Search: “benchmark”

LACE-CRAFT: Robot Co-Design with Actor Inheritance and Blackboard Collaboration

arXiv:2610.09283v1 Announce Type: new Abstract: Robot co-design couples morphology search with policy learning, yet training every new design from scratch discards acquired control experience. We pres

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Learning in the Recurrent State: Gradient Descent with Linear Recurrent Networks

DGX agent

arXiv:2410.11687v4 Announce Type: replace Abstract: In-context learning lets a sequence model adapt to a new task from examples in its input. A prominent line of work shows how self-attention can be c

safetyarxiv-cs-lg

8 Oct 2026

Learning Transition Kernels of Jump-Diffusion Processes with Conditional Diffusion Models

arXiv:2610.09045v1 Announce Type: cross Abstract: We study the problem of learning transition kernels for time-homogeneous jump-diffusion processes using conditional diffusion models, with the goal of

LiveMACE: Process-Aware Evaluation of LLM Agent Capabilities in Evolving Markets

model-releasesarxiv-cs-cl

arXiv:2610.09872v1 Announce Type: cross Abstract: Evaluating agents by outcomes alone can obscure the capabilities that produce them. This problem is especially pronounced in evolving environments, wh

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

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

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

Measurement-Efficient Differentiable Quantum Architecture Search for Combinatorial Optimization

arXiv:2610.10351v1 Announce Type: cross Abstract: Differentiable quantum architecture search (DQAS) is a promising framework for the automated design of quantum circuits, particularly for variational

MeshSIPP: Efficient Lattice Planning in Dynamic Environment

model-releasesarxiv-cs-ro

arXiv:2610.09652v1 Announce Type: cross Abstract: Autonomous navigation in dynamic environments requires computing spatiotemporal trajectories that satisfy non-holonomic motion constraints. When the t

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

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Tutorials

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

MOTIF: Person-of-Interest Deepfake Detection Beyond 3DMM Coefficients

arXiv:2610.09830v1 Announce Type: new Abstract: Video deepfakes targeting a specific individual, the Person-of-Interest (POI), are the most harmful ones, and, since a public figure is abundantly recor

Agents

Multi-Agent Coordination via Support-Preserving Distillation

arXiv:2610.10087v1 Announce Type: new Abstract: Offline MARL increasingly relies on generative policies to model multimodal joint behavior, typically by distilling a centralized teacher into decentral

agentsarxiv-cs-lg

Local Ai

Neighborhood Smoothing for Calibration

arXiv:2610.09020v1 Announce Type: new Abstract: Modern neural networks are often miscalibrated, with a tendency to overconfidence. Existing train-time calibration methods largely modify task losses or

local-aiarxiv-cs-lg

NeRFifyMesh: Optimizing Neural Radiance Fields from Textured Meshes for Robotics Scene Building

arXiv:2610.10387v1 Announce Type: new Abstract: In robotics, scene representation plays a pivotal role in understanding and interacting with the environment. The advent of Neural Radiance Fields (NeRF

researcharxiv-cs-ro

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

One Frame, Full Heartbeat: ECG-Free Cardiac Cine MRI Synthesis via Phase-Conditioned Flow Matching

arXiv:2610.09397v1 Announce Type: new Abstract: Cine cardiovascular magnetic resonance (CMR) analysis relies on multi-frame sequences capturing the full cardiac cycle. However, standard multi-frame ac

Online Resource Allocation with an Endogenous Markov State: Fewer LP Solves Earn More

arXiv:2610.09577v1 Announce Type: new Abstract: We study finite-horizon online resource allocation with i.i.d. requests and an endogenous Markov state on a finite state space: each action affects the

ORACLE: Optimizer-Relative Alignment for Constrained LEarning

arXiv:2610.09040v1 Announce Type: new Abstract: Constraint handling methods typically intervene before the optimizer acts, by modifying the objective or the gradient. Yet momentum, adaptive scaling, a

