Search: “routing”

What If We Let Forecasting Forget? A Sparse Bottleneck for Cross-Variable Dependencies

arXiv:2605.08289v1 Announce Type: cross Abstract: Multivariate time series forecasting is critical in many real-world systems, and thus modeling cross-channel dependencies is essential. Although exist

applicationsarxiv-cs-ai

12 May 2026

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Agents

Willful Disobedience: Automatically Detecting Failures in Agentic Traces

DGX agent

arXiv:2603.23806v2 Announce Type: replace-cross Abstract: AI agents are increasingly embedded in real software systems, where they execute multi-step workflows through multi-turn dialogue, tool invoca

agentsarxiv-cs-ai

12 May 2026

Workspace Optimization: How to Train Your Agent

arXiv:2605.09650v1 Announce Type: new Abstract: Modern agents built on frontier language models often cannot adapt their weights. What, then, remains trainable? We argue it is the agent's workspace, t

12 May 2026

A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks

arXiv:2603.22586v2 Announce Type: replace Abstract: In-context learning (ICL) enables task adaptation at inference time by conditioning on demonstrations rather than updating model parameters. Althoug

ART for Diffusion Sampling: A Reinforcement Learning Approach to Timestep Schedule

arXiv:2601.18681v2 Announce Type: replace-cross Abstract: We consider time discretization for score-based diffusion models to generate samples from a learned reverse-time dynamic on a finite grid. Uni

Attention Transfer Is Not Universally Effective for Vision Transformers

model-releasesarxiv-cs-cv

arXiv:2605.07191v1 Announce Type: new Abstract: A recent work shows that Attention Transfer, which transfers only the attention patterns from a pre-trained teacher Vision Transformer (ViT) to a random

Beyond GSD-as-Token: Continuous Scale Conditioning for Remote Sensing VLMs

model-releasesarxiv-cs-cv

arXiv:2605.07562v1 Announce Type: new Abstract: Remote sensing vision-language models (RS-VLMs) face a fundamental mismatch with natural-image counterparts: the same geographic object exhibits radical

BioProVLA-Agent: An Affordable, Protocol-Driven, Vision-Enhanced VLA-Enabled Embodied Multi-Agent System with Closed-Loop-Capable Reasoning for Biological Laboratory Manipulation

arXiv:2605.07306v1 Announce Type: cross Abstract: Biological laboratory automation can reduce repetitive manual work and improve reproducibility, but reliable embodied execution in wet-lab environment

Hardware

Closed-Form Linear-Probe Dataset Distillation for Pre-trained Vision Models

arXiv:2605.07194v1 Announce Type: cross Abstract: Dataset distillation compresses a large training set into a small synthetic set that preserves downstream training utility. While most existing method

hardwarearxiv-cs-ai

Continually Evolving Skill Knowledge in Vision Language Action Model

arXiv:2511.18085v4 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models show promising knowledge accumulation ability from pretraining, yet continual learning in VLA remains chal

Dr-BA: Separable Optimization for Direct Radar Bundle Adjustment & Localization

arXiv:2605.07041v1 Announce Type: cross Abstract: This paper introduces Dr-BA, a first-of-its-kind radar bundle adjustment (BA) framework that operates directly on 2D spinning radar intensity images.

safetyarxiv-cs-cv

Flow-OPD: On-Policy Distillation for Flow Matching Models

arXiv:2605.08063v1 Announce Type: cross Abstract: Existing Flow Matching (FM) text-to-image models suffer from two critical bottlenecks under multi-task alignment: the reward sparsity induced by scala

GazeVLM: Active Vision via Internal Attention Control for Multimodal Reasoning

arXiv:2605.07817v1 Announce Type: cross Abstract: Human visual reasoning is governed by active vision, a process where metacognitive control drives top-down goal-directed attention, dynamically routin

Intelligent Truck Matching in Full Truckload Shipments using Ping2Hex approach

arXiv:2605.07733v1 Announce Type: cross Abstract: Accurate truck-to-shipment matching using GPS data is foundational for full truckload supply chain visibility, enabling real-time tracking and accurat

applicationsarxiv-cs-ai

LLM-Guided Open Hypothesis Learning from Autonomous Scanning Probe Microscopy Experiments

arXiv:2605.06839v1 Announce Type: cross Abstract: Autonomous experimentation has transformed microscopy and materials discovery by enabling closed-loop optimization including imaging and spectroscopy

MORPH-U: Multi-Objective Resilient Motion Planning for V2X-Enabled Autonomous Driving in High-Uncertainty Environments via Simulation

arXiv:2605.07370v1 Announce Type: cross Abstract: V2X can warn an autonomous vehicle about hazards beyond line-of-sight, but it also brings uncertainty: messages may be delayed, dropped, or even forge

