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arXiv:2510.12843v2 Announce Type: replace Abstract: Spiking neural networks (SNNs) promise energy-efficient artificial intelligence on neuromorphic hardware but struggle with tasks requiring both fast

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Hardware

PageWeaver: KV-Guided Query Unions for Sparse Attention

DGX agent

arXiv:2610.11201v1 Announce Type: cross Abstract: Dynamic sparse attention limits the KV pages selected by each query, but a small support does not necessarily yield efficient GPU work. Query unions s

hardwarearxiv-cs-lg

9 Oct 2026

Read What Matters: Query-Adaptive Quantization for KV Caches

arXiv:2610.11245v1 Announce Type: cross Abstract: KV-cache entries are stored before their future queries are known, but each decoding query needs precision in different places. We study this mismatch

The Missing Fourth Term for the Emulation Tensor Memory Equilibrium (TME) Model: The Residue Deconstruction Cost

arXiv:2610.10924v1 Announce Type: cross Abstract: The Tensor-Memory Equilibrium (TME) model of 'FP8 is All You Need (Part 1)' calculates the execution time of Ozaki Scheme II emulation of fp64 as the

Traceable World State: A Provenance-Aware State Representation and Deterministic Replay Framework for Robotic Systems

arXiv:2610.12033v1 Announce Type: cross Abstract: Robotic systems operating over extended tasks must maintain a world state assembled from observations arriving at different times, with varying confid

Accelerating Floating-Point Satisfiability Solving via Gradient Normalization

arXiv:2610.08808v1 Announce Type: cross Abstract: Satisfiability Modulo Theories (SMT) solvers are foundational to software verification, program analysis, and compiler testing, particularly over the

Artificial intelligence pathways from weather to climate

arXiv:2610.09770v1 Announce Type: cross Abstract: Deep learning has made rapid advances in weather forecasting: autoregressive models trained on atmospheric reanalyses now rival dynamical models acros

Closing the Loop on Contrail Avoidance with Satellite Verification

arXiv:2610.09363v1 Announce Type: new Abstract: Contrails are the thin ice clouds that aircraft leave behind. They cause a large share of aviation's warming, and rerouting the few flights that produce

Denoising Blocks, Not Tokens: Efficient Compressed Continuous Diffusion with Branching Token Realization

arXiv:2610.09311v1 Announce Type: new Abstract: Diffusion language models (DLMs) generate text through iterative parallel refinement, offering the potential for higher throughput than autoregressive (

Expert Coupling in MoE Pretraining: Reducing All-to-All Overhead with Correlated Placement and Token Shuffling

arXiv:2610.09372v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) layers replace the feed-forward block of a Transformer with E expert networks, and each token is routed to k of these experts.

HE-OFT: Privacy-Preserving One-Shot Federated Fine-Tuning under Homomorphic Encryption

arXiv:2610.08255v1 Announce Type: cross Abstract: Many organizations adapt large pretrained models to their own tasks by fine-tuning on private data. Several of these parties often hold data for the s

NeuralZip: Reusable Setup for Fast Lossless Compression

arXiv:2610.09916v1 Announce Type: new Abstract: Lossless compression can reduce the storage and movement of model weights without changing their floating-point values, but repeated statistical analysi

PoreML: A Data-Driven Framework for Learning Multiphase Flow in Porous Media

arXiv:2610.10314v1 Announce Type: new Abstract: Multiphase flow in porous microstructures is central to CO_2 storage, fuel-cell operation, and flip-chip packaging. Predicting these flows remains chall

RealtimeWAM: How Fast Can I Run My World Action Model?

arXiv:2610.10079v1 Announce Type: new Abstract: World Action Models (WAMs) combine visual dynamics modeling with action generation, but their high inference latency limits responsive robot control. Re

hardwarearxiv-cs-ro

YANchor-4B: Effective Long-Horizon Reasoning in O(N) Time with O(1) Memory

arXiv:2610.10118v1 Announce Type: cross Abstract: Long-horizon reasoning demands access to earlier information at a manageable generation cost. Full-history attention incurs growing storage and comput

AEGIS: Runtime-Guided GPU Collocation for Multi-Tenant Deep Learning Training

arXiv:2508.19073v4 Announce Type: replace-cross Abstract: Deep learning training commonly runs on shared multi-tenant GPU servers, where exclusive allocation provides isolation but can leave resources

