Search: “routing”

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

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Endogenous Regime Switching Driven by Scalar-Irreducible Learning Dynamics

DGX agent

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

7 May 2026

Generative Quantum-inspired Kolmogorov-Arnold Eigensolver

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

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

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

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-

Applications

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

safetyarxiv-cs-ai

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

Applications

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

Privacy-Preserving Empathy Detection in Video Interactions

model-releasesarxiv-cs-cv

arXiv:2504.10808v3 Announce Type: replace Abstract: Detecting empathy from video interactions has emerging applications, yet raw videos that could be used for training AI models are rarely available d

Replacing Parameters with Preferences: Federated Alignment of Heterogeneous Vision-Language Models

arXiv:2605.03426v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have broad potential in privacy-sensitive domains such as healthcare and finance, yet strict data-sharing constraints rend

SafeRedir: Prompt Embedding Redirection for Robust Unlearning in Image Generation Models

arXiv:2601.08623v2 Announce Type: replace Abstract: Image generation models (IGMs), while capable of producing impressive and creative content, often memorize a wide range of undesirable concepts from

safetyarxiv-cs-cv

Tutorials

Stream-T1: Test-Time Scaling for Streaming Video Generation

arXiv:2605.04461v1 Announce Type: new Abstract: While Test-Time Scaling (TTS) offers a promising direction to enhance video generation without the surging costs of training, current test-time video ge

tutorialsarxiv-cs-cv

Unifying Dynamical Systems and Graph Theory to Mechanistically Understand Computation in Neural Networks

arXiv:2605.03598v2 Announce Type: cross Abstract: Understanding how biological and artificial neural networks implement computation from connectivity is a central problem in neuroscience and machine l

safetyarxiv-cs-ai

Applications

YOTOnet: Zero-Shot Cross-Domain Fault Diagnosis via Domain-Conditioned Mixture of Experts

arXiv:2605.04528v1 Announce Type: new Abstract: Mechanical equipment forms the critical backbone of modern industrial production, yet domain shift severely limits the generalization of deep learning b

applicationsarxiv-cs-lg

AfriqueLLM: How Data Mixing and Model Architecture Impact Continued Pre-training for African Languages

arXiv:2601.06395v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly multilingual, yet open models continue to underperform relative to proprietary systems, with the gap m

Agentic AI Systems Should Be Designed as Marginal Token Allocators

arXiv:2605.01214v1 Announce Type: new Abstract: This position paper argues that agentic AI systems should be designed and evaluated as marginal token allocation economies rather than as text generator

agentsarxiv-cs-ai

EngiAgent: Fully Connected Coordination of LLM Agents for Solving Open-ended Engineering Problems with Feasible Solutions

arXiv:2605.02289v1 Announce Type: new Abstract: Engineering problem solving is central to real-world decision-making, requiring mathematical formulations that not only represent complex problems but a

agentsarxiv-cs-ai

Enhancing Self-Supervised Talking Head Forgery Detection via a Training-Free Dual-System Framework

arXiv:2605.03390v1 Announce Type: new Abstract: Supervised talking head forgery detection faces severe generalization challenges due to the continuous evolution of generators. By reducing reliance on

GEM-FI: Gated Evidential Mixtures with Fisher Modulation

arXiv:2605.03750v1 Announce Type: new Abstract: Evidential Deep Learning (EDL) enables single-pass uncertainty estimation by predicting Dirichlet evidence, but it can remain overconfident and poorly c

HeadQ: Model-Visible Distortion and Score-Space Correction for KV-Cache Quantization

arXiv:2605.03562v1 Announce Type: new Abstract: KV-cache quantizers usually optimize storage-space reconstruction, even though attention reads keys through logits and values through attention-weighted

local-aiarxiv-cs-lg

Ortho-Hydra: Orthogonalized Experts for DiT LoRA

arXiv:2605.03252v1 Announce Type: cross Abstract: LoRA fine-tuning of diffusion transformers (DiT) on multi-style data suffers from style bleed: a single low-rank residual cannot represent several dis

PERSA: Reinforcement Learning for Professor-Style Personalized Feedback with LLMs

arXiv:2605.01123v1 Announce Type: new Abstract: Large language models (LLMs) can provide automated feedback in educational settings, but aligning an LLMs style with a specific instructors tone while m

Position: LLM Serving Needs Mathematical Optimization and Algorithmic Foundations, Not Just Heuristics

arXiv:2605.01280v1 Announce Type: cross Abstract: This position paper argues that LLM inference serving has outgrown generic heuristics and now demands mathematical optimization and algorithmic founda

researcharxiv-cs-ai

RD-ViT: Recurrent-Depth Vision Transformer for Semantic Segmentation with Reduced Data Dependence Extending the Recurrent-Depth Transformer Architecture to Dense Prediction

model-releasesarxiv-cs-cv

arXiv:2605.03999v1 Announce Type: new Abstract: Vision Transformers (ViTs) achieve state-of-the-art segmentation accuracy but require large training datasets because each layer has unique parameters t

