Search: “concepts”

BaT-SAM: Introducing Inductive Bias into SAM via a Mixture of Convolutional Experts for Brain Tumor Segmentation

arXiv:2610.15330v1 Announce Type: new Abstract: Accurate brain tumor segmentation from magnetic resonance imaging (MRI) is essential for diagnosis and treatment planning; however, manual delineation i

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Research

Bayesian Test-Time Inference of Task-Aligned Similarity from Weak Interactive Feedback

DGX agent

arXiv:2610.18656v1 Announce Type: new Abstract: Language model systems repeatedly make test-time decisions by comparing similarity: they retrieve exemplars, rank candidates, and revise responses. Yet

researcharxiv-cs-lg

14 Oct 2026

Applications

HGA-Quant: Heterogeneity-Aware Quantization for AutoRegressive Visual Generation Models

arXiv:2610.15297v1 Announce Type: new Abstract: Recently, AutoRegressive Visual Generation (ARVG) models have emerged as a competitive paradigm for high-quality image synthesis. However, their substan

applicationsarxiv-cs-cv

Integrating 3D Posture Neutralization with Statistical Shape Modeling for Head-Neck-Shoulder Ergonomic Design

arXiv:2610.17671v1 Announce Type: cross Abstract: The design of ergonomic products and workspaces requires a deep understanding of human anatomy and posture. In particular, the head-neck-shoulder regi

Know-Thy-Not: Training-Free Targeted Negation in Dual-Encoder Vision-Language Models

arXiv:2610.17440v1 Announce Type: new Abstract: Dual-encoder vision-language models systematically fail at negation, scoring ''a cat without a dog'' nearly identically to ''a cat with a dog.'' We show

Tutorials

Learning to Detect Shifts in Unstructured Data Streams via Monitoring-by-Betting

arXiv:2610.17399v1 Announce Type: new Abstract: Continuous monitoring of generative AI systems requires detecting distribution shifts in the unstructured data they ingest and generate. Existing monito

tutorialsarxiv-cs-lg

mathbf{S^2LM}: Towards Semantic Steganography via Large Language Models

arXiv:2511.05319v3 Announce Type: replace Abstract: Despite remarkable progress in steganography, embedding sentence-level information into cover media remains challenging. In this work, we present th

Local Ai

NoduleFlow: Automatic 3D Lung Nodule Detection and Segmentation

arXiv:2610.16548v1 Announce Type: new Abstract: Low dose Computed Tomography (CT) is the standard imaging modality for lung cancer screening. On CT scans, lung cancer typically manifests as pulmonary

local-aiarxiv-cs-cv

On Collusion-Free Teaching in Planar Graphs

arXiv:2610.18714v1 Announce Type: cross Abstract: Non-clashing teaching minimizes teaching complexity among models satisfying the Goldman--Mathias collusion-avoidance criterion. While the Vapnik--Cher

Probing and Inducing Clinical Modality Grounding in Brain Tumor Segmentation

arXiv:2603.19844v3 Announce Type: replace Abstract: Multimodal MRI provides complementary information for brain tumor segmentation, but high accuracy alone does not reveal whether a model relies on cl

Q-Save: Towards Scoring and Attribution for Generated Video Evaluation

arXiv:2511.18825v3 Announce Type: replace Abstract: Evaluating AI-generated video (AIGV) quality hinges on three crucial dimensions: visual quality, dynamic quality, and text-video alignment. While nu

QK-Edit: Revisiting Attention-based Injection in MM-DiT for Image and Video Editing

arXiv:2610.17829v1 Announce Type: new Abstract: Multimodal Diffusion Transformers (MM-DiTs) have recently emerged as a powerful framework for unified text-vision synthesis, surpassing traditional U-Ne

Sea-Net: A Small and Inherently Interpretable Neural Network for Time Series Classification

arXiv:2610.17939v1 Announce Type: cross Abstract: Traditional time-series classification methods often operate as black boxes, providing a class prediction without indicating which time point or time

Agents

SHRUMS: Sensor Hallucination for Real-time Underwater Motion Planning with a Compact 3D Sonar

arXiv:2510.18996v2 Announce Type: replace Abstract: Autonomous navigation in 3D is a fundamental problem for autonomy. Despite major advancements in terrestrial and aerial settings due to improved ran

agentsarxiv-cs-ro

Tutorials

Siam-ALS: An Explainable Siamese Deep Learning Framework for Early ALS Detection Using EEG and Eye-Tracking Signals

arXiv:2610.15351v1 Announce Type: new Abstract: Amyotrophic lateral sclerosis (ALS) diagnosis remains challenging due to heterogeneous symptoms and reliance on clinical assessment, underscoring the ne

tutorialsarxiv-cs-lg

Taking Krea-2 apart, one piece at a time

model-releasesr-stablediffusion

Hellow fellow AI-generated goblins of r/StableDiffusion For a few weeks I’ve been stress-testing my tool, Arthemy Krea-2 Tuner: https://github.com/aledelpho/comfyui-arthemy-krea2-tuner I wanted to inv