Can Power Draw Constrain Covert Compute? Limits of Analogue Verification for AI Governance

arXiv:2610.07476v1 Announce Type: cross Abstract: Frontier AI treaties or agreements on limiting computation require external verification; an external auditor must be able to confirm how much computa

Demo: Closed-Loop Sionna-Isaac Sim Co-Simulation Framework for Wireless-Aware Robot Navigation over ROS 2

arXiv:2610.08618v1 Announce Type: cross Abstract: A robot that offloads its control loop to the network carries the receiver with it, so link quality is decided by where it goes. Simulating this requi

hardwarearxiv-cs-ro

Demo: Vision-Language Model-Guided Online Calibration of an Electromagnetic Digital Twin

arXiv:2610.07081v1 Announce Type: cross Abstract: An electromagnetic (EM) digital twin gives mobile robots wireless situational awareness but depends on material conductivities that change with the en

Efficient Multimodal Inference through Adaptive Acquisition and Sequential Fusion

arXiv:2610.07466v1 Announce Type: new Abstract: Multimodal systems often encode every available input, even when a subset suffices for prediction. Adaptive acquisition can reduce this cost by using pr

Feature Space Analysis by Guided Diffusion Model

arXiv:2509.07936v3 Announce Type: replace Abstract: This paper aims to analyse the feature space of a vision-related Deep Neural Network (DNN) by proposing a decoder that can generate an image whose f

Forecast Accuracy Is Not Trading Profit: Evolving Small Recurrent Networks for Stock Return Prediction

arXiv:2610.07825v1 Announce Type: cross Abstract: Time series forecasting models are typically compared on pointwise error, which scores a prediction in isolation from the decision it is produced for,

Hybrid Latent Attention for Looped Language Models

arXiv:2610.07940v1 Announce Type: cross Abstract: Looped language models apply the same stack of layers T times to each token, which deepens the model without adding parameters but multiplies its key-

ScanSTL: Parallel Robustness Evaluation for Signal Temporal Logic

arXiv:2610.07346v1 Announce Type: new Abstract: Repeated evaluation and differentiation of Signal Temporal Logic (STL) robustness can become a computational bottleneck in robot planning and control. S

hardwarearxiv-cs-ro

T-CCL: Resource Efficient and Performant Collective Communication using Tensor Memory Accelerator

arXiv:2610.07098v1 Announce Type: cross Abstract: Large transformer-based models increasingly depend on multi-GPU execution, which requires frequent collective communication among GPUs. Existing commu

VisionWeave: Weaving Elastic Visual Representations as a Native Capability of MLLMs

arXiv:2610.07987v1 Announce Type: cross Abstract: Multimodal large language models have become the dominant paradigm for visual understanding, but incur substantial costs by encoding inputs into dense

Wikidata Search Traces: A Dataset for Training Knowledge Graph Search Agents

arXiv:2610.06650v2 Announce Type: replace Abstract: Wikidata is one of the largest open knowledge bases, yet answering a complex question over it still requires a SPARQL query that names the right ent

AffordCraft: Scalable Construction of Task-Ready Simulation Assets from Single Images

arXiv:2610.06643v1 Announce Type: cross Abstract: Robot learning in simulation depends on the objects the simulator offers. Many tasks need objects with separate parts, joints that allow the required

Answer Set Networks: Casting Answer Set Programming into Deep Learning

arXiv:2412.14814v2 Announce Type: replace-cross Abstract: Although Answer Set Programming (ASP) allows constraining neural-symbolic (NeSy) systems, its employment is hindered by the prohibitive costs

FedUHD: Unsupervised Federated Learning using In-Memory Hyperdimensional Computing

arXiv:2508.12021v2 Announce Type: replace Abstract: Unsupervised federated learning (UFL) enables privacy-preserving distributed training without data labeling, yet practical deployment remains challe

Frozen Factor or Spectral Band? Disentangling Two Choices in Low-Rank LoRA

arXiv:2610.06621v1 Announce Type: new Abstract: Spectral variants of low-rank adaptation (LoRA) choose both a subspace and which factor to freeze. We separate these choices by freezing the input facto

Image-Based Breast Implant Detection for Mammography Dataset Curation and Near-Real-Time Deployment: Comparing Foundation Models and Task-Specific Convolutional Models

arXiv:2610.03817v1 Announce Type: cross Abstract: Purpose: To evaluate the performance-feasibility tradeoffs of foundation models (FMs) and task-specific convolutional neural networks (CNNs) trained f

