Search: “framework”

ProgressNet: Sketching and Prompting with a Frozen Text-to-Image Model

arXiv:2610.03512v1 Announce Type: new Abstract: Humans draw progressively: a few strokes, a look at the result, a stroke erased, a prompt revised. Image generators do not work this way. They typically

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PsyEvo: A Personalized Counseling Agent That Self-Evolves at Test Time

DGX agent

arXiv:2610.02885v1 Announce Type: new Abstract: Mental health disorders affect a substantial proportion of the global population, yet a persistent shortage of trained practitioners leaves the majority

safetyarxiv-cs-ai

5 Oct 2026

Real-Time sEMG-Based Telecontrol of an Assistive Robotic Arm Using a 1D Convolutional Neural Network

arXiv:2607.16310v2 Announce Type: replace Abstract: Motor impairments affecting the upper limb significantly reduce autonomy in daily activities, particularly for tasks involving object manipulation.

researcharxiv-cs-ro

Applications

Reasoning with Evidence, Not Merely Rationales: Verifiable Preference Proofs for LLM-Based Recommendation

arXiv:2610.02968v1 Announce Type: new Abstract: Large language models (LLMs) can infer user preferences from interaction histories and reviews, yet the rationales they generate may not reflect the inf

applicationsarxiv-cs-ai

Recursive Harness Self-Improvement for Frontier Reasoning Data Synthesis

arXiv:2610.03548v1 Announce Type: new Abstract: Generating progressively harder reasoning problems requires synthesis procedures that adapt as the task distribution evolves. Existing task-level recurs

researcharxiv-cs-ai

Reinforcement Learning Techniques for the Optimization of Target Polarization in Nuclear Physics Scattering Experiments

arXiv:2610.02452v1 Announce Type: new Abstract: The operation of dynamically polarized targets in nuclear physics experiments relies on continuous tuning of the microwave frequency to compensate for r

agentsarxiv-cs-ai

Reliability Stress Tests and Decision-Time Routing for Chest X-ray Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2610.02270v1 Announce Type: cross Abstract: Medical vision-language model (VLM) evaluation is sensitive to workflow design, prompting strategy, and benchmark construction, yet most studies treat

Applications

ReSCUE: Re-translation with Sentence Commitment for Unsegmented Long-Form Simultaneous Sign Language Translation

arXiv:2610.03022v1 Announce Type: cross Abstract: Simultaneous Sign Language Translation (SLT) is critical for real-time communication, yet existing methods remain largely confined to sentence-level,

applicationsarxiv-cs-cl

Revealing Epistemic Uncertainty in MLLMs via Causal-Invariant Masking

arXiv:2610.02887v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) suffer from hallucinations, creating a critical need for Uncertainty Quantification (UQ) to ensure reliable d

Revisiting Visual Representation Enhancement of VLMs via Kernel Canonical Correlation Analysis

arXiv:2610.02718v1 Announce Type: cross Abstract: Vision-language models such as CLIP exhibit strong semantic generalization, but remain limited in fine-grained visual perception. A recent work named

Local Ai

RIPPLE in Still Water: Zero-Shot Clustering in Federated Learning with Wavelet Scattering Transform

arXiv:2610.03054v1 Announce Type: new Abstract: Clustered Federated Learning (FL) partitions a client population into groups of similar local distributions and trains one specialized model per cluster

local-aiarxiv-cs-lg

RNADyn: A Benchmark for Generating and Understanding RNA Dynamics

model-releasesarxiv-cs-lg

arXiv:2610.03712v1 Announce Type: new Abstract: Ribonucleic acid (RNA) functions through conformational changes that are not fully captured by static structures. However, large-scale standardized RNA

Applications

ROVE: Unlocking Human Interventions for Humanoid Manipulation via Reinforcement Learning

arXiv:2606.17011v2 Announce Type: replace-cross Abstract: Human interventions provide crucial corrective signals for post-training Vision-Language-Action (VLA) models. However, enabling seamless human

applicationsarxiv-cs-lg

SARI: Phase-Split Sim-Real Co-Training for Contact-Rich Manipulation

arXiv:2610.02804v1 Announce Type: new Abstract: Vision-language-action (VLA) models often require costly real-world demonstrations to adapt to contact-rich manipulation tasks, particularly when genera

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Scaling Trajectories for Complex Tasks through Recursive Self-Rewrite

arXiv:2610.02826v1 Announce Type: new Abstract: Successful trajectories on difficult tasks provide valuable supervision for model improvement, but specialized harnesses introduce interventions that ma