When Do Learned Blocks Preserve Causal Meaning? Block Identifiability and Constructive Causal Abstractions

arXiv:2610.18155v1 Announce Type: new Abstract: Standard identifiability theory assumes one-dimensional latent factors, but learned representations can encode latent information across multidimensiona

Local Ai

From 1,000s of raw images to a training-ready dataset — pixel-curator (similarity training curation tool)

local-air-stablediffusion

pixel-curator — curation tooling for similarity training (identity, subject, and style models) Repo: https://github.com/snoozey-mf-bnui/pixel-curator What it is pixel-curator is a local-first CLI that

13 Oct 2026

Localized Generative Design of Ship Hulls with Diffusion Models and High-Fidelity Assessment

model-releasesarxiv-cs-ai

arXiv:2610.12870v1 Announce Type: cross Abstract: Practical ship design requires localized refinement and performance evaluation. This paper presents a reward-directed diffusion framework for localize

12 Oct 2026

Neural networks are more modular than single neurons suggest

arXiv:2610.12842v1 Announce Type: new Abstract: Neural networks routinely develop representations in which individual neurons contribute to multiple distinct functions, leading to the widespread view

12 Oct 2026

A Structural Theory of Cognitive Representation and Problem Solving,Contexts, Invariance, and the Knowledge Space

arXiv:2610.12306v1 Announce Type: new Abstract: Learning and problem solving depend critically on the structure of internal representations. While many modern data-driven artificial systems achieve st

9 Oct 2026

From Sparse Representations to Behavioral Insights for Multimodal Depression Assessment

arXiv:2610.11787v1 Announce Type: new Abstract: Multimodal depression assessment offers a promising approach to analyzing behavioral patterns associated with depression. However, existing methods ofte

researcharxiv-cs-cl

9 Oct 2026

A conceptual framework for ideology in online discourse beyond the left and right

arXiv:2603.18945v2 Announce Type: replace-cross Abstract: Computational social science (CSS) has largely operationalized ideology along a single left/right partisan axis when studying online discourse

researcharxiv-cs-cl

Agents

Had fun nerding out on the @_odsc AI podcast about: • Building in public as both market diligence and a way to meet founders • Jev experimen…

Had fun nerding out on the @_odsc AI podcast about: • Building in public as both market diligence and a way to meet founders • Jev experiments: knowledge graphs, relevance filters, and emotional blobs

agentsyohei-nakajima--x

sk-bench: A Native-First Benchmark for Evaluating Large Language Models in Slovak

model-releasesarxiv-cs-cl

arXiv:2610.09152v1 Announce Type: new Abstract: Multilingual LLM benchmarks omit Slovak, a morphologically rich West Slavic language of five million speakers, or cover it only by machine translation.

Validity Without Ground Truth: What Stated-Preference Economics Offers the Evaluation of Language Models

arXiv:2610.10506v1 Announce Type: cross Abstract: Many of the questions now put to large language models have no correct answer to score against: what a policy is worth, which option a user should cho

safetyarxiv-cs-cl

Complementary Feature Domains: Information Preservation Does Not Imply Predictive-Contribution Preservation

arXiv:2610.07565v1 Announce Type: cross Abstract: Complementary Feature Domains (CFD) theory characterizes predictive value as a context-indexed contribution system induced jointly by representations

LiLib: Lifelong Air-to-Ground Path-Loss Prediction on UAVs via a Drift-Triggered Model Library

arXiv:2610.07111v1 Announce Type: cross Abstract: UAVs that act as relays or base stations need accurate air-to-ground path-loss predictions for rate adaptation and placement, but propagation conditio

Mathematical Invariant-Enabled Topological Neural Networks for Molecular and Materials Property Prediction

arXiv:2610.07712v1 Announce Type: cross Abstract: Existing molecular and materials learning approaches often rely on a limited set of structural representations, which may capture only selected aspect

REPA-G: Test-Time Conditioning with Representation-Aligned Visual Features

arXiv:2602.03753v2 Announce Type: replace Abstract: While representation alignment with self-supervised models has been shown to improve diffusion model training, its potential for enhancing inference

Zero-Shot Visualization: Exploring Text Corpora with User-Prompted Axes

model-releasesarxiv-cs-ai

arXiv:2610.06889v1 Announce Type: cross Abstract: We study the application of large language models (LLMs) to the visual exploration of textual corpora. We introduce zero-shot visualization (ZSV), a t