LogSig-SSM: Time-Series Modelling with Multi-Scale Log-Signature Compression for State-Space Models

arXiv:2610.05051v1 Announce Type: new Abstract: Time-series data are often sampled irregularly at high frequencies and exhibit long-range dependencies, which makes long-horizon modelling difficult. Co

MC-Sparse: Deconstructing and Closing the Dense-Sparse Attention Gap in Diffusion Transformers

arXiv:2610.06801v1 Announce Type: new Abstract: Sparse attention is a primary approach to reducing the latency of diffusion transformers in long-sequence generation tasks, such as video and high-resol

Measuring and Reducing Cross-Vendor Mismatch in Language Models

arXiv:2610.05458v1 Announce Type: new Abstract: Running the same language model on different graphics processing unit (GPU) vendors can produce different logits, even when the model weights and inputs

MetaKernelBench: Measuring GPU Kernel Knowledge Transfer Beyond Code

arXiv:2610.05014v1 Announce Type: new Abstract: Recent GPU kernel optimization agents retain what they learn in knowledge bases or as distilled skills. Kernel benchmarks score each attempt's implement

PhysMamba: Selective State Space Models as Learned Articulated Body Simulators

arXiv:2610.04014v1 Announce Type: new Abstract: We introduce the first learned articulated body simulator based on a selective state space model (SSM), called PhysMamba. PhysMamba predicts next-frame

RESOLVE: Language-Agnostic Validation of GPU Kernels Through Testing, Reduction, and Proof

arXiv:2610.05683v1 Announce Type: cross Abstract: AI systems can now write and optimize production GPU kernels, but validating them remains an important challenge. Evaluating the kernel on a few rando

Rethinking Least-Core Computation in Contextual-Distractor Games

arXiv:2610.06087v1 Announce Type: new Abstract: Game-theoretic attribution explains a model by assigning credit to its features or training examples. The least core has attracted interest as an altern

Model Releases

Saying, Not Knowing: Aggressively GGUF-Quantized Small Language Models Still Write Rare Words They Can No Longer Define

model-releasesarxiv-cs-lg

arXiv:2610.04403v1 Announce Type: cross Abstract: Post-training quantization to the GGUF format's mixed-precision K-quants is commonly how open-weight language models reach consumer hardware, yet its

Static Bootstrap Placement for Encrypted Language Model Decoding

arXiv:2610.04912v1 Announce Type: cross Abstract: Language models increasingly serve prompts that carry private data, and secure inference under homomorphic encryption lets a client outsource the comp

Super-Resolution in The Right Latent Space: A Frozen Vision-Foundation Substrate

arXiv:2610.04781v1 Announce Type: new Abstract: In an image latent space, the embeddings of high-resolution, natural, and sharp images form a manifold. Degradation of high-resolution images pushes the

Vision Transformer Ensembles for Panoramic Street Segmentation

arXiv:2610.06063v1 Announce Type: new Abstract: Semantic segmentation of street panoramas can support detailed descriptions of urban environments, yet small datasets and unequal training costs make mo

Batched Speech Decisions Without Decoding: Single-Token Supervision Lets a Frozen LLM Hear Beyond the Transcript

arXiv:2610.02638v1 Announce Type: new Abstract: Full-duplex voice agents make many small, closed decisions, which current systems answer by slow autoregressive decoding. We propose DuplexJev, which fe

DyRA: Dynamic Residual Approximation for Efficient Matrix Multiplication in DNNs

arXiv:2610.02882v1 Announce Type: cross Abstract: Large-scale foundation models achieve strong performance across diverse tasks, but their size makes inference costly, largely due to dense matrix mult

Efficient Memory Crystallization for Graph Learning under Non-Stationary Distribution Shifts

arXiv:2610.02795v1 Announce Type: new Abstract: Deep graph learning models deployed in real-world systems often need to cope with non-stationary environments, where the underlying graph distribution d

FlashSinkhorn 2: Block-Sparse Entropic Optimal Transport

arXiv:2610.02395v1 Announce Type: new Abstract: Streaming GPU solvers for entropic optimal transport (EOT), such as FlashSinkhorn, avoid storing the dense kernel but still evaluate all nimes m point p

I2CD: Direct Image-to-Convex Decomposition for Simulation-Ready Collision Geometry

arXiv:2610.03453v1 Announce Type: cross Abstract: Physics simulators and motion planners require convex collision geometry, yet image-to-3D generative models output dense, frequently non-manifold visu