Relay Buffer Independent Communication over Pooled HBM for Efficient MoE Inference on Ascend

arXiv:2605.06055v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) inference requires large-scale token exchange across devices, making dispatch and combine major bottlenecks in both p

SatSurfGS: Generalizable 2D Gaussian Splatting for Sparse-View Satellite Surface Reconstruction

model-releasesarxiv-cs-cv

arXiv:2605.07181v1 Announce Type: new Abstract: Sparse-view satellite image surface reconstruction remains highly challenging, fundamentally because the reliability of multi-view matching under satell

Self-Consolidating Language Models: Continual Knowledge Incorporation from Context

arXiv:2605.07076v1 Announce Type: new Abstract: Large language models (LLMs) increasingly receive information as streams of passages, conversations, and long-context workflows. While longer context wi

researcharxiv-cs-cl

Switchcraft: AI Model Router for Agentic Tool Calling

arXiv:2605.07112v1 Announce Type: new Abstract: Agentic AI systems that invoke external tools are powerful but costly, leading developers to default to large models and overspend inference budgets. Mo

Visual Text Compression as Measure Transport

arXiv:2605.06708v1 Announce Type: cross Abstract: Visual text compression (VTC) promises efficient long-context processing by rendering text into an image and re-encoding it with a vision-language mod

VLA-GSE: Boosting Parameter-Efficient Fine-Tuning in VLA with Generalized and Specialized Experts

model-releasesarxiv-cs-ro

arXiv:2605.06175v2 Announce Type: replace Abstract: Vision-language-action (VLA) models inherit rich visual-semantic priors from pre-trained vision-language backbones, but adapting them to robotic con

Where's the Plan? Locating Latent Planning in Language Models with Lightweight Mechanistic Interventions

arXiv:2605.07984v1 Announce Type: cross Abstract: We study planning site formation in language models -- where internal representations of structurally-constrained future tokens form during the forwar

XDecomposer: Learning Prior-Free Set Decomposition for Multiphase X-ray Diffraction

arXiv:2605.05866v1 Announce Type: cross Abstract: Multiphase powder X-ray diffraction (PXRD) analysis remains a fundamental bottleneck in structure identification, as real-world synthesis often produc

applicationsarxiv-cs-lg

Docs from @NousResearch on how to set up Pareto Code in Hermes: https://hermes-agent.nousresearch.com/docs/user-guide/configuration#openrout…

Docs from @NousResearch on how to set up Pareto Code in Hermes: https://hermes-agent.nousresearch.com/docs/user-guide/configuration#openrouter-routing--pareto-code-for-auxiliary-tasks Introducing Pare

agentsnous-research--x

10 May 2026

@OpenRouter http://hermes-agent.nousresearch.com

Nous Research announced or shared information about their Hermes Agent project via OpenRouter, likely detailing capabilities, updates, or technical specifications for their AI agent system. OpenRouter

agentsnous-research--x

9 May 2026

The human brain🧠 is incredibly efficient because it only activates the specific neurons needed for a thought. Modern LLMs naturally try to …

The human brain🧠 is incredibly efficient because it only activates the specific neurons needed for a thought. Modern LLMs naturally try to do this too (> 95% of neurons in feedforward layers stay sile

safetydavid-ha--x

8 May 2026

When well-behaved agents trigger disaster

It’s 2:17 a.m., and your application monitor flags elevated database latency. Before your on-call engineer finishes reading the alert, three agents have already responded. The performance agent double

agentssiliconangle

8 May 2026

An Agent-Oriented Pluggable Experience-RAG Skill for Experience-Driven Retrieval Strategy Orchestration

arXiv:2605.03989v1 Announce Type: new Abstract: Retrieval-augmented generation systems often assume that one fixed retrieval pipeline is sufficient across heterogeneous tasks, yet factoid question ans

AnyPos: Automated Task-Agnostic Actions for Bimanual Manipulation

arXiv:2507.12768v2 Announce Type: replace Abstract: Learning generalizable manipulation policies hinges on data, yet robot manipulation data is scarce and often entangled with specific embodiments, ma

safetyarxiv-cs-cv

ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration

arXiv:2605.03042v1 Announce Type: cross Abstract: This report describes ARIS (Auto-Research-in-sleep), an open-source research harness for autonomous research, including its architecture, assurance me

Consensus Entropy: Harnessing Multi-VLM Agreement for Self-Verifying and Self-Improving OCR

arXiv:2504.11101v4 Announce Type: replace Abstract: Optical Character Recognition (OCR) is fundamental to Vision-Language Models (VLMs) and high-quality data generation for LLM training. Yet, despite

researcharxiv-cs-cv

Contextual Memory-Enhanced Source Coding for Low-SNR Communications

arXiv:2605.04400v1 Announce Type: cross Abstract: While Separate Source-Channel Coding (SSCC) retains the practical benefits of modular system design, its effectiveness in noisy text transmission is f

