HRI: Foundation-Model Assisted Multi-Modal Human-Robot Interaction Combining Gaze and Speech

model-releasesarxiv-cs-ro

arXiv:2503.16492v3 Announce Type: replace-cross Abstract: ffective Human-Robot Interaction (HRI) is crucial for enhancing accessibility and usability in real-world robotics applications. However, exis

Gesture First, LLM-Assisted Voice Complement: Exploring Multimodal Robot 'Puppeteer' Teleoperation Via Virtual Counterpart in Augmented Reality

arXiv:2506.13189v3 Announce Type: replace-cross Abstract: Robot teleoperation via augmented reality (AR) offers a promising path toward more intuitive human-robot interaction (HRI). We present a head-

researcharxiv-cs-ro

Applications

MR-SLAM: Immersive Spatial Supervision for Multi-Robot Mapping via Mixed Reality

arXiv:2605.16432v1 Announce Type: cross Abstract: Operating a multi-robot fleet for simultaneous localization and mapping (SLAM) in applications such as building inspection or warehouse-aisle monitori

applicationsarxiv-cs-ai

The Laplacian Keyboard: Beyond the Linear Span

arXiv:2602.07730v2 Announce Type: replace-cross Abstract: Across scientific disciplines, Laplacian eigenvectors serve as a fundamental basis for simplifying complex systems, from signal processing to

WinDeskGround: A Benchmark for Robust GUI Grounding in Complex Multi-Window Desktop Environments

model-releasesarxiv-cs-cv

arXiv:2605.16402v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have revolutionized GUI automation, yet their efficacy is largely established on idealized, single-layer interf

Applications

CHoE: Cross-Domain Heterogeneous Graph Prompt Learning via Structure-Conditioned Experts

arXiv:2605.15888v1 Announce Type: cross Abstract: Heterogeneous Graph Prompt Learning (HGPL)has emerged as a promising paradigm for bridging the gap between the objectives of pre-training foundation m

applicationsarxiv-cs-ai

Applications

ExplainerPFN: Towards tabular foundation models for model-free zero-shot feature importance estimations

arXiv:2601.23068v2 Announce Type: replace-cross Abstract: Computing the importance of features in supervised classification tasks is critical for model interpretability. Shapley values are a widely us

applicationsarxiv-cs-ai

Large Language Models as Optimization Controllers: Adaptive Continuation for SIMP Topology Optimization

arXiv:2603.25099v2 Announce Type: replace-cross Abstract: We present a framework in which a large language model (LLM) acts as an online adaptive controller for SIMP topology optimization, replacing c

Learn2Splat: Extending the Horizon of Learned 3DGS Optimization

model-releasesarxiv-cs-cv

arXiv:2605.15760v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) optimization is most commonly performed using standard optimizers (Adam, SGD). While stable across diverse scenes, standard

Searching on a Budget: HW-NAS with 10 Latency Probes

arXiv:2504.00663v2 Announce Type: replace Abstract: Existing hardware-aware NAS (HW-NAS) methods typically assume access to precise information circa the target device, either via analytical approxima

A Regret Perspective on Online Multiple Testing

arXiv:2605.13916v1 Announce Type: cross Abstract: Online Multiple Testing (OMT), a fundamental pillar of sequential statistical inference, traditionally evaluates the False Discovery Rate (FDR) and st

Beyond the Final Answer: Evaluating the Reasoning Trajectories of Tool-Augmented Agents

arXiv:2510.02837v2 Announce Type: replace Abstract: Although recent tool-augmented benchmarks involve complex requests, evaluation remains limited to answer matching, neglecting critical trajectory as

agentsarxiv-cs-ai

Causal Foundation Models with Continuous Treatments

arXiv:2605.15133v1 Announce Type: new Abstract: Causal inference, estimating causal effects from observational data, is a fundamental tool in many disciplines. Of particular importance across a variet

researcharxiv-cs-lg

Causal Multi-Task Demand Learning

arXiv:2602.09969v2 Announce Type: replace Abstract: We study a canonical multi-task demand-learning problem motivated by retail pricing, where a firm seeks to estimate heterogeneous linear price-respo

researcharxiv-cs-lg

EvolveMem:Self-Evolving Memory Architecture via AutoResearch for LLM Agents

arXiv:2605.13941v1 Announce Type: cross Abstract: Long-term memory is essential for LLM agents that operate across multiple sessions, yet existing memory systems treat retrieval infrastructure as fixe