Origins of Universal Machine Learning Force-Field Errors in Multicomponent Materials

arXiv:2610.09837v1 Announce Type: cross Abstract: Universal machine learning force-field generalization to multicomponent environments generated by compositional design remains insufficiently assessed

Oscillatory Neural Dynamics over Sheaves

arXiv:2610.10018v1 Announce Type: new Abstract: Effective long-range propagation remains a central challenge in graph neural networks, as increasing a model's propagation depth does not guarantee that

researcharxiv-cs-lg

OverLay++: Dense-Overlap Layout-to-Image Generation Dataset

arXiv:2610.09071v1 Announce Type: new Abstract: Layout-to-Image generation has made substantial progress in spatial and object-level control. However, existing methods still struggle with complex scen

PanoPed: Beyond Bounding Boxes for Sim-to-Real Panoramic Pedestrian Tracking

arXiv:2610.08826v1 Announce Type: new Abstract: Full-sphere panoramic cameras let fixed monitoring systems and mobile robots track people in every direction, but a planar bounding box does not fully d

Performance at What Cost? A Sustainability-Aware Performance Index for Cell and Nucleus Instance Segmentation

arXiv:2610.10324v1 Announce Type: new Abstract: Pretrained models for cell and nuclear instance segmentation differ substantially in architecture, pretraining data and objectives, parameter count, inf

Tutorials

Physics-Informed Neural Plasticity: PDE Solvers That Reshape Themselves

arXiv:2610.09510v1 Announce Type: new Abstract: Physics-informed neural PDE solvers adapt their parameters to satisfy governing equations, yet their representational structure typically remains fixed

tutorialsarxiv-cs-lg

Applications

Precise SE(3) End-Effector Tracking in Whole-Body Humanoid Control

arXiv:2610.09479v1 Announce Type: new Abstract: Precise end-effector tracking during humanoid whole-body motion is challenging due to floating-base oscillations, gravity, dynamic coupling, and locomot

applicationsarxiv-cs-ro

PrismSSL: One Interface, Many Modalities; A Single-Interface Library for Multimodal Self-Supervised Learning

arXiv:2511.17776v2 Announce Type: replace Abstract: We present PrismSSL, a Python library that unifies state-of-the-art self-supervised learning (SSL) methods across audio, vision, graphs, and cross-m

Prototype-Based Knowledge Guidance for Fine-Grained Structured Radiology Reporting

arXiv:2603.11938v2 Announce Type: replace-cross Abstract: Structured radiology reporting promises faster, more consistent communication than free text, but automation remains difficult as models must

Purifying Backdoored Large Vision-Language Models by Removing Hijacked Directions

arXiv:2610.09941v1 Announce Type: new Abstract: Large vision-language models (LVLMs) are increasingly deployed in safety-critical applications, yet they remain vulnerable to backdoor attacks. Defendin

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QuadTok: Quadtree Visual Tokenizer for Autoregressive Image Generation

arXiv:2610.10497v1 Announce Type: new Abstract: We introduce QuadTok, a novel framework for visual tokenization and autoregressive image generation. Compared to traditional approaches using 2D grids o

Quasi-Binarized Autoencoders: An Architecture-Independent Information Bottleneck for Medical Image Anomaly Detection

arXiv:2610.09670v1 Announce Type: new Abstract: Unsupervised anomaly detection, which learns only from normal images, is a central task in medical image analysis and remains an open problem. Reconstru

Local Ai

RACER: Reflective Agent Coupling Query Interpretation and Tool-Based Retrieval for Frame Selection in Long Video Understanding

arXiv:2610.08954v1 Announce Type: new Abstract: Video large language models (Vid-LLMs) excel at diverse video-language tasks by reasoning over selected frames. However, frame selection for long videos

local-aiarxiv-cs-cv

RDGSplat: Render-Dedicated Geometry for Novel View Synthesis

arXiv:2610.09173v1 Announce Type: new Abstract: 3D foundation models enable efficient novel view synthesis by carrying a Gaussian head on the representation they already use for reconstruction. Howeve

