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Depth-Guided Contrastive Learning for 2D Representations with 3D Spatial Awareness

arXiv:2609.28159v1 Announce Type: new Abstract: Standard contrastive learning frameworks are mainly designed from a semantic perspective, yet learning 2D visual representations that preserve 3D spatia

researcharxiv-cs-cv

Content type

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Design and Modeling of a Single-Port Three-Arm Robotic Tool for Minimally Invasive Neurosurgery

DGX agent

arXiv:2609.27099v1 Announce Type: new Abstract: Surgical robots require highly dexterous and compact robotic systems capable of operating effectively within confined anatomical spaces. However, due to

researcharxiv-cs-ro

24 Sept 2026

Diff-RF: Mutually Reinforced Image Registration and Fusion via Degradation-Aware Learning

arXiv:2609.28235v1 Announce Type: new Abstract: Image registration and fusion aim to establish spatial correspondences from misaligned multi-modal source images, and integrate complementary informatio

safetyarxiv-cs-cv

Digital diglossia: Arabic between X and Facebook

arXiv:2609.28352v1 Announce Type: new Abstract: This study highlights the distribution of Standard Arabic (SA; H(igh) variety) and Colloquial Arabic (CA; L(ow) variety) across X and Facebook. 16754 pu

Dirichlet Process Mixtures of Trees with Gaussian Process Splits: A Bayesian Nonparametric Framework with Posterior Contraction Rate

arXiv:2609.27930v1 Announce Type: cross Abstract: We propose a Bayesian nonparametric mixture of regression trees with a Dirichlet process prior over tree-parameter pairs, enabling data-driven selecti

Discover, Falsify, Revise: Auditing Input-Use Claims from Source Code to Predictive Contribution in Agent-Discovered Cell Models

arXiv:2609.27234v1 Announce Type: new Abstract: AI virtual cells aim to predict cellular responses to specified interventions, yet held-out predictive performance alone does not establish use of the s

Discovery of fully efficient fault indicators along a data-based diagnosis process

arXiv:2609.28087v1 Announce Type: new Abstract: The integration of model-based and data-driven paradigms provides a powerful framework for fault diagnosis by combining the interpretability of analytic

Tutorials

Discrete Diffusion Models via Evolving Variational Autoregressive Networks

arXiv:2609.27306v1 Announce Type: new Abstract: Conventional score-based diffusion models learn scores without representing normalized densities, whereas tractable normalized models support both sampl

tutorialsarxiv-cs-lg

Discrete optimal transport is a strong audio adversarial attack

arXiv:2509.14959v4 Announce Type: replace-cross Abstract: In this paper, we investigate discrete optimal transport (DOT) as a black-box attack against modern automatic speaker verification (ASV) and a

Dissecting Advantage-Guided Post-Training for Vision-Language-Action Policies

arXiv:2609.28161v1 Announce Type: new Abstract: Advantage-guided reinforcement learning provides a practical way to post-train vision-language-action (VLA) policies using limited robot data. However,

safetyarxiv-cs-ro

Distillation for Efficient Multitask Manipulation Policies via Conditional Flow Matching

arXiv:2609.28107v1 Announce Type: cross Abstract: Advances in generative modeling have recently been extensively employed in robotics for policy learning. In particular, Conditional Flow Matching (CFM

Distilling Sequential Computation in Transformer Language Models

arXiv:2609.27233v1 Announce Type: new Abstract: Transformer language models process sequences token by token in an autoregressive manner, making growing contexts increasingly expensive. Yet many adjac

Diverse by Design: Architectural Constraints for Prototype-Based Interpretability

arXiv:2609.27194v1 Announce Type: new Abstract: Prototype-based neural networks provide inherent interpretability through case-based reasoning, yet suffer from critical limitations: prototypes converg

researcharxiv-cs-cv

DMM-Align: Closed-Loop Optimization for 2D-3D Registration with Dual-Role Diffusion

arXiv:2609.27794v1 Announce Type: new Abstract: 2D-3D registration remains brittle in challenging scenarios such as low overlap, occlusion, repetitive structures, and severe cross-modal ambiguity. A k

safetyarxiv-cs-cv

Do Center Biases Propagate? Robustness of Pathology Foundation Models in Whole-Slide Image Classification

arXiv:2609.28231v1 Announce Type: cross Abstract: Pathology foundation models (PFMs) have transformed computational pathology through powerful representation learning from histopathological images. PF

Do We Need Complex Topology Control? Distinct-Peer Random Routing Improves Cost-Efficiency in Sparse Multi-Agent Debate

arXiv:2609.27150v1 Announce Type: new Abstract: Multi-agent debate (MAD) has emerged as a promising paradigm for improving the reasoning accuracy of large language models (LLMs) through iterative peer

Do y'all remember the snake model evaluation test?