In-Context Learning for Data-Driven Censored Inventory Control

arXiv:2605.14840v1 Announce Type: new Abstract: We study inventory control with decision-dependent censoring, focusing on the censored or repeated newsvendor (R-NV), where each order quantity determin

Polaris: A Godel Agent Framework for Small Language Models through Experience-Abstracted Policy Repair

arXiv:2603.23129v2 Announce Type: replace Abstract: Godel agent realize recursive self-improvement: an agent inspects its own policy and traces and then modifies that policy in a tested loop. We intro

Rethinking the Good Enough Embedding for Easy Few-Shot Learning

arXiv:2605.14145v1 Announce Type: new Abstract: The field of deep visual recognition is undergoing a paradigm shift toward universal representations. The Platonic Representation Hypothesis suggests th

researcharxiv-cs-cv

ROAD: Adaptive Data Mixing for Offline-to-Online Reinforcement Learning via Bi-Level Optimization

arXiv:2605.14497v1 Announce Type: cross Abstract: Offline-to-online reinforcement learning harnesses the stability of offline pretraining and the flexibility of online fine-tuning. A key challenge lie

The Evaluation Trap: Benchmark Design as Theoretical Commitment

arXiv:2605.14167v1 Announce Type: new Abstract: Every AI benchmark operationalizes theoretical assumptions about the capability it claims to assess. When assumptions function as unexamined commitments

AIvaluateXR: An Evaluation Framework for on-Device AI in XR with Benchmarking Results

arXiv:2502.15761v3 Announce Type: replace-cross Abstract: The deployment of large language models (LLMs) on extended reality (XR) devices has great potential to advance the field of human-AI interacti

local-aiarxiv-cs-ai

CHAL: Council of Hierarchical Agentic Language

arXiv:2605.12718v1 Announce Type: new Abstract: Multi-agent debate has emerged as a promising approach for improving LLM reasoning on ground-truth tasks, yet current methodologies face certain structu

agentsarxiv-cs-ai

LLM Flow Processes for Text-Conditioned Regression

arXiv:2601.06147v2 Announce Type: replace Abstract: Recent work has demonstrated surprisingly good performance of pre-trained LLMs on regression tasks (for example, time-series prediction), with the a

local-aiarxiv-cs-lg

MMSkills: Towards Multimodal Skills for General Visual Agents

arXiv:2605.13527v1 Announce Type: new Abstract: Reusable skills have become a core substrate for improving agent capabilities, yet most existing skill packages encode reusable behavior primarily as te

agentsarxiv-cs-ai

Procedural Refinement by LLM-driven Algorithmic Debugging for ARC-AGI-2

arXiv:2603.20334v2 Announce Type: replace-cross Abstract: In high-complexity abstract reasoning, a system must infer a latent rule from a few examples or structured observations and apply it to unseen

Active inference as a unified model of collision avoidance behavior in human drivers

arXiv:2506.02215v5 Announce Type: replace Abstract: Collision avoidance -- involving a rapid threat detection and quick execution of the appropriate evasive maneuver -- is a critical aspect of driving

researcharxiv-cs-ro

AgentDisCo: Towards Disentanglement and Collaboration in Open-ended Deep Research Agents

arXiv:2605.11732v1 Announce Type: cross Abstract: In this paper, we present AgentDisCo, a novel Disentangled and Collaborative agentic architecture that formulates deep research as an adversarial opti

An Empirical Study of Automating Agent Evaluation

arXiv:2605.11378v1 Announce Type: new Abstract: Agent evaluation requires assessing complex multi-step behaviors involving tool use and intermediate reasoning, making it costly and expertise-intensive