Relational Abstractions for Spatial Reasoning with Diffusion Models

arXiv:2610.09780v1 Announce Type: new Abstract: Diffusion models excel at image synthesis, but they remain limited in their ability to reliably satisfy structured spatial reasoning constraints. In con

Residual Learning in Empirical Asset Pricing

arXiv:2610.09613v1 Announce Type: cross Abstract: Shallow models are special cases of deep models, and deep models theoretically have the potential to outperform the shallow ones. However, the existin

researcharxiv-cs-lg

ResidualQuant: KV Cache Quantization for Looped Transformers with 2-Bit Residuals

arXiv:2610.10381v1 Announce Type: new Abstract: Looped Transformers improve parameter efficiency by repeatedly applying shared Transformer blocks over multiple recurrent loops, increasing computationa

RLHND: Video Foundation Models as Physically Grounded Hand Trackers for Robot Learning

arXiv:2610.09455v1 Announce Type: new Abstract: Recently, approaches that leverage human video datasets for robot policy training have become increasingly prevalent. However, most existing hand tracke

RoboPilot: Generalizable Dynamic Robotic Manipulation with Dual-thinking Modes

model-releasesarxiv-cs-ro

arXiv:2510.00154v2 Announce Type: replace Abstract: Despite rapid progress in robotics, complex or long-horizon tasks remain a fundamental challenge. Most current approaches follow an open-loop paradi

RoboQuest: Generalist Physical Agents that Search, Inspect and Test

arXiv:2610.10388v1 Announce Type: cross Abstract: Recent advances in multimodal foundation models have made them capable generalist physical agents for a range of manipulation tasks. However, successf

Tutorials

S2Tok: Streaming 3D Gaussian Reconstruction with Persistent Spatial Tokens

arXiv:2610.08978v1 Announce Type: new Abstract: Streaming 3D reconstruction requires more than a sequence of geometric predictions: it requires a persistent scene state that can incorporate new eviden

tutorialsarxiv-cs-cv

SANet: Selective Attention Network for Infrared Small Target Detection

arXiv:2610.09875v1 Announce Type: new Abstract: Infrared small target detection aims to accurately identify and locate dim targets in complex backgrounds and supports applications such as maritime sur

SAPD: Step-Aligned Privileged Distillation

arXiv:2610.09665v1 Announce Type: new Abstract: On-policy post-training can improve large language models by learning from their own trajectories, but requires costly rollout generation. We ask whethe

safetyarxiv-cs-cl

Scalable Logistic Gaussian Process Density Regression with Kinetic Langevin Sampling

arXiv:2610.09591v1 Announce Type: cross Abstract: Conditional density estimation targets the full distribution of a response given covariates, as required, for example, for per-galaxy photometric reds

safetyarxiv-cs-lg

Scalable Patch-Level Self-Supervised Learning

arXiv:2610.10013v1 Announce Type: new Abstract: Self-supervised learning (SSL) at scale produces powerful visual representations. However, most scalable SSL methods rely on ad hoc combinations of mult

SciExam for ENSO: Can AI Agents Build Climate Models?

arXiv:2610.10513v1 Announce Type: cross Abstract: Language-model agents are increasingly asked to carry out open-ended scientific research, yet their results are usually graded against a known answer,

Self-correction Optimization for Interleaved Multimodal Generation

arXiv:2610.10400v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have made significant progress in visual understanding and generation. However, generating interleaved image--t

Sparse Planning in Visual World Models via Cost Gradients

arXiv:2610.10274v1 Announce Type: new Abstract: Token-based world models enable fine-grained latent planning, but repeatedly processing large spatial token grids makes action search expensive. We intr

researcharxiv-cs-lg

Sparsifying Stochasticity, Not Capacity: Partial Stochasticity via Deep Weight Factorization of Prior Scales

arXiv:2610.09886v1 Announce Type: cross Abstract: Bayesian neural networks need not be fully stochastic to be universal conditional density approximators, but it remains open which parameters should b