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OncoNoteBERT: A Foundation Representation Model for Natural Language Processing of Real-World Outpatient Oncology Notes

arXiv:2610.03829v1 Announce Type: cross Abstract: Real-world outpatient oncology notes contain specialised terminology, tumour staging expressions, treatment names, toxicity descriptions, and institut

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One-Cycle Fault Classification and Faulted-Line Identification on the PROTECT-90 Dataset: An Initial Application Benchmark

DGX agent

arXiv:2610.04155v1 Announce Type: cross Abstract: Open electromagnetic-transient datasets are beginning to make reproducible learning-based protection studies possible, but the practical use of these

model-releasesarxiv-cs-lg

6 Oct 2026

One Figure, Every Canvas: Editable Flowchart Relayout via Agentic Pipeline

model-releasesarxiv-cs-cv

arXiv:2610.06852v1 Announce Type: new Abstract: Pipeline figures in ML papers must be repurposed across many canvases, including paper columns, 16:9 slides, portrait posters, 1:1 social teasers, 9:16

One-Step Curvature Probes Miss the Fitting Operator: Retained Capacity and Terminal Null-Space Correction for Continual Learning

arXiv:2610.03952v1 Announce Type: new Abstract: A one-step curvature probe evaluates an initial direction, whereas continual learners are judged after reaching comparable new-task fit. In an overparam

One-Step Generation via Riemannian Wasserstein Gradient Flows

arXiv:2610.04454v1 Announce Type: new Abstract: Recently, Drifting Models and Wasserstein Gradient Flows have attracted substantial attention because they move iterative distributional refinement to t

One Tile, Multiple Instances: Rethinking MIL for Sparse Diagnostic Evidence

arXiv:2610.04853v1 Announce Type: new Abstract: In weakly supervised Whole Slide Image (WSI) classification, feature extractors typically compress each image tile into a single global embedding. Conse

One Token Can Be Enough: Bridging Prompting and Activation Steering with Prefix Steering

arXiv:2610.04967v1 Announce Type: new Abstract: Prompting guides language model behavior through the initial context, whereas activation steering often intervenes throughout generation. A natural ques

tutorialsarxiv-cs-lg

Online AutoML: Evaluating Poisoning Attacks on Adversarial Training Defense Strategy in IoT Networks

arXiv:2610.05810v1 Announce Type: cross Abstract: Machine learning (ML)-powered poisoning attack vectors are adversarial maneuvers whereby an attacker intentionally inserts, corrupts, or alters traini

Online Control via Counterfactual Tracking

arXiv:2607.13029v2 Announce Type: cross Abstract: We study online control of a known linear dynamical system with adversarial costs and bounded disturbances, measuring regret against a general class o

Online Linear Programming with Batching

arXiv:2408.00310v2 Announce Type: replace Abstract: We study Online Linear Programming (OLP) with batching. The planning horizon is cut into K batches, and decisions on orders can be delayed to the en

Online Target-less Radar-LiDAR-Camera Extrinsic Calibration via Joint Optimization

arXiv:2610.04552v1 Announce Type: new Abstract: Fusing radar, LiDAR, and camera enables robust perception in diverse and adverse conditions, but the fusion performance critically depends on accurate e

researcharxiv-cs-ro

Only Project Once: Projection-Adaptive Loss for Exact Constraint Satisfaction

arXiv:2610.04572v1 Announce Type: new Abstract: Precise constraint satisfaction is a prerequisite to deploying learned models in many areas, motivating methods that repair raw neural predictions with

Ontology Concept Overlap as a Training Signal: Knowledge-Grounded Reinforcement Learning for Clinical Question Answering

arXiv:2610.06360v1 Announce Type: cross Abstract: Reinforcement learning post-training for language models relies on two reward designs: human preferences (RLHF, DPO) and binary verifiers (RLVR). Clin

Open-World Panoptic Segmentation

model-releasesarxiv-cs-cv

arXiv:2412.12740v2 Announce Type: replace Abstract: Robots need to be able to understand their surroundings in order to operate safely and robustly, and to interact with the surrounding environment. R

Operational Abstractions of Neural Network Concepts via Topological Representations

arXiv:2610.05017v1 Announce Type: new Abstract: Concept-based methods provide a semantic level for interpreting and manipulating learned representations, but existing editing approaches are typically

