Search: “framework”

From Pareto to Preference: Personalized Test-Time Scaling via Amortized Agentic Policy Discovery

arXiv:2610.09684v1 Announce Type: new Abstract: Test-time scaling (TTS) improves the reasoning capabilities of large language models by allocating additional inference computation. Existing approaches

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From Prompts to Trees: Effective LLM-Guided Tree Generation for Few-Shot Tabular Classification

DGX agent

arXiv:2610.10227v1 Announce Type: cross Abstract: While Large Language Models (LLMs) possess rich world knowledge and impressive generalization capabilities, their direct application to tabular data c

applicationsarxiv-cs-cl

8 Oct 2026

Gaussian Density Splatting Network

arXiv:2610.10396v1 Announce Type: new Abstract: This paper proposes a novel crowd counting approach, the Gaussian Density Splatting Network (GDSNet). Unlike methods that rely on conventional, grid-bas

Geometry-Aware Diffusion Approximate Posterior Sampling for Sparse-View and Limited-Angle CT

arXiv:2610.08866v1 Announce Type: cross Abstract: Sparse-view computed tomography (CT) reduces radiation dose and acquisition time and may mitigate motion artifacts. However, angular undersampling pro

Geometry-Supervised Visual Representation Learning for Multi-Phenotype Lesion Interpretation in Medical VLMs

arXiv:2610.10238v1 Announce Type: new Abstract: Medical vision-language models (VLMs) have shown increasing potential for clinical image interpretation. However, these models still struggle to interpr

safetyarxiv-cs-cv

GeoPrior-Mamba: Structured Process Priors with Mamba for Fine-Resolution XCO2 Reconstruction

arXiv:2610.09456v1 Announce Type: new Abstract: Reconstructing fine-resolution column-averaged dry-air CO2 (XCO2) fields from sparse satellite observations requires models to infer spatial structure t

tutorialsarxiv-cs-lg

GRACE: Generation-aware latent compression for efficient video generation

arXiv:2610.10524v1 Announce Type: new Abstract: Highly compressed video autoencoders offer an effective way to accelerate video diffusion models, as the Diffusion Transformer (DiT) operates on far few

tutorialsarxiv-cs-cv

GraphRectify: Graph-Based Transfer of Adversarial Example Detectors Across Neural Networks

arXiv:2610.10423v1 Announce Type: new Abstract: Adversarial example detectors are often tied to the classifier backbone they were trained on, limiting reuse when the protected model is replaced or upg

GUARD: Geometric Uncertainty-Aware Point Cloud Denoising and Segmentation for Robotic Hard Disk Drive Disassembly

arXiv:2610.09068v1 Announce Type: new Abstract: Reliable robotic disassembly requires part-level representations that distinguish genuine component geometry from scanning and reconstruction artifacts.

HarnessIR: Harnessing Multimodal Foundation Models for Universal Real-World Image Restoration

arXiv:2610.10133v1 Announce Type: new Abstract: Real-world low-quality images suffer from complex mixed degradations, including but not limited to noise, blur, atmospheric effects, etc. Recent agentic

HeiCo-FOCUS: A Clinically Grounded Dataset for Long-Context Video Understanding

arXiv:2610.10156v1 Announce Type: new Abstract: Recent advances in Vision-Language Models (VLMs) have led to rapid progress in video understanding across a wide range of benchmark tasks. However, exis

Hidden in Plain Sight: Benchmarking Agent Safety Against Decomposition Attacks with DECOMPBENCH

model-releasesarxiv-cs-lg

arXiv:2606.13994v2 Announce Type: replace-cross Abstract: LLM-based Agents are becoming increasingly capable and widely deployed, creating growing incentives for adversarial misuse in the real-world.

How to train your model organism

model-releasesarxiv-cs-lg

arXiv:2610.10203v1 Announce Type: new Abstract: Model organisms of alignment-relevant behaviors (e.g., backdoors, sycophancy, spurious correlations) have emerged as a key tool for evaluating whitebox

HULK: Learning Whole-Body Forceful Loco-Manipulation for Humanoids

arXiv:2610.08970v1 Announce Type: cross Abstract: Humanoid loco-manipulation of large, heavy objects demands forceful interaction across the entire body. However, such payloads shift a humanoid's cent

safetyarxiv-cs-lg

InterView-C: A Synchronized Multimodal Corpus of VR Avatar-Mediated Survey Interviews

arXiv:2610.10145v1 Announce Type: new Abstract: We present InterView-C, a German multimodal corpus of 27 survey interviews conducted entirely in virtual reality, with both interlocutors represented by

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

model-releasesarxiv-cs-cl

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

researcharxiv-cs-cl

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

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

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

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

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

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

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

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

Machine learning modularity

arXiv:2601.01779v2 Announce Type: replace-cross Abstract: Based on a transformer based sequence-to-sequence architecture combined with a dynamic batching algorithm, this work introduces a machine lear

MAGIC: Learning from Visibility Asymmetry for Unsupervised Stereo Matching

arXiv:2508.10838v3 Announce Type: replace Abstract: Learning disparity in occluded regions remains difficult for unsupervised stereo matching. Photometric supervision lacks valid target-view correspon

