Search: “models”

Background2Background: a self-supervised background removal framework for high dimensional microscopy

arXiv:2610.17615v1 Announce Type: cross Abstract: High-dimensional microscopy captures features across space, time, and spectrum, but complex backgrounds obscure signals. We present Background2Backgro

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Research

Barycentric Guidance: Turning Foundation Image Editors into Continuous Affective Controllers

DGX agent

arXiv:2610.16892v1 Announce Type: new Abstract: Emotions are expressed on a continuum and are naturally described in the valence-arousal (VA) space. Existing VA-based image editors are typically train

researcharxiv-cs-cv

14 Oct 2026

BehaviorFormer: Discovering Behavioral Patterns via Clusterable Next-Token Prediction

arXiv:2610.16322v1 Announce Type: new Abstract: Discovering behavioral patterns in open-ended games is challenging due to the lack of clear objectives or ground-truth annotations. In this work, we ext

Belief Embedding Tree Search

arXiv:2610.15046v1 Announce Type: cross Abstract: Beliefs in a Partially Observable Markov Decision Process (POMDP) are posterior distributions over the hidden state given the agent's history of actio

Better together? A performance theory of human-machine skill policies under generalization difficulty

arXiv:2610.16863v1 Announce Type: cross Abstract: Organizations pairing a human and a machine on a task decide, often by default, which executes each instance and what happens when both do. We account

Beyond Gate Weights: Decision-Level Interpretation of Radiomics-Image Feature Fusion for RCC Classification

arXiv:2610.14152v1 Announce Type: cross Abstract: Gate coefficients describe how a fusion layer weights intermediate features, but they do not necessarily reflect the magnitude of branch contributions

Beyond Policy Rollouts: Embedding-Space Directional Exploration with Anchored Noise for LLM RLVR

arXiv:2610.16105v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) typically uses small rollout groups per prompt, where repeated sampling from the same policy can y

Beyond RMSE and Granger Gain: Multi-Horizon Forecast-Error Entropy for Nonlinear Predictive Coupling

arXiv:2610.18390v1 Announce Type: cross Abstract: We investigate whether the past of an auxiliary time series provides predictive information about a target beyond that contained in the target's own h

Can Machine Learning Potentials Be More Accurate Than the Methods They Are Trained On?

arXiv:2610.18027v1 Announce Type: cross Abstract: Although machine learning potentials (MLPs) generalize across configurational and chemical compound spaces, their accuracy is commonly believed to be

Comprehensive Workflow for Uncertainty-Aware Ionic Liquid Solvent Discovery

arXiv:2610.17171v1 Announce Type: cross Abstract: Designing synthesizable materials with targeted properties remains one of the central objectives in materials sciences. Ionic liquids (ILs) are well s

Concealed Handgun Detection using WiFi Signals

arXiv:2610.18736v1 Announce Type: new Abstract: While conventional camera-based surveillance systems and metal detectors can provide a sufficient level of security when used appropriately, they have f

ConDenseDrive: Knowledge-Dense, Token-Sparse Visual Encoder for End-to-End Autonomous Driving

arXiv:2610.16908v1 Announce Type: new Abstract: End-to-end driving requires rich spatiotemporal representations to support scene understanding and trajectory planning under strict latency constraints.

agentsarxiv-cs-cv

Context-aware Bayesian Fusion for Multimodal Object Detection

arXiv:2610.18741v1 Announce Type: new Abstract: Reliable detection of pedestrians and road users is essential for the safe operation of autonomous vehicles. However, this task becomes increasingly cha

agentsarxiv-cs-cv

Contrastive Metric Learning for Point Cloud Segmentation in Highly Granular Detectors

arXiv:2603.23356v2 Announce Type: replace-cross Abstract: We propose a novel clustering approach for point-cloud segmentation based on supervised contrastive metric learning (CML). Rather than predict

Cross-Embodiment Affordance Transfer for Robotic Manipulation

arXiv:2610.18194v1 Announce Type: new Abstract: Robotic manipulation systems commonly learn object affordances from human-annotated datasets, which reflect interaction possibilities for a human hand r

tutorialsarxiv-cs-ro

Deep Mesoscopic Dynamics

arXiv:2610.17885v1 Announce Type: new Abstract: Microscopic simulations resolve spatial patterns but are feasible only over small domains and short timescales, whereas bulk descriptions erase those pa

