Search: “benchmark”

Arm-wise Compositional Generalization in Dual-Arm Vision-Language-Action Models

arXiv:2610.06184v1 Announce Type: new Abstract: Generalization in multi-arm collaboration can be studied as composing familiar atomic skills in new ways across arms. However, existing evaluations offe

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Model Releases

ArtifactArena: Evaluating Models by What They Build in the Physical World

DGX agent

arXiv:2610.06511v1 Announce Type: new Abstract: To evaluate the frontier, we must measure models not by what they say, but by what they can engineer and build in grounded physical environments. We int

model-releasesarxiv-cs-ro

6 Oct 2026

Bayes-Sufficient Compression Is Not Enough: How Does Communication Help Multi-Agent Systems?

arXiv:2610.03769v1 Announce Type: new Abstract: Multi-agent LLM systems pair a sender with broad context and an executor with a limited local view. We study when a short message improves the executor'

Tutorials

Bayesian Entropy-based Reordering for Calibrated Diffusion Language Models

arXiv:2610.05125v1 Announce Type: new Abstract: Masked Diffusion Language Models (MDLMs) generate sequences by iteratively replacing masked tokens with model predictions. At each denoising step, the d

tutorialsarxiv-cs-lg

BazaarBench: Delegation Safety in Decentralized C2C Marketplaces Run by LLM Agents

arXiv:2610.06748v1 Announce Type: cross Abstract: In decentralized consumer-to-consumer (C2C) marketplaces, people list goods, negotiate with strangers, and rate one another, so trust rests on reputat

Tutorials

Broaden Your Views for Self-Supervised Video Learning

arXiv:2103.16559v3 Announce Type: cross Abstract: Most successful self-supervised learning methods are trained to align the representations of two independent views from the data. State-of-the-art met

tutorialsarxiv-cs-lg

CASE: Cost-Aware Stopping for Efficient Long-Video Agents

arXiv:2610.05400v1 Announce Type: cross Abstract: Long-video agents can actively gather question-relevant evidence, but they typically leave a central decision implicit: when has the agent seen enough

CCQ: A Multi-State Child Care Quality Dataset to Support AI for Children's Health Research

arXiv:2610.05863v1 Announce Type: new Abstract: High-quality child care in early life is a critical determinant of children's growth and development. Research on child care quality has been constraine

CLIFT: Conformal Self-Verification for Web Agent Training and Test-Time Scaling

arXiv:2610.06829v1 Announce Type: cross Abstract: Open-source web agents are now strong enough to execute realistic browser tasks, but training them with reinforcement learning still depends on weak s

Closing the Context Gap: Activation Alignment for Tabular In-Context Learning

arXiv:2610.06679v1 Announce Type: new Abstract: Tabular foundation models perform in-context learning (ICL) by conditioning predictions on labeled training examples provided as context. Unlike traditi

CoDG-Net: Structure-Guided Style Diffusion and Collaborative Learning to Mitigate Catastrophic Forgetting in Medical Image Domain Generalization

arXiv:2610.05053v1 Announce Type: new Abstract: Domain Generalization (DG) for medical image segmentation is both highly challenging and critically important. However, existing medical DG methods larg

ConEx: Human-Interpretable Saliency Maps via Concept-Aware Attribution

arXiv:2610.04605v1 Announce Type: new Abstract: Many visual explanation methods in computer vision highlight pixel importance but struggle to link these low-level cues to semantically meaningful conce

safetyarxiv-cs-cv

Conformal Prediction with Paraphrase-Aware Scoring for LLM Uncertainty Quantification

arXiv:2610.04239v1 Announce Type: cross Abstract: Uncertainty quantification (UQ) for large language models (LLMs) aims to provide reliable measures of predictive confidence, yet current methods are o

Consideration Circuits: Depth Separation and Universality Beyond a Single Softmax

arXiv:2610.04143v1 Announce Type: new Abstract: Most feature-based choice models, classical and deep, score items and apply a single softmax. We introduce consideration circuits (CC), feature-based mo

Contrastive Time Series Forecasting with Anomalies

arXiv:2512.11526v2 Announce Type: replace Abstract: Time series forecasting predicts future values from past data. In real-world settings, some anomalous events have lasting effects and influence the

Controllable and Photorealistic Pedestrian Risky Motion Generation for End-to-End Driving Safety Evaluation

arXiv:2610.06171v1 Announce Type: new Abstract: Evaluating end-to-end autonomous driving under rare, safety-critical vehicle-pedestrian interactions requires photorealistic, sensor-level scenarios. Ho