Aligning Multimodal Patient Evidence with Biomedical Knowledge Graphs for Clinical LLMs

arXiv:2610.06685v1 Announce Type: new Abstract: Clinical questions often depend on linking a patient's multimodal evidence to external biomedical knowledge, yet existing predictive systems rarely repr

safetyarxiv-cs-lg

Arithmetic Actor Heads and Training Stabilization for Out-of-Distribution Reinforcement Learning

arXiv:2610.05143v1 Announce Type: new Abstract: Reinforcement learning (RL) policies can deteriorate under out-of-distribution (OOD) magnitude shifts. Starting from soft actor-critic (SAC) and its Bay

BrainTRACE: Tracing Longitudinal, Multimodal, and Volumetric Evidence in Brain MRI Clinical Reasoning

arXiv:2610.06571v1 Announce Type: new Abstract: Brain MRI interpretation is a longitudinal clinical reasoning problem: radiologists compare serial studies, integrate information across MRI sequences,

ClasSAE: Class-Aligned Sparse Autoencoders via Differentiable Feature-Class Affinity

arXiv:2610.04020v1 Announce Type: new Abstract: Sparse Autoencoders (SAEs) began as an unsupervised tool for decomposing neural representations into sparse, interpretable features, and are increasingl

DASH: Fast, Valid Counterfactuals for Deep Networks via Batched Directional Search

arXiv:2610.04783v1 Announce Type: new Abstract: Counterfactual explanations are most useful when they can be generated with low latency, remain close to the factual input, and satisfy input-domain, ca

Loss-Invariant Projections as Passive Probes of Learned Representations

arXiv:2610.06195v1 Announce Type: cross Abstract: Learned feature representations in neural networks often contain structure beyond that directly used by the final task output. We study this structure

MOXIE: Discovering Alternative Explanations for Biomedical Image Classifiers

arXiv:2610.04814v1 Announce Type: new Abstract: Segment-based explanation methods such as LIME return a single explanation for each prediction, computed from one fixed image segmentation. This hides t

Networking for AI inference model serving - GKE only and for all other backends

model-releasesgoogle-cloud-ai

Enterprises and individual developers frequently run multiple AI inference models. The right architecture can simplify how the models are called while also providing centralized governance. In this po

Safe Image Generation via Reinforcement Learning

arXiv:2610.05908v1 Announce Type: new Abstract: Recent Text-to-Image (T2I) models achieve remarkable visual image generation performance, but they can still generate NSFW (Not-Safe-For-Work) contents,

SPIN: Image Immunization Against Diffusion Editing via Single-Step Projection in Stochastic Neighborhoods

arXiv:2610.06334v1 Announce Type: new Abstract: Diffusion models have greatly advanced instruction-guided image editing, while also raising concerns about unauthorized image manipulation. Image immuni

The Numerical Linear Algebra of Large Language Models

arXiv:2610.04631v1 Announce Type: new Abstract: Numerical Linear Algebra (NLA) has consistently played a vital role in advancing science by providing tools to solve fundamental problems encountered in

Confidence-Controlled XAI Auditing for Pedestrian Detection under Domain Shift

arXiv:2610.02364v1 Announce Type: new Abstract: Explainability is increasingly required for perception models in intelligent vehicles, yet whether explanations remain faithful under driving domain shi

Local Ai

EviDent-CBCT: Evidence-Bottlenecked Report Generation from Dental CBCT under Non-Exhaustive Report Supervision

arXiv:2610.02375v1 Announce Type: cross Abstract: Dento-maxillofacial cone-beam CT (CBCT) reports may contain dozens of tooth-specific, anatomical, and spatial findings from a single 3D scan. Learning

local-aiarxiv-cs-ai

Agents

From Benchmarks to Production: A Text-to-SQL System for Complex Financial Data

arXiv:2610.03524v1 Announce Type: new Abstract: General-purpose Text-to-SQL systems achieve strong performance on academic benchmarks like Spider and BIRD, where schemas are relatively shallow and col

agentsarxiv-cs-ai

Tutorials

Learning a Fact Is Not Learning How to Retrieve It

arXiv:2610.03251v1 Announce Type: new Abstract: A model trained on 'The capital of X is Y' may produce 'Y' after 'The capital of X is' but fail after 'The capital of X:'. We call these different ways

tutorialsarxiv-cs-ai

TerrainForge: Physics-Grounded road geometry Editing for Counterfactual Autonomous Driving

arXiv:2610.02825v1 Announce Type: new Abstract: Road geometry (e.g., crests, sags, and speed humps) and surface conditions (e.g., wet or icy pavement) affect how vehicles move, what drivers and onboar

ULTRADISCOVERY: Abductive Exploration in an Interconnected, Epistemically Open Universe

arXiv:2610.03092v1 Announce Type: cross Abstract: Scientific discovery often begins when scattered clues call for a new way of describing the world. Such abductive exploration can require constructing

safetyarxiv-cs-ai