MambaDSF: Multi-Scale SSM with Dilated Feature Fusion for Sonar Small Target Detection

arXiv:2605.24928v2 Announce Type: replace Abstract: Sonar imaging is the primary modality for underwater target detection, yet small targets remain difficult to detect due to insufficient pixel covera

MaRK: Markov-adapted Recurrent Kernels for Dynamic Operator Conditioning in State Space Models

model-releasesarxiv-cs-lg

arXiv:2610.09092v1 Announce Type: new Abstract: State Space Models (SSMs) offer an efficient alternative to Transformers for sequence modeling, yet conditioning pre-trained SSMs for iterative generati

Marrying Pricing and Advertising with LLMs

arXiv:2610.09985v1 Announce Type: cross Abstract: We study a sequential pricing problem in which a seller jointly posts a price and an advertisement generated by a large language model (LLM). The sell

safetyarxiv-cs-lg

Local Ai

Masked Feature Encoding for Large-Scale Whole Slide Image Representation

arXiv:2610.10225v1 Announce Type: new Abstract: Whole slide image (WSI) analysis in computational pathology follows a multiple instance learning (MIL) pipeline where patch embeddings are extracted ind

local-aiarxiv-cs-cv

MimicX: Policy-in-the-Loop Supervision Refinement for Video-Driven Humanoid Motion Tracking

arXiv:2610.09055v1 Announce Type: new Abstract: Human videos provide rich motion targets for humanoid learning, yet visually plausible references can still produce persistent failures under physics-ba

safetyarxiv-cs-ro

MIRROR: From Imitation to Internalization in LLM Personalization

arXiv:2610.09795v1 Announce Type: new Abstract: The demand for personalized LLMs is shifting from style imitation toward content quality. We investigate whether self-distillation can bridge this gap i

MoR-MLLM: Mixture of Recursions for Efficient Multimodal Large Language Models

arXiv:2610.08830v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable reasoning capabilities across vision and language tasks. However, their massive co

applicationsarxiv-cs-cv

MORA: Modeling Observed Changes for Drift-Robust Time-Series Anomaly Detection

arXiv:2610.09473v1 Announce Type: new Abstract: Time-series anomaly detection (TSAD) identifies deviations from patterns learned from historical data. In non-stationary settings, distribution drift an

tutorialsarxiv-cs-lg

MORCA: Offline-to-Online Reinforcement Learning for Adaptive Cache Reuse in Video Diffusion Acceleration

arXiv:2610.10457v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) achieve remarkable performance in video synthesis, but their iterative denoising process suffers from high inference laten

tutorialsarxiv-cs-cv

MorphCL: Morphological Contrastive Learning for Inertial-based Human Activity Recognition

arXiv:2610.10245v1 Announce Type: new Abstract: Despite the ubiquity of sensors in wearable and mobile devices and the abundance of human movement data they generate, translating unlabeled recordings

MovieSTAGE: Scene, Transition, and Global Encoding for Movie-fMRI ADHD Classification

arXiv:2610.09306v1 Announce Type: new Abstract: Naturalistic movie-fMRI provides a shared, temporally structured probe of brain dynamics, yet predictive models commonly rely on whole-run functional co

Multimodal LLMs Can Learn to Read Brain Signals: A Vision--Language Model for Unified Multi-Task EEG Decoding

arXiv:2610.09355v1 Announce Type: cross Abstract: Learning EEG representations that generalize across cognitive tasks, subjects, and recording conditions remains a key challenge in electroencephalogra

tutorialsarxiv-cs-cv

Agents

Not All Uncertainty Matters: Simulation-in-the-Loop Fast-Slow Reasoning for Decision-Critical Autonomous Driving System

arXiv:2610.09520v1 Announce Type: new Abstract: Large vision-language models (VLMs) provide powerful open-world perception and reasoning for autonomous driving, but their high computational cost and i

agentsarxiv-cs-ro

NovaPlan: Zero-Shot Long-Horizon Manipulation via Closed-Loop Video Language Planning

arXiv:2602.20119v2 Announce Type: replace-cross Abstract: Solving complex long-horizon robotic tasks requires joint reasoning over abstract task structure and low-level physical interaction. While com

applicationsarxiv-cs-cv

On KL-Regularized Policy Optimization

arXiv:2610.08963v1 Announce Type: cross Abstract: Asynchronous reinforcement learning (RL) for large language model (LLM) agents trains one policy on trajectories generated by another: rollouts come f

On-Policy Distillation Teaches New Skills but Not New Knowledge

arXiv:2610.09639v1 Announce Type: new Abstract: On-policy distillation (OPD) strengthens language-model reasoning, yet whether students acquire new factual knowledge or compositional skill for multi-s

One Frame, Full Heartbeat: ECG-Free 4D Cardiac Cine MRI Synthesis via Radial-Decomposed Flow Matching

arXiv:2610.09185v1 Announce Type: new Abstract: Cine cardiovascular magnetic resonance (CMR) captures the cardiac cycle as a four-dimensional (4D) sequence, but standard acquisition requires electroca