Controllable Road Marking Generation

arXiv:2610.05771v1 Announce Type: new Abstract: Lane and road markings provide critical guidance for vehicle navigation and multi-agent coordination, yet authoring them at scale remains a manual workf

Correct Verdicts, Flawed Reasoning: Structured Auditing of LLM-based Vulnerability Reasoning

arXiv:2610.06366v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly deployed for automated software vulnerability analysis. Binary classification alone is insufficient; pra

Coupling Noisy Pairwise Knowledge to the DAG Posterior for Causal Discovery

arXiv:2610.04559v1 Announce Type: new Abstract: External causal reports can improve structure learning from limited observations, but their reliability varies across sources and variable pairs. We int

COVER: Learning to Accept More in Selective Sleep Staging

arXiv:2610.03911v1 Announce Type: new Abstract: Traditional sleep-staging methods apply the same model to every EEG epoch. Such uniform deployment expends computation on epochs that a smaller model co

Hardware

Cut Binary Cross Entropy: Efficient Large-Vocabulary Loss and Gradient Kernels for Sequential Recommendation

arXiv:2610.05559v1 Announce Type: new Abstract: Industrial sequential recommender systems operate over massive item catalogs (e.g., 10^5--10^7 items). Multi-label recommendation models are trained wit

hardwarearxiv-cs-lg

D-DOIT: Training-free Adaptation of Discrete Diffusion via Doob's h-Transform

arXiv:2610.04938v1 Announce Type: new Abstract: We propose D-DOIT (Discrete Doob-Oriented Inference-time Transformation), a training-free and efficient adaptation method for discrete diffusion models

Decouple, Purify and Unite: Semantic-Structural Prototype Learning for Federated Medical Segmentation

arXiv:2610.04700v1 Announce Type: new Abstract: Federated learning enables medical institutions to train a global model without sharing data, yet feature heterogeneity from diverse scanners or protoco

safetyarxiv-cs-cv

Deep Fair Learning: Task-Aware Fair Representations via Joint Distance-Covariance Regularization

arXiv:2504.06470v2 Announce Type: replace-cross Abstract: Ensuring fairness is essential as machine learning increasingly informs consequential decisions. However, many fairness-aware methods focus on

Deep Learning Denoising of Real SWOT Sea Surface Height Observations

arXiv:2610.03739v1 Announce Type: cross Abstract: The SWOT (Surface Water Ocean Topography) mission is currently providing unpreceded high-resolution measurements of Sea Surface Height (SSH), revealin

Deep Learning Reforms Image Matching: A Survey and Outlook

arXiv:2506.04619v2 Announce Type: replace Abstract: Image matching, which establishes correspondences between two images to recover 3D structure and camera geometry, is a cornerstone of computer visio

dIon: Fragmentation-Based Invariance for Self-Supervised Learning of Tandem Mass Spectra

arXiv:2610.06282v1 Announce Type: new Abstract: We introduce a novel invariance for peptide tandem mass spectrometry data, unlocking self-supervised representation learning that improves de novo seque

Direct Intermediate Initialization for Tilted Diffusion Samplers

arXiv:2610.06834v1 Announce Type: cross Abstract: Some diffusion posterior samplers construct Gaussian-tilted intermediate distributions along the reverse process. We observe that these targets can be

Divide-and-Conquer CoT: RL for Reducing Latency via Parallel Reasoning

arXiv:2601.23027v2 Announce Type: replace Abstract: Long chain-of-thought reasoning (Long CoT) is now fundamental to state-of-the-art LLMs, especially in mathematical reasoning. However, LLM generatio

DreamFormer: Dream Imitation with a Transformer World Model for Language-Conditioned Robotic Manipulation

arXiv:2610.04540v1 Announce Type: new Abstract: We introduce DreamFormer, a model-based agent that acquires language-conditioned, multi-task skills by imitating expert demonstrations within the latent

Local Ai

DriftSR: One-Step Real-World Image Super-Resolution via Distribution Drifting

arXiv:2610.04819v1 Announce Type: new Abstract: One-step real-world image super-resolution (Real-ISR) offers efficient inference, but recovering realistic and perceptually rich details often relies on

local-aiarxiv-cs-cv

Agents

DUET: Co-Evolving Solver and Grader Agents

arXiv:2610.04087v1 Announce Type: new Abstract: Agentic workflows are increasingly used across domains such as technology, finance, and enterprise operations. As these agents become more widely deploy

agentsarxiv-cs-lg

DV-Lens: Revealing the Functional Organization of Language Model Parameters

arXiv:2610.04489v1 Announce Type: cross Abstract: Understanding parameter functions helps elucidate the internal mechanisms of large language models (LLMs). However, how to connect parameters from dif