Local Ai

Contextual Multi-Objective Optimization: Rethinking Objectives in Frontier AI Systems

arXiv:2605.03900v1 Announce Type: new Abstract: Frontier AI systems perform best in settings with clear, stable, and verifiable objectives, such as code generation, mathematical reasoning, games, and

local-aiarxiv-cs-ai

Endogenous Regime Switching Driven by Scalar-Irreducible Learning Dynamics

arXiv:2605.04054v1 Announce Type: new Abstract: Achieving endogenous regime switching is crucial for the emergence of autonomous intelligence, yet remains a central challenge for existing machine lear

agentsarxiv-cs-lg

Generative Quantum-inspired Kolmogorov-Arnold Eigensolver

model-releasesarxiv-cs-lg

arXiv:2605.04604v1 Announce Type: cross Abstract: High-performance computing (HPC) is increasingly important for scalable quantum chemistry workflows that couple classical generative models, quantum c

Local Ai

Geometry-Aware State Space Model: A New Paradigm for Whole-Slide Image Representation

arXiv:2605.05164v1 Announce Type: new Abstract: Accurate analysis of histopathological images is critical for disease diagnosis and treatment planning. Whole-slide images (WSIs), which digitize tissue

local-aiarxiv-cs-cv

HUGO-CS: A Hybrid-Labeled, Uncertainty-Aware, General-Purpose, Observational Dataset for Cold Spray

model-releasesarxiv-cs-lg

arXiv:2605.04257v1 Announce Type: new Abstract: Cold spraying is an increasingly common approach for repairing and manufacturing components due to its solid-state manufacturing capabilities. However,

InterFuserDVS: Event-Enhanced Sensor Fusion for Safe RL-Based Decision Making

arXiv:2605.04355v1 Announce Type: new Abstract: Autonomous driving systems rely heavily on robust sensor fusion to perceive complex envi- ronments. Traditional setups using RGB cameras and LiDAR often

safetyarxiv-cs-cv

LAWS: Learning from Actual Workloads Symbolically -- A Self-Certifying Parametrized Cache Architecture for Neural Inference, Robotics, and Edge Deployment

arXiv:2605.04069v1 Announce Type: new Abstract: We introduce LAWS (Learning from Actual Workloads Symbolically), a self-certifying inference caching architecture that builds a growing library of certi

agentsarxiv-cs-lg

Lightning Unified Video Editing via In-Context Sparse Attention

arXiv:2605.04569v1 Announce Type: new Abstract: Video editing has evolved toward In-Context Learning (ICL) paradigms, yet the resulting quadratic attention costs create a critical computational bottle

researcharxiv-cs-cv

Tutorials

Meta-LegNet: A Transferable and Interpretable Framework for Surface Adsorption Prediction via Self-Defined Adsorption-Environment Learning

arXiv:2605.04102v1 Announce Type: cross Abstract: A central challenge in computational catalysis is the identification of low-energy and chemically plausible adsorption configurations, as these direct

tutorialsarxiv-cs-lg

MoLF: Mixture-of-Latent-Flow for Pan-Cancer Spatial Gene Expression Prediction from Histology

arXiv:2602.02282v2 Announce Type: replace Abstract: Inferring spatial transcriptomics (ST) from histology enables scalable histogenomic profiling, yet current methods are largely restricted to single-

New Bigtable in-memory tier for sub-millisecond read latency

In the high-stakes world of digital infrastructure, speed isn't just a metric — it’s currency. At Google Cloud Next ‘26 we announced the Bigtable in-memory tier, a breakthrough for our fully managed c

safetygoogle-cloud-ai

Perturbation is All You Need for Extrapolating Language Models

arXiv:2605.04344v1 Announce Type: cross Abstract: We introduce a simple yet powerful framework for training large language models. In contrast to the standard autoregressive next-token prediction base

applicationsarxiv-cs-lg

PhySe-RPO: Physics and Semantics Guided Relative Policy Optimization for Diffusion-Based Surgical Smoke Removal

arXiv:2603.22844v4 Announce Type: replace Abstract: Surgical smoke severely degrades intraoperative video quality, obscuring anatomical structures and limiting surgical perception. Existing learning-b

Physics-Grounded Multi-Agent Architecture for Traceable, Risk-Aware Human-AI Decision Support in Manufacturing

arXiv:2605.04003v1 Announce Type: cross Abstract: High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledg

Predictive and Prescriptive AI toward Optimizing Wildfire Suppression

arXiv:2605.04510v1 Announce Type: cross Abstract: Intense wildfire seasons require critical prioritization decisions to allocate scarce suppression resources over a dispersed geographical area. This p

applicationsarxiv-cs-lg