DeltaNet-PC: Test-Time Memory Without Backpropagation Through Time

arXiv:2610.15185v1 Announce Type: new Abstract: Test-time memorization of sequential information is a foundational capability for any intelligent system that needs to rapidly store and retrieve data,

local-aiarxiv-cs-lg

Dependency Reasoning for Aspect Sentiment Quadruple Prediction

arXiv:2610.14873v1 Announce Type: cross Abstract: Aspect Sentiment Quadruple Prediction (ASQP) is fundamentally a relational reasoning problem: identifying aspect-opinion-category-sentiment quadruples

Deterministic denoising of long-duration gravitational-wave signal candidates with alpha-(de)blending

arXiv:2609.15308v1 Announce Type: cross Abstract: We present a deterministic machine-learning method for denoising candidate signals from all-sky searches for continuous gravitational waves from rotat

DexNinja: Learning Robust Dexterous Cutting Policy with a Real-to-Sim-to-Real Data Engine

arXiv:2610.17208v1 Announce Type: cross Abstract: Cutting a piece of food looks effortless in human hands. For a robot, however, every cut is a high-contact interaction with a deformable, elasto-plast

DexStitch: Learning and Composing Dexterous Skills from Human Videos via Contact-Aware Robotic Inpainting

arXiv:2610.17789v1 Announce Type: cross Abstract: A long-horizon manipulation task consists of primitive skills and the transitions connecting them. Learning skills that can be executed in sequence re

Disease-level drug approval forecasting from trial-agnostic public data

arXiv:2610.14013v1 Announce Type: cross Abstract: Drug development is an expensive and lengthy process requiring developers to select drugs for human trials and diseases to target. Computational tools

EmbodiedEvo: Self-improving Coding Agents for Physical Intelligence

arXiv:2610.18867v1 Announce Type: new Abstract: Bringing general-purpose agents into the physical world calls for an executable representation of physical intelligence. Compared with vision-language-a

safetyarxiv-cs-ro

Equilibrium Learning in Unbounded Stochastic Games with Gaussian Transitions

arXiv:2610.16149v1 Announce Type: cross Abstract: Learning equilibria from data is difficult when several decision makers interact indefinitely and the system state has no prescribed bounds. We examin

Error-Based Bidirectional Predictive Coding Enables Deep, 4-Bit Predictive Coding Networks

arXiv:2610.15933v1 Announce Type: new Abstract: Predictive coding networks (PCNs) promise properties not offered by backpropagation-trained networks: learning from purely local information, a single n

local-aiarxiv-cs-lg

Hardware

Event2Vec: additive event embeddings where a linear score on a history decomposes exactly into per-event terms [P]

hardwarer-machinelearning

I've been working on Event2Vec, a small library for learning embeddings of discrete event sequences (purchases, logs, clinical codes, etc.) with a deliberately simple structure: a history is the runni

Exact power indices for plurality-voting ensembles

arXiv:2610.17980v1 Announce Type: new Abstract: Plurality-voting ensembles aggregate the predictions of multiple base classifiers and output the most voted class, with ties typically broken at random.

Explore with Memory, Learn without It: In-Context Exploration and Self-Distillation for LLM Reasoning

arXiv:2610.17734v1 Announce Type: new Abstract: Exploration bounds learning efficiency in reinforcement learning with verifiable rewards (RLVR). Current methods explore mostly through independent samp

Flow-Support-Weighted Proposals for Test-Time Verified VLA Policies

arXiv:2610.14588v1 Announce Type: cross Abstract: Test-time sampling promises to turn one action prediction into a set of distinct executable candidates that a verifier can choose among. Downstream fi

FlowSim: Rendering-Free Closed-Loop Simulation for Evaluating End-to-End Driving Systems

arXiv:2610.18030v1 Announce Type: new Abstract: Closed-loop evaluation of end-to-end (E2E) driving systems typically relies on generating sensor observations and re-processing them through the percept

agentsarxiv-cs-cv

FRACTION: Fraud Explanation Generation via Agentic Graph Context Navigation

arXiv:2610.18023v1 Announce Type: new Abstract: Graph fraud explanation generation emerges as an important task, which requires jointly leveraging graph structure and content information to produce hu

agentsarxiv-cs-lg

FrameFold: Response-Guided KV Cache Consolidation for Autoregressive Long Video Generation

arXiv:2610.14568v1 Announce Type: new Abstract: In autoregressive video generation, retaining all historical key-value (KV) states increases memory usage and per-step attention costs as videos grow lo

tutorialsarxiv-cs-cv

From Failure Prediction to Component Selection in Semantic Segmentation

arXiv:2610.16058v1 Announce Type: new Abstract: Reliable scene understanding requires deciding which predictions to trust, retain, or inspect. In semantic segmentation, component failure predictors su