Dynamic Harness Search: Building Multi-Agent Systems Per-Query via Prediction

arXiv:2610.04137v1 Announce Type: new Abstract: Agent harnesses specify the roles, instructions, tools, and communication structure used to solve a task, and the right harness depends on the query. Be

Dynamic Time Step Prediction in Inverse Heat Dissipation for Blur-Like Image Restoration Tasks

arXiv:2610.03942v1 Announce Type: new Abstract: When using diffusion models to target image restoration problems, diffusion inversion is typically employed to retain relevant image information from th

researcharxiv-cs-cv

Dynamics-Aware Adaptive Corridors with Feasibility-Perturbed Trust-Region SQP for Certified Nonholonomic Motion Planning

arXiv:2610.05796v1 Announce Type: new Abstract: Optimisation-based parking planners usually impose collision constraints only at the time samples, so a vehicle corner can cut an obstacle between sampl

EEGDM: Label-Efficient EEG Representation Learning with Generative Diffusion Model

arXiv:2508.14086v4 Announce Type: replace Abstract: Electroencephalography (EEG) is a critical tool for monitoring brain activity and diagnosing neurological disorders such as epilepsy. However, learn

Tutorials

Efficient Graph Generation via Direct Prediction and Flow Matching

arXiv:2610.05397v1 Announce Type: new Abstract: Generative modeling of graph-structured data is crucial for tasks ranging from drug discovery to social network simulation. Among these models, denoisin

tutorialsarxiv-cs-lg

Efficient Secure Federated Learning via Information-Theoretically Secure Key Distribution: A Medical Imaging Case Study

arXiv:2610.06420v1 Announce Type: new Abstract: Federated Learning (FL) enables collaborative training of models across institutions without centralizing sensitive data, making it well-suited for priv

Efficient Test-time Adaptation through Candidate Verification and Divergence Shifts

arXiv:2610.06147v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot transferability but remain vulnerable to target-domain shifts at inference time. Test-time adapta

EORestore-Agent: Fidelity-Guided Agentic Restoration of Remote Sensing Images with Composite Degradations

arXiv:2610.06196v1 Announce Type: new Abstract: Remote sensing images often carry composite degradations, in which haze, cloud, noise, blur, low light, and low resolution coexist. Restoring them requi

Event-based Continuous Color Video Decompression from Single Frames

arXiv:2312.00113v4 Announce Type: replace Abstract: We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional ca

researcharxiv-cs-cv

Evolving LLM-Generated Features for Interpretable Classification

arXiv:2610.03951v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as classifiers, yet they operate as opaque systems whose decisions are difficult to interpret, which

EvoMem-VLA: State-Evolution Memory for Long-Horizon Robot Manipulation

arXiv:2610.05418v1 Announce Type: cross Abstract: Most vision-language-action (VLA) models rely on current observations and lose task-relevant evidence once it leaves view, limiting performance on lon

EvoState: Closed-Loop Visual State Management for Long-Form Video Generation

arXiv:2606.16184v2 Announce Type: replace Abstract: Multi-shot long-form video generation remains challenging due to identity drift and compounding inconsistencies across shots. Existing methods encod

Extending Dynamic World Surface Water Mapping to Sentinel-1 with AlphaEarth Embeddings

arXiv:2610.06704v1 Announce Type: new Abstract: Dynamic World (DW) maps land use and land cover globally at 10 m from Sentinel-2 (S2) imagery, but only for cloud-free observations, which limits where

F^2 SLAM: Turning Feed-Forward Geometry into Persistent Factors for SLAM

arXiv:2610.05207v1 Announce Type: new Abstract: Feed-forward 3D models provide strong multi-view geometric priors, while on- line simultaneous localization and mapping (SLAM) relies mainly on local me

researcharxiv-cs-cv

Hardware

FlashGaze: Training-Free Multi-Scale Patch Pruning For Efficient Video Understanding

arXiv:2610.04225v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong performance in video understanding, yet efficiently processing long, high-resolution v

hardwarearxiv-cs-cv