Hardware

MLCommons Chakra: Advancing Performance Benchmarking and Co-design using Standardized Execution Traces

arXiv:2605.11333v1 Announce Type: cross Abstract: The fast pace of artificial intelligence~(AI) innovation demands an agile methodology for observation, reproduction and optimization of distributed ma

hardwarearxiv-cs-lg

POP: Prior-Fitted First-Order Optimization Policies

arXiv:2602.15473v2 Announce Type: replace Abstract: Gradient-based optimizers are highly sensitive to design choices in their adaptive learning rate mechanisms. To address this limitation, we introduc

Position: Universal Aesthetic Alignment Narrows Artistic Expression

arXiv:2512.11883v3 Announce Type: replace-cross Abstract: Over-aligning image generation models to a generalized aesthetic preference conflicts with user intent, particularly when 'anti-aesthetic' out

safetyarxiv-cs-cv

Rethinking LLMOps for Fraud and AML: Building a Compliance-Grade LLM Serving Stack

arXiv:2605.11232v1 Announce Type: cross Abstract: Fraud detection and anti-money-laundering (AML) compliance are high-value domains for large language models (LLMs), but their serving requirements dif

Hardware

To Err Is Human; To Annotate, SILICON? Toward Robust Reproducibility in LLM Annotation

arXiv:2412.14461v4 Announce Type: replace Abstract: Unstructured text data annotation is foundational to management research. LLMs offer a cost-effective and scalable alternative to human annotation,

hardwarearxiv-cs-cl

TOPPO: Rethinking PPO for Multi-Task Reinforcement Learning with Critic Balancing

arXiv:2605.11473v1 Announce Type: cross Abstract: Soft Actor-Critic (SAC) and its variants dominate Multi-Task Reinforcement Learning (MTRL) due to their off-policy sample efficiency, while on-policy

Byte-Exact Deduplication in Retrieval-Augmented Generation: A Three-Regime Empirical Analysis Across Public Benchmarks

arXiv:2605.09611v1 Announce Type: new Abstract: This preprint presents an empirical analysis of byte-exact chunk-level deduplication in Retrieval-Augmented Generation (RAG) pipelines. We measure conte

CapVector: Learning Transferable Capability Vectors in Parametric Space for Vision-Language-Action Models

model-releasesarxiv-cs-cv

arXiv:2605.10903v1 Announce Type: new Abstract: This paper proposes a novel approach to address the challenge that pretrained VLA models often fail to effectively improve performance and reduce adapta

EvoMAS: Learning Execution-Time Workflows for Multi-Agent Systems

arXiv:2605.08769v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems have shown strong potential on complex tasks through agent specialization, tool use, and collaborat

FlashEvolve: Accelerating Agent Self-Evolution with Asynchronous Stage Orchestration

arXiv:2605.08520v1 Announce Type: new Abstract: LLM-based evolution has emerged as a promising way to improve agents by refining non-parametric artifacts, but its wall-clock cost remains a major bottl

local-aiarxiv-cs-lg

GAMBIT: A Three-Mode Benchmark for Adversarial Robustness in Multi-Agent LLM Collectives

arXiv:2605.09027v1 Announce Type: new Abstract: In multi-agent systems (MAS), a single deceptive agent can nullify all gains of an agentic AI collective and evade deployed defenses. However, existing

GRC: Unifying Reasoning-Driven Generation, Retrieval and Compression

arXiv:2605.09100v1 Announce Type: new Abstract: Text embedding and generative tasks are usually trained separately based on large language models (LLMs) nowadays. This causes a large amount of trainin

agentsarxiv-cs-cl

LLM Jaggedness Unlocks Scientific Creativity

arXiv:2605.10574v1 Announce Type: new Abstract: As artificial intelligence advances, models are not improving uniformly. Instead, progress unfolds in a jagged fashion, with capabilities growing uneven

One for All: A Non-Linear Transformer can Enable Cross-Domain Generalization for In-Context Reinforcement Learning

arXiv:2605.09727v1 Announce Type: cross Abstract: A central challenge in reinforcement learning (RL) is to learn models that generalize beyond the tasks on which they are trained, a goal traditionally

Playing games with knowledge: AI-Induced delusions need game theoretic interventions

arXiv:2605.08409v1 Announce Type: new Abstract: Conversational AI has a fundamental flaw as a knowledge interface: sycophantic chatbots induce epistemic entrenchment and delusional belief spirals even

local-aiarxiv-cs-ai