Optimal Control with Learned Critics under Unmodeled State Dependencies

arXiv:2610.05359v1 Announce Type: new Abstract: Model Predictive Control (MPC) provides a structured and constraint-aware mechanism for decision-making, but its reliance on optimization-friendly analy

local-aiarxiv-cs-ro

Optimal Oracle Complexity for Finite-Sum Monotone Inclusions

arXiv:2610.05038v1 Announce Type: cross Abstract: We present an oracle-optimal method for finite-sum monotone inclusions under mean-square Lipschitz continuity. Our switching regularization method fin

Optimizer Geometry Sets the Pace: Spectral Learning Dynamics in Matrix Factorization

arXiv:2610.04249v1 Announce Type: new Abstract: Recent successes of matrix- and curvature-based optimizers have renewed interest in how update geometry shapes learning. These methods normalize or prec

Optimizing Breast Cancer Detection in Mammograms: A Comprehensive Study of Transfer Learning, Resolution Reduction, and Multi-View Classification

arXiv:2503.19945v4 Announce Type: replace-cross Abstract: Mammography, an X-ray-based imaging technique, remains central to the early detection of breast cancer. Recent advances in artificial intellig

tutorialsarxiv-cs-cv

ORCA: The Annealed Spectral Conditioning Optimizer for Faster, Better LLM Training

arXiv:2610.06116v1 Announce Type: new Abstract: Modern LLM optimizers such as Muon often produce weight matrices with higher effective rank than Adam, yet further spectral control has delivered only m

Orchestrating Level-K Policies Against Unknown Opponents in Partially-Observable Dynamic Games

arXiv:2610.04937v1 Announce Type: cross Abstract: Level-K reasoning generates a hierarchy of policies specialized to opponents with different reasoning levels. When an opponent's level is unknown, a c

Order Matters: Competition-Guided Query Ordering for RNN-Based Object Detection

arXiv:2610.05191v1 Announce Type: new Abstract: DETR-style detectors use one-to-one bipartite matching during training to assign object queries to ground-truth objects, enabling end-to-end set predict

Ordinary Least Squares as an Attention Mechanism

arXiv:2504.09663v3 Announce Type: replace Abstract: I show that ordinary least squares (OLS) predictions can be rewritten as the output of a restricted attention module, akin to those forming the back

Organize Primitives into Semantic Parts: Reinforcement Reasoning for 3D Segmentation

arXiv:2610.04602v1 Announce Type: new Abstract: Primitive-based 3D segmentation offers a compact and explicit alternative to dense surface prediction, naturally supporting structural abstraction and b

local-aiarxiv-cs-cv

Out-of-control Hamiltonian Learning

arXiv:2610.06709v1 Announce Type: cross Abstract: Learning the Hamiltonian of a many-body system from its dynamics is a central task in quantum science, yet the algorithms with the strongest provable

tutorialsarxiv-cs-lg

Outcome-Guided On-Policy Self-Distillation

arXiv:2610.05070v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) provides denser token-level supervision and better computational efficiency than Reinforcement Learning with Verifiab

OVAL: Output-Aware Local Page Bases for KV Cache Retrieval

arXiv:2610.06686v1 Announce Type: new Abstract: Long context inference with large language models becomes increasingly expensive as attention must operate over an ever growing KV cache. Page sparse at

P3: Persistent Particle Planning for Constrained Diffusion Control

arXiv:2610.06002v1 Announce Type: cross Abstract: Diffusion models provide expressive priors over trajectories, but adapting these priors to test-time constraints requires maintaining feasibility and

PACMI: Provenance-Aware Cascading Memory Invalidation for Long-Term LLM Agents

arXiv:2610.05732v1 Announce Type: new Abstract: LLM agents rely on long-term memory to retain and reuse information when performing tasks over long horizons. Existing methods provide limited support f

PaLoRA: Paced Low-Rank Adaptation for Continual Learning

arXiv:2610.04226v1 Announce Type: new Abstract: LoRA-based continual learning methods mitigate catastrophic forgetting through various mechanisms, yet nearly all complement these with small learning r

Paradee: Distilling Kokoro-82M into an 8M-Parameter Single-Voice Text-to-Speech Model

arXiv:2610.06817v1 Announce Type: cross Abstract: We distill Kokoro-82M, a widely used open text-to-speech model with 54 voices, into Paradee, an 8.07M-parameter model that speaks one of them. Paradee

Parameter Estimation in Machining Dynamics with Regenerative Delay and Nonsmooth Friction using Physics-Informed Neural Networks

arXiv:2610.06230v1 Announce Type: new Abstract: A multi-domain eXtended Physics-Informed Neural Network (XPINN) framework is developed for nonsmooth Delay Differential Equations (DDEs). This is the fi