Tutorials

SDECast: Probabilistic Weather Forecasting in Continuous Time with Neural SDEs

arXiv:2610.03313v1 Announce Type: cross Abstract: Existing machine learning weather forecasting models typically generate forecasts through autoregressive rollouts at a fixed temporal resolution. Whil

tutorialsarxiv-cs-lg

Self-Repairing Recurrent Ensembles for Real-Time Recovery from Distribution Shift

model-releasesarxiv-cs-ro

arXiv:2610.03249v1 Announce Type: cross Abstract: Deploying a pretrained controller exposes it to conditions that are absent from its training data. Sensor drift, outright sensor failure and accumulat

Self-Supervised Scaling of Terminal Environments for Scientific Domains

arXiv:2610.02710v1 Announce Type: cross Abstract: Terminal agents are increasingly deployed beyond software engineering in science and other specialized domains. Constructing training environments req

agentsarxiv-cs-ai

Shrome at Touche: Soft-Vote Ensembling and Counter-Causal Augmentation for Causality Extraction

arXiv:2610.03268v1 Announce Type: new Abstract: Touche 2026 extends causality extraction to counter-causal claims: news sentences whose surface form appears causal but whose meaning denies the causati

SigLIP2 for aerial fire risk classification

arXiv:2610.03689v1 Announce Type: new Abstract: We examine the transfer of a pretrained SigLIP2 image encoder to seven class fire risk classification from aerial imagery. We introduce a reproducible p

Signal Simplification Is Not Predictive Simplification: Diagnosing Residual Neural Forecasting in Short-Horizon Volatility

arXiv:2610.03019v1 Announce Type: new Abstract: Hybrid statistical-neural pipelines often assume that a successful statistical first stage leaves a cleaner and more learnable residual target. We exami

researcharxiv-cs-lg

Single-Pass Uncertainty Heads for Claim-Level Hallucination Detection in Persian Medical Language Models

arXiv:2610.03482v1 Announce Type: new Abstract: Hallucination detection is particularly important for medical language models, but repeated-sampling approaches are expensive and existing uncertainty-h

Skill2Real: Agentic Skill Learning for Zero-Shot Sim-to-Real Robot Manipulation

model-releasesarxiv-cs-ro

arXiv:2610.02788v1 Announce Type: new Abstract: Transferring robotic skills from simulation to reality requires task knowledge that remains usable across differences in perception, dynamics, and embod

Slow-Fast Multi-Teacher On-Policy Distillation for Capability Preservation

arXiv:2610.02324v1 Announce Type: cross Abstract: Foundation multimodal large language models are designed to support a broad spectrum of capabilities across diverse domains. Multi-teacher on-policy d

Source Preference in the Wild: How LLM Agents Favor Items by Source, and How to Reduce It

arXiv:2610.03195v1 Announce Type: new Abstract: As LLM agents decide on users' behalf which product to buy, which hotel to book, or which paper to cite, a preference for items from certain sources (th

agentsarxiv-cs-cl

Spatial Memory Intelligence: Endowing World Models with Understanding-Driven Long-Term Memory

arXiv:2610.02521v1 Announce Type: new Abstract: Long-video generation and world models have shown strong potential for interactive entertainment and embodied simulation by predicting future observatio

SpectralCache: Accelerating Diffusion-Based World Models via Spectral Feature Caching

arXiv:2610.02660v1 Announce Type: new Abstract: Diffusion-based world models enable high-quality interactive environment generation but suffer from substantial inference overhead due to repeated Trans

State-Space Unlearning for Non-Stationary Bias in Land Surface Forecasting

arXiv:2610.02248v1 Announce Type: new Abstract: Operational land surface forecasting systems built on Mamba-family Structured State Space Models absorb non-stationary confounding events (unrecorded ir

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Structural-Functional Brain Connectivity Generation via Multimodal Hypergraph-based Flow Matching

arXiv:2610.02722v1 Announce Type: new Abstract: Structural connectivity (SC) and functional connectivity (FC) provide complementary information on interactions between brain regions and are widely use

researcharxiv-cs-lg

SymRegFlow: Symmetry-Regularized Flow Matching for Video World Models

arXiv:2610.02726v1 Announce Type: new Abstract: Flow-matching-based multi-view world models generate realistic videos, but are commonly restricted to fixed camera rigs. Extending them to continuously

agentsarxiv-cs-cv

Temporal Geometry of Deep Networks: Hyperbolic Representations of Training Dynamics for Intrinsic Explainability

arXiv:2610.03000v1 Announce Type: cross Abstract: Intrinsic explainability remains a challenging problem, particularly in contexts where multilayer perceptrons (MLPs) require dynamic re-training withi

Test-time Calibration Learning for Large Language Model Reasoning

arXiv:2610.02695v1 Announce Type: cross Abstract: Reliable large language models (LLMs) must not only produce accurate answers but also express confidence that faithfully reflects their probability of

