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Inverting Multi-Vector Visual Document Indices

arXiv:2610.09920v1 Announce Type: cross Abstract: Prevailing multi-vector visual document retrievers store each page as about a thousand patch vectors, often in vector databases run by a third party.

Iris-3B: Going Beyond the Latent with Pixel-Space Diffusion Training, Conversion and Fine-Tuning

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DGX agent

arXiv:2610.09450v1 Announce Type: new Abstract: Pixel-space diffusion models avoid the lossy VAE of latent models, which suggests an advantage on downstream tasks where fine-grained detail matters. We

model-releasesarxiv-cs-cv

8 Oct 2026

Is Word Error Rate Enough? Rethinking Privacy Evaluation in Speech with Entity-Aware Metrics

arXiv:2610.08831v1 Announce Type: cross Abstract: As the use of smart devices continues to increase, their potential to capture sensitive speech content raises growing privacy concerns. It is therefor

safetyarxiv-cs-cl

It Is Not Seeing the Hazard: A Frozen Vision-Language Safety Score Measures Its Caption Bank

arXiv:2610.09517v1 Announce Type: new Abstract: Frozen vision-language models increasingly provide safety signals for reinforcement learning. Their use assumes that similarity to language describing d

safetyarxiv-cs-cv

Itgan at NADI 2026 shared task: Parameter-Efficient Whisper Adaptation for Robust, Mixed-Dialect and Code-Switched Arabic ASR

arXiv:2610.09934v1 Announce Type: new Abstract: We describe the Itgan systems for the three ASR subtasks of NADI 2026, namely robust country-level ASR (1.1), mixed-dialect ASR (1.2), and Tunisian code

Agents

IVG-UAV: An Intelligent Voice-Guided UAV System for Autonomous Ripe Fruit Harvesting with Vision-Based Classification and Adaptive Path Planning

arXiv:2610.09398v1 Announce Type: new Abstract: In tropical regions, their agricultural sectors remain highly dependent on manual labor for fruit harvesting. On large-scale farms, this dependency ofte

agentsarxiv-cs-ro

Judging in Latent Space: Efficient Generative Reward Modeling via Semantics-Preserving Compression

arXiv:2610.09788v1 Announce Type: new Abstract: Reward modeling often requires jointly representing and reasoning over multiple evaluation criteria, yet verbalizing this process token by token can inc

Juno: Taming Predictive Latents for Vision-Language-Action Models

arXiv:2610.09940v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) predict masked or future observations in representation space, offering a natural source of predictiv

safetyarxiv-cs-cv

Just for FUNS: LLM-Guided Spatio-Temporal Graph Node Generation for Forecasting Unobserved Node States

arXiv:2610.08818v1 Announce Type: cross Abstract: Spatio-temporal forecasting is a cornerstone of logistics, urban planning, and intelligent transportation systems. However, constrained by deployment

KASALv2: Fully Automatic 3D Rotational Symmetry Classification and Axis Localization

arXiv:2610.09534v1 Announce Type: new Abstract: Rotational symmetry is an important prior in 6D pose estimation, improving pose accuracy and supporting symmetry-aware evaluation. However, current symm

applicationsarxiv-cs-cv

Kernel Autoresearch for Open-Ended Model Discovery

arXiv:2610.10394v1 Announce Type: new Abstract: Kernels encode the inductive bias of a wide range of machine learning models, yet automated kernel design faces a fundamental dilemma. A fixed grammar o

safetyarxiv-cs-lg

KGATE : a Knowledge Graph Embedding Training Environment

arXiv:2610.09927v1 Announce Type: new Abstract: Knowledge graph embedding (KGE) models encode the entities and relations of a knowledge graph into a low-dimensional latent space, enabling tasks such a

Kinetic Langevin Meets Split Gibbs: Accelerated Posterior Sampling for Imaging Inverse Problems with Diffusion Priors

arXiv:2610.10187v1 Announce Type: cross Abstract: Split Gibbs sampling (SGS) is a popular framework for posterior sampling in Bayesian imaging inverse problems. It decouples a Gaussian data-fidelity t

Koopman Observers for Diffusion Acceleration: Correcting Feature Forecasts with Shallow Measurements

arXiv:2610.10366v1 Announce Type: new Abstract: Feature caching accelerates diffusion sampling by replacing expensive network evaluations with predictions from previously computed activations. However

Kuration SDK: Addressing the Virtual2Real Gap via Data Curation

arXiv:2610.09305v1 Announce Type: cross Abstract: Benchmarks for measuring the quality of action-conditioned world models are still evolving and shifting away from visual similarity-based metrics to a

researcharxiv-cs-cv

KVFetch: Temporal Prefetching for the Missing Half of KV Cache Compression

arXiv:2610.08811v1 Announce Type: new Abstract: As context windows scale to tens or hundreds of thousands of tokens, KV cache compression has become essential for efficient LLM inference. Existing met