The Right Answer, the Wrong Direction: Why Transformers Fail at Counting and How to Fix It

arXiv:2605.03258v1 Announce Type: cross Abstract: Large language models often fail at simple counting tasks, even when the items to count are explicitly present in the prompt. We investigate whether t

Where Paths Split: Localized, Calibrated Control of Moral Reasoning in Large Language Models

arXiv:2605.03609v1 Announce Type: cross Abstract: Large language models often display heterogeneous moral preferences across settings. We study inference-time steering toward a desired ethical framewo

A Category-Theoretic Analysis of Conformal Prediction

arXiv:2507.04441v4 Announce Type: replace-cross Abstract: Conformal prediction (CP) produces prediction regions with finite-sample, distribution free coverage guarantees, but its interpretation as a q

Attention Is Where You Attack

arXiv:2605.00236v1 Announce Type: cross Abstract: Safety-aligned large language models rely on RLHF and instruction tuning to refuse harmful requests, yet the internal mechanisms implementing safety b

Beyond Sentiment: A Multi-Agent Pipeline for Actionable Business Advice from Reviews

arXiv:2601.12024v2 Announce Type: replace-cross Abstract: Customer reviews contain valuable signals about service quality, but converting large-scale review corpora into actionable business recommenda

agentsarxiv-cs-cl

Decoding-Time Debiasing via Process Reward Models: From Controlled Fill-in to Open-Ended Generation

arXiv:2605.02348v1 Announce Type: new Abstract: Large language models pick up social biases from the data they are trained on and carry those biases into downstream applications, often reinforcing ste

Disentangled Anatomy-Disease Diffusion (DADD) for Controllable Ulcerative Colitis Progression Synthesis

arXiv:2605.01848v1 Announce Type: new Abstract: Synthesizing longitudinal medical images at controllable disease stages while preserving patient-specific anatomy is hindered by the entanglement of pat

Exploring Data-Free LoRA Transferability for Video Diffusion Models

arXiv:2605.01929v1 Announce Type: new Abstract: Video diffusion models leveraging step distillation or causal distillation have achieved remarkable performance. However, adapting existing LoRAs to the

safetyarxiv-cs-cv

FractalMamba++: Scaling Vision Mamba Across Resolutions via Hilbert Fractal Geometr

arXiv:2505.14062v3 Announce Type: replace Abstract: Vision Mamba offers linear complexity for long visual sequences, yet its performance depends critically on how a two-dimensional patch grid is seria

local-aiarxiv-cs-cv

From Cortical Synchronous Rhythm to Brain Inspired Learning Mechanism: An Oscillatory Spiking Neural Network with Time-Delayed Coordination

arXiv:2605.01656v1 Announce Type: cross Abstract: Human cognition emerges from coordinated spiking dynamics in distributed neural circuits, where information is encoded via both firing rates and preci

IConFace: Identity-Structure Asymmetric Conditioning for Unified Reference-Aware Face Restoration

arXiv:2605.02814v1 Announce Type: new Abstract: Blind face restoration is highly ill-posed under severe degradation, where identity-critical details may be missing from the degraded input. Same-identi

local-aiarxiv-cs-cv

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE

model-releasesarxiv-cs-cv

arXiv:2605.02641v1 Announce Type: new Abstract: We present Mamoda2.5, a unified AR-Diffusion framework that seamlessly integrates multimodal understanding and generation within a single architecture.

Model Merging: Foundations and Algorithms

arXiv:2605.01580v1 Announce Type: new Abstract: Modern deep learning usually treats models as separate artifacts: trained independently, specialized for particular purposes, and replaced when improved

MPCS: Neuroplastic Continual Learning via Multi-Component Plasticity and Topology-Aware EWC

arXiv:2605.02509v1 Announce Type: new Abstract: Continual learning systems face a fundamental tension between plasticity -- acquiring new knowledge -- and stability -- retaining prior knowledge. We in

Multi-Rater Calibrated Segmentation Models

arXiv:2605.02437v1 Announce Type: new Abstract: Objective: Accurate probability estimates are essential for the safe deployment of medical image segmentation models in clinical decision-making. Howeve

PC-MNet: Dual-Level Congruity Modeling for Multimodal Sarcasm Detection via Polarity-Modulated Attention

arXiv:2605.02447v1 Announce Type: new Abstract: Multimodal sarcasm detection, which aims to precisely identify pragmatic incongruities between literal text and nonverbal cues, has gained substantial a

Rethink MAE with Linear Time-Invariant Dynamics

arXiv:2605.00915v1 Announce Type: new Abstract: Standard representation probing for visual models relies on mathematically permutation-invariant operations like Global Average Pooling (GAP) or CLS tok

Space Network of Experts: Architecture and Expert Placement

arXiv:2605.00515v1 Announce Type: cross Abstract: Leveraging continuous solar energy harvesting at high efficiency, space data centers are envisioned as a promising platform for executing energy-inten

researcharxiv-cs-ai