Agents

Pareto-Dominant Clarification: Post-Training Coding LLMs via PPO-Lagrangian Budget Constraints

arXiv:2610.04089v1 Announce Type: new Abstract: Coding agents operating under ambiguous instructions or user prompts must decide whether to ask clarifying questions or attempt a solution directly. Whi

agentsarxiv-cs-lg

Pareto-Improving Adversarial Attacks with Primal-Dual Regularization

arXiv:2610.04652v1 Announce Type: new Abstract: Transferable adversarial attacks are arguably the most practical black-box threat model. Under the same perturbation budget, stronger transfer attacks a

Applications

Patch-based Querying Identifies Structures of Interest in Electron Microscopy

arXiv:2610.06020v1 Announce Type: new Abstract: Volume electron microscopy (vEM) has emerged as an essential sensing technique in biomedical research, allowing the three-dimensional imaging of biologi

applicationsarxiv-cs-cv

Path Laplacian Encodings for Directed Graphs

arXiv:2610.04657v1 Announce Type: new Abstract: Directed graphs naturally model many real-world systems in which interactions are asymmetric, such as citation networks, web graphs, and information-flo

PatternDex: Learning Interaction Patterns to Guide Reinforcement Learning of Bimanual Dexterous Manipulation of Articulated Objects

arXiv:2610.04765v1 Announce Type: new Abstract: In this paper, we develop a method that enables bimanual dexterous hands to manipulate articulated objects with a high success rate without suffering fr

Pay to Learn, Share to Earn: Incentivized Federated Multi-Player Bandits

arXiv:2610.06062v1 Announce Type: new Abstract: Federated multi-player multi-armed bandit problems model collaborative sequential decision-making where multiple players interact with a common bandit e

tutorialsarxiv-cs-lg

PB-STDG: A Prediction-Based Short-Term Decentralized Greedy Guidance Algorithm for a Drone Road System

arXiv:2610.05122v1 Announce Type: new Abstract: In recent years, Unmanned Aerial Vehicles (UAVs) or drones have been increasingly adopted in urban environments for applications such as parcel delivery

PCLM: Small-target localization with frozen CLIP via prototype contrast and local magnification

arXiv:2610.05115v1 Announce Type: new Abstract: Small targets occupy few patches in a vision-language encoder, so spatial features often mix object appearance with surrounding content. We propose Prot

PDE-SSM: A Spectral State Space Approach to Spatial Mixing in Diffusion Transformers

arXiv:2603.13663v2 Announce Type: replace Abstract: The success of vision transformers-especially for generative modeling-is limited by the quadratic cost and weak spatial inductive bias of self-atten

PerCoV2: Ultra-Low Bit-Rate Perceptual Image Compression via Query-Based 1D Multimodal Image Tokens

arXiv:2503.09368v2 Announce Type: replace Abstract: Despite recent progress in learned image compression, current image codecs still struggle to maintain realistic reconstructions at low bit-rates, of

Periscope: Extending Frozen Language Models Beyond Their Context Window

arXiv:2610.04047v1 Announce Type: cross Abstract: A language model reads long text in one quadratic forward pass, stops at the context window, and loses accuracy with length before reaching it. We ask

PermVLA: Factorization Order as a Regularizer for VLA Learning

arXiv:2610.04659v1 Announce Type: cross Abstract: Vision-language-action (VLA) policies commonly learn action chunks through a fixed left-to-right (LTR) factorization, although the same expert traject

Personal VAD: Speaker-Conditioned Voice Activity Detection

arXiv:1908.04284v5 Announce Type: replace-cross Abstract: In this paper, we propose 'personal VAD', a system to detect the voice activity of a target speaker at the frame level. This system is useful

local-aiarxiv-cs-lg

PerturBot: Breaking Shortcut Priors in Vision-Language-Action Models with Perturbative Training

arXiv:2610.04616v1 Announce Type: cross Abstract: A vision--language--action (VLA) policy can complete complex tasks while ignoring the evidence that should determine its actions. An object held near

safetyarxiv-cs-cv

Pessimistic Minimax Learning for Public-Private Information Games under Unilateral Coverage

arXiv:2610.04997v1 Announce Type: new Abstract: We study offline learning in two-player zero-sum contextual games with public and private information, motivated by strategic settings such as auctions

PhaseGate: Phase-Aware CPU Retrieval Scheduling for On-Device LLMs on Unified Memory

arXiv:2610.04537v1 Announce Type: new Abstract: On-device assistants run GPU-based LLM inference alongside CPU retrieval on unified-memory systems. Under a saturated local-retrieval workload, four con

local-aiarxiv-cs-lg