Label-free cell counting and viability prediction with brightfield imaging and deep learning

arXiv:2610.10473v1 Announce Type: new Abstract: Cell viability assessment is a core requirement in cell culture systems, with critical applications in biopharmaceutical manufacturing and drug developm

LACE-CRAFT: Robot Co-Design with Actor Inheritance and Blackboard Collaboration

arXiv:2610.09283v1 Announce Type: new Abstract: Robot co-design couples morphology search with policy learning, yet training every new design from scratch discards acquired control experience. We pres

safetyarxiv-cs-ro

Large-scale Repository Engineering via Agent-Native Reusable Code Primitives

arXiv:2610.09079v1 Announce Type: cross Abstract: Large language models equipped with development environments have moved code generation toward repository-scale construction, yet building complete re

LASER: Latent Space Adjoint Matching for Support-Constrained Entropy-Regularized Offline RL

arXiv:2610.08989v1 Announce Type: new Abstract: While offline reinforcement learning (RL) enables policy optimization from static datasets without costly online interaction, it remains bottlenecked by

safetyarxiv-cs-lg

Latent Watermarks under Generative Editing: A Benchmark and Analysis of Detection Survival

arXiv:2610.09702v1 Announce Type: new Abstract: Ordinary prompt-based editing can cause latent watermark detection to fail without explicitly targeting the watermark. We benchmark eight watermark meth

LayerRoPE: Dynamic Depth-wise Magnitude & Angular Superposition

arXiv:2610.09179v1 Announce Type: cross Abstract: As data propagates through a Transformer, the norm of its hidden states grows by orders of magnitude with depth, a phenomenon framed as 'curse of dept

Layerwise Error Attribution for Fast and Robust Mixed-Precision Post-Training Quantization

arXiv:2610.09877v1 Announce Type: new Abstract: Mixed-precision post-training quantization is a network compression method that assigns bits layer by layer, under a global memory budget using a small

Tutorials

Leaner Transformers Can Easily Learn to Cluster

arXiv:2610.09760v1 Announce Type: new Abstract: Transformers have in-context learning capabilities, where some known learning algorithms can be executed in the forward pass through the model. Recent w

tutorialsarxiv-cs-lg

Learned Monotone Recurrent Features in Governed Credit Scoring: The Price of the Frame and the Necessity of Macro Conditioning

arXiv:2610.08869v1 Announce Type: cross Abstract: Regulated credit scoring requires scores monotone non-decreasing in every exposure input. Deployed pipelines -- hand-crafted monotone aggregates feedi

applicationsarxiv-cs-lg

Learning Cross-Model Activation Alignments with Explicit Many-to-Many Layer Maps

arXiv:2610.09058v1 Announce Type: new Abstract: LLMs are released at a rapid pace, raising a natural question: how do two independently trained models relate, both in which layers correspond and in ho

Learning in the Recurrent State: Gradient Descent with Linear Recurrent Networks

arXiv:2410.11687v4 Announce Type: replace Abstract: In-context learning lets a sequence model adapt to a new task from examples in its input. A prominent line of work shows how self-attention can be c

safetyarxiv-cs-lg

Learning joint probabilistic weather forecasts from station observations alone

arXiv:2610.09898v1 Announce Type: cross Abstract: Assessing compound weather risks requires forecasts representing dependence between variables. CLARA (Calibrated Advection-Routing Attention) learns j

Learning Situation-Conditioned Thinking Policies for Long-Term LLM Agents

model-releasesarxiv-cs-ro

arXiv:2610.09590v1 Announce Type: cross Abstract: Long-running autonomous agents must reuse accumulated reasoning experience without allowing explicit historical memory and LLM context to grow indefin

Learning to Act with Task Progress: Distilling Small Agents from Compact Teacher Supervision

arXiv:2610.10332v1 Announce Type: new Abstract: Learning from large-model demonstrations offers a way to train small agents that can complete recurring tasks without calling a large model at every ste

Learning Traffic Flow Dynamics with Stochastic Physics-Informed Neural Cellular Automata

arXiv:2610.09946v1 Announce Type: new Abstract: Traffic flow modeling is essential for understanding and predicting the collective dynamics of vehicles on road networks. Cellular automata provide a si

Learning Transition Kernels of Jump-Diffusion Processes with Conditional Diffusion Models

arXiv:2610.09045v1 Announce Type: cross Abstract: We study the problem of learning transition kernels for time-homogeneous jump-diffusion processes using conditional diffusion models, with the goal of

Learning Unknown Constraints without Unsafe Data via Optimality and Counterfactual Regularization

arXiv:2610.09350v1 Announce Type: cross Abstract: Learning from demonstrations (LfD) provides a framework for inferring unknown constraints from locally optimal, constraint-satisfying expert behavior.