Test-time Multi-agent Coordination by Decomposed Value Gradient Flow

arXiv:2610.02554v1 Announce Type: new Abstract: Offline multi-agent reinforcement learning (MARL) faces a persistent trade-off. Expressive generative policies can represent multi-modal coordination in

safetyarxiv-cs-lg

The AI Theorist reveals excitonic structure in alpha-RuCl_3

arXiv:2610.02417v1 Announce Type: new Abstract: Advances in experimental instrumentation and automation generate increasingly rich datasets, but turning experimental observations into microscopic unde

agentsarxiv-cs-lg

Tutorials

The Fragility of Trigger-Tag Mechanisms for Misuse Detection in Open-Weight LLMs

arXiv:2610.03124v1 Announce Type: cross Abstract: Open-weight language models can be downloaded, modified, and deployed beyond their developers' control, limiting the effectiveness of centrally enforc

tutorialsarxiv-cs-ai

The Geometry of Knowledge Accessibility in Large Language Models

arXiv:2610.03052v1 Announce Type: new Abstract: Large language models (LLMs) contain broad knowledge, but they cannot access all of it reliably. We study this problem through knowledge accessibility,

The Percept-V Challenge: Can Multimodal LLMs Crack Simple Perception Problems?

arXiv:2508.21143v4 Announce Type: replace Abstract: Cognitive science research treats visual perception, the ability to understand and make sense of a visual input, as one of the early developmental s

To Explore The Strange New World Beyond Data Distribution: System Behavior, Causality Tax, and Non-causal Base Model

arXiv:2610.02839v1 Announce Type: cross Abstract: We show that the causality of language models (LMs) may not be necessary nor optimal. This is the case when system behavior (denoted as S) is incorpor

Trading Strategy Optimization via Textual Gradient

arXiv:2610.03128v1 Announce Type: new Abstract: Quantitative trading strategy design aims to discover trading programs from historical data that remain effective in future markets, which can be viewed

Uncertainty as a Proxy for Semantic Correctness in Diffusion-Based Medical Image Synthesis

arXiv:2610.03224v1 Announce Type: cross Abstract: Diffusion models can synthesise contrast-enhanced CT (CECT) from non-contrast CT (NCCT), avoiding contrast administration and its environmental and pa

researcharxiv-cs-ai

Understanding Clinical Cognitive Dialogues Using Large Language Models

model-releasesarxiv-cs-cl

arXiv:2609.34125v2 Announce Type: replace Abstract: In-person cognitive assessment is both a test and an interaction. Clinicians explain tasks, repair misunderstandings, and adapt to patient responses

Understanding Trajectory Heterogeneity in Federated World Model Learning

model-releasesarxiv-cs-cl

arXiv:2610.02957v1 Announce Type: cross Abstract: World models learn state evolution from trajectories, making access to temporal context a central training requirement. Federated learning can use dis

Variance-reduced accelerated methods for decentralized stochastic double-regularized nonconvex strongly-concave minimax problems

arXiv:2307.07113v2 Announce Type: replace-cross Abstract: In this paper, we consider the decentralized, stochastic nonconvex strongly-concave (NCSC) minimax problem with nonsmooth regularization terms

researcharxiv-cs-lg

VDOT++: Unified Few-Step Video Generation via Unbalanced Optimal Transport Distillation

model-releasesarxiv-cs-cv

arXiv:2610.03221v1 Announce Type: new Abstract: Video creation spans text-to-video (T2V), image-to-video (I2V), and condition-based generation, yet video diffusion models remain costly because they re

VIGOR: Zero-Shot Visual Generalization via Latent-Space Consistency in Model-Based Reinforcement Learning

arXiv:2610.02801v1 Announce Type: new Abstract: Model-based reinforcement learning (MBRL) achieves strong sample efficiency by planning within learned latent dynamics, yet its performance degrades sub

researcharxiv-cs-ai

Weave Forcing: Compositional Memory Routing for Interactive Long Video Generation

arXiv:2610.03510v1 Announce Type: cross Abstract: Recent advances in autoregressive video generation have improved temporal consistency over extended durations, yet interactive storytelling requires m

We're expanding our approach to content provenance to include text in response to EU regulatory requirements, while recognizing the signific…

We're expanding our approach to content provenance to include text in response to EU regulatory requirements, while recognizing the significant limitations of current text watermarking technology. Our

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When Can We Trust the Matching Principle? Robust Deployment Geometry Under Finite-Sample and Model Uncertainty

arXiv:2610.02894v1 Announce Type: cross Abstract: Match only geometry you can identify; otherwise spread the penalty. We quantify that decision by the trust ratio tau = epsilon / gamma (estimation unc