From Parallel to Sequential: Small-Batch Noise Restores Simplicity Bias of Muon

arXiv:2610.16868v1 Announce Type: new Abstract: Simplicity bias, which can arise from sequential feature learning during training, has been proposed as a general explanation for the success of deep le

From Volpiano to Pixels: 30,000 Lines of OMR Ground Truth for Medieval Chant

arXiv:2610.16862v1 Announce Type: new Abstract: Optical music recognition (OMR) for medieval chant lacks training data linking manuscript images to musical symbols across notational families. Using ex

Frozen History: When Temporal Losses Stop Accumulation in Learned Real-Time Supersampling

arXiv:2610.15752v1 Announce Type: new Abstract: Learned real-time supersampling accumulates jittered low-resolution samples along motion vectors. Many methods use a temporal consistency loss to reduce

Generalized PINN-Based Inverse Estimation of Spatially Varying Heat Transfer Coefficients with Transfer Learning

arXiv:2610.14008v1 Announce Type: new Abstract: This study investigates generalized boundary representations and transfer learning for physics-informed neural-network (PINN) estimation of spatially va

Generative Quantum Machine Learning Methods for Cancer Detection using Augmented Datasets

arXiv:2610.15110v1 Announce Type: cross Abstract: Cancer detection using AI methods and image databases faces several challenges, including limited and imbalanced image datasets, long algorithm traini

Getting Space Right: Agentic Rewards for Image Generation

arXiv:2610.14852v1 Announce Type: new Abstract: Reinforcement learning (RL) is promising for spatial text-to-image generation, but existing work largely focuses on policy optimization, assuming accura

Global Disaster Risk Assessment Using World Risk Index Data: A Geospatial and Visual Analytics Approach

arXiv:2610.15064v1 Announce Type: new Abstract: The world has seen several threats that include resource depletion, food security, poverty and inequality, difficulties associated with urbanization, mi

Graph3R: Unifying View Graph Initialization with Feed-Forward Reconstruction

arXiv:2610.16272v1 Announce Type: new Abstract: Feed-forward reconstruction recovers camera poses and dense geometry from image sets whose views are assumed to come from a single scene. In practice, u

local-aiarxiv-cs-cv

Applications

Harnessing VLM in Embodied RL: From Reward Regressor to Success Detector via Exploration-Augmented Key-Observation Gating

arXiv:2610.15401v1 Announce Type: new Abstract: VLMs provide promising solutions to embodied reward design. Most current methods that train VLMs as reward regressors not only require extensive annotat

applicationsarxiv-cs-lg

Hierarchical Multi-Agent Reasoning Systems for Knowledge-Grounded Material Substitution

arXiv:2610.14123v1 Announce Type: cross Abstract: AI-assisted scientific discovery increasingly seeks to move beyond generating plausible ideas toward reproducible, constraint-aware workflows that can

agentsarxiv-cs-lg

HiPAD: A Unified Gait, Audio-Visual, and Personality Fusion Network for Depression Detection, with a Hierarchical Personality Ablation and the Calibration Limits of Domain-Adapted LLMs

arXiv:2610.14961v1 Announce Type: cross Abstract: We present HiPAD, a single fusion network submitted to all six sub-tracks of the MPDD-AVG 2026 depression-detection challenge, covering the Elder and

Honeycomb Crystal in a Mass-Asymmetric Electron-Hole Bilayer

arXiv:2610.17030v1 Announce Type: cross Abstract: A two-dimensional electron gas in a uniform neutralizing background forms a triangular Wigner crystal at low density. In a strongly mass-asymmetric el

local-aiarxiv-cs-lg

How Shared Representations Become Specialized: Formation, Maintenance, and Latent Susceptibility

arXiv:2610.15830v1 Announce Type: new Abstract: When several predictions use the same internal representation, information about some targets can remain easier to recover than information about others

Hyperbolic Time Series Forecasting with Learnable Decomposition and Manifold Dynamics

arXiv:2610.15760v1 Announce Type: new Abstract: Multiscale structure is central to time series forecasting: temporal signals contain slowly varying trends, intermediate seasonal patterns, and high-fre

Tools

ICYMI from yesterday's @dealbook: inference startups are ripping as enterprises continue to adopt AI - @togethercompute's annual bookings hi…

ICYMI from yesterday's @dealbook: inference startups are ripping as enterprises continue to adopt AI - @togethercompute's annual bookings hit 1.2 billion as of July - @FireworksAI_HQ crossed 1 billion

toolstogether-ai--x