LeCuration: A Tiny World Model as a Data Curation Multi-Tool

arXiv:2610.09285v1 Announce Type: cross Abstract: Many applications of physical AI run within finite or closed physical worlds with a limited set of physical laws governing object behavior. Examples i

applicationsarxiv-cs-cv

Leveraging LLM-Generated Explanations for Detecting Emotionally Rewritten Fake News

arXiv:2610.08835v1 Announce Type: new Abstract: The spread of fake news may cause severe social consequences. Existing fake news detection methods mainly focus on stylistic variations or incorporate e

Lifelong small-object navigation in changing object layouts: a benchmark and method

arXiv:2610.10125v1 Announce Type: cross Abstract: Household robots need to continually navigate to different objects in the same environment, many of which are small and portable, such as tools and to

LiG-DETR: Local-in-Global Reassembly in Latent Space for Aerial Object Detection

arXiv:2610.09511v1 Announce Type: new Abstract: Aerial object detection faces substantial scale and density variations. Small objects are easily degraded by downsampling and feature compression, while

Local Ai

LighTROcc: Lightweight 4D Occupancy Forecasting via Instance-Centric 3D Gaussians

arXiv:2610.09444v1 Announce Type: new Abstract: Forecasting future 3D occupancy from surround-view cameras is essential for autonomous driving, yet existing approaches rely on dense voxel or bird's-ey

local-aiarxiv-cs-cv

Lightweight and Versatile Learned Optimization by Recombination of Gradient History

arXiv:2610.09604v1 Announce Type: new Abstract: This paper presents a lightweight and versatile learned optimizer that dynamically recombines gradient history, represented as averages over disjoint ti

LiveMACE: Process-Aware Evaluation of LLM Agent Capabilities in Evolving Markets

arXiv:2610.09872v1 Announce Type: cross Abstract: Evaluating agents by outcomes alone can obscure the capabilities that produce them. This problem is especially pronounced in evolving environments, wh

Hardware

LLA-MPPI: Rapidly Adaptive Whole-body Control of Legged Robots with GPU-Accelerated Parallel Simulations

arXiv:2610.10465v1 Announce Type: new Abstract: Real-time whole-body controllers for legged robots typically plan through a fixed nominal model and degrade when the deployed dynamics change. Adaptive

hardwarearxiv-cs-ro

LLM Persuasion Is in the Eye of the Evaluation

arXiv:2610.10232v1 Announce Type: new Abstract: Large language models (LLMs) have already been shown to match or exceed human experts in persuasion. While their persuasive capabilities hold promise fo

applicationsarxiv-cs-cl

LLM4Impact: Integrating Heterogeneous Information for Scientific Impact Prediction

arXiv:2610.10138v1 Announce Type: new Abstract: Predicting the future impact of a newly published paper is challenging because it must be inferred from heterogeneous evidence available at publication

Logarithmic Regret via Passive Change Detection in Piecewise-Stationary Self-Tuning Regulation

arXiv:2610.10250v1 Announce Type: new Abstract: We study minimum-variance control of an unknown autoregressive system with exogenous inputs and coefficients that change at unknown times. Under bounded

LoGRA: Scaling LLM Reinforcement Learning with Low-Rank Gradient Sketches

arXiv:2610.06647v2 Announce Type: replace Abstract: Reinforcement learning has greatly advanced the capabilities of large language models, but its memory demands remain a barrier to broader adoption.

Local Ai

Long-WAM: Scaling the Context of World-Action Models

arXiv:2610.10528v1 Announce Type: cross Abstract: Real-time robot control demands enough visual history to infer motion and task progress, but processing that history can delay action. We present Long

local-aiarxiv-cs-cv

LoomSC: Scalable Deep Subspace Clustering with Projector Factorization and Exact Spectral Reduction

arXiv:2610.10266v1 Announce Type: new Abstract: Dense self-expression matrices and full-affinity spectral clustering limit the scalability of subspace clustering. We introduce the Latent Orthogonal Op

researcharxiv-cs-cv

Lower Bounds for Parallel Diffusion Sampling

arXiv:2610.09166v1 Announce Type: cross Abstract: Standard diffusion samplers generate samples through repeated evaluations of a learned score function. Parallel sampling methods seek to accelerate ge