model-releasesr-localllama

Just watched a video from three years ago where Matt Berman tested Bard (yes, remember Bard?) and most of the tests were like summarization or logic tests. If it ever came to coding, it was the snake

Does Graph Structure Earn Its Place in Microservice Root-Cause Analysis? A Controlled Study on RCAEval, and What the Benchmark Was Really Measuring

arXiv:2609.27069v1 Announce Type: cross Abstract: Graph neural networks dominate recent work on microservice root-cause analysis, yet recent results question whether the graph contributes. Those resul

Hardware

Does Step Law Transfer to Small-Scale Language Models? An Empirical Recalibration Below 59M Parameters

arXiv:2609.27581v1 Announce Type: cross Abstract: Step Law gives power-law formulas for the optimal peak learning rate eta* and batch size B* when pre-training language models. It was calibrated on mo

hardwarearxiv-cs-cl

Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev use cases I have found so far. Jev is a nat…

Don't sleep on using Jev-as-a-Judge for agent evaluation. This is one of the most impressive Jev use cases I have found so far. Jev is a natural fit as a Judge, but it doesn't mean you use it everywhe

agentsdair-ai--x

DRSR: Learning Set-Level Deletion Risk for Efficient Long-Horizon Agents

arXiv:2609.27276v1 Announce Type: new Abstract: Long-horizon language-model agents accumulate reasoning traces, tool exchanges, and observations whose relevance changes with the current decision. Exis

Applications

DualStabSleepNet: A Dual-Domain Diffusion Stabilization Network for Robust Sleep Staging

arXiv:2609.27793v1 Announce Type: new Abstract: Existing deep learning approaches for automatic sleep staging suffer from limited robustness under heterogeneous recording conditions, where non-station

applicationsarxiv-cs-cv

DUGM-R: Uncertainty-Aware Dynamic Grid Mapping and Risk-Triggered Recovery for Learned Local Navigation

model-releasesarxiv-cs-ro

arXiv:2609.27338v1 Announce Type: new Abstract: Learned local navigation in crowded indoor environments is sensitive to how dynamic obstacle motion is represented, while collision-prone behaviour may

Dynamic, Decentralized Spatial Code Reuse for OCDMA LiDAR in Robot Swarms

arXiv:2609.28172v1 Announce Type: new Abstract: Robots in a LiDAR-equipped swarm mutually interfere when their optical ranging codes collide. Existing mitigations either assign codes statically -- req

agentsarxiv-cs-ro

EA-WM: Event-Aware Generative World Model with Structured Kinematic-to-Visual Action Fields

arXiv:2605.06192v2 Announce Type: replace-cross Abstract: Pretrained video diffusion models provide powerful spatiotemporal generative priors, making them a natural foundation for robotic world models

Hardware

EBRL: Asynchronous Embodied RL by Multi-Grained Resource Management

arXiv:2609.27547v1 Announce Type: new Abstract: Embodied reinforcement learning (RL) improves model capabilities with a pipeline of environment simulation, action generation, and model updates. These

hardwarearxiv-cs-lg

EduBehaviors: Assertion-based Schemas for Auditable Coding of Educational Dialogues

arXiv:2609.27043v1 Announce Type: new Abstract: Large language models have allowed the rapid deployment of pedagogical annotations corresponding to constructs of interest, allowing a natural language

Efficient Linear Bandits via Cluster-Aware Sketching

arXiv:2609.27594v1 Announce Type: new Abstract: We study the problem of computational efficiency for linear bandits in high-dimensional settings with a finite arm set. In linear bandits, the increase

researcharxiv-cs-lg

Hardware

Efficient MoE Training for Biological Foundation Models

Mixture‑of‑Experts (MoE) models scale capacity more efficiently than dense transformers by activating only a subset of expert subnetworks per token. NVIDIA’s Transformer Engine optimizes MoE training

hardwarenvidia-developer

EidosDoc: Implicit Structure Encoding for Cost-Effective Semi-Structured Document QA

arXiv:2609.27784v1 Announce Type: cross Abstract: Semi-structured documents are ubiquitous in scientific reports, financial statements, and technical manuals. Question answering over such documents re

Local Ai

EMA: Elastic and Performance Transparent Memory Across GPUs

arXiv:2609.27040v1 Announce Type: cross Abstract: Multi-GPU servers have become the standard building block of modern data centers, providing aggregated capacity through high-bandwidth interconnects.

local-aiarxiv-cs-ai

EmbodiedMemory-Bench: Benchmarking Embodied Memory for Long-Horizon Embodied Tasks

arXiv:2609.28236v1 Announce Type: new Abstract: Long-horizon embodied interaction requires agents to retain and continually update information about the environment as they observe, act, and encounter

safetyarxiv-cs-cv

EmbodiedSWE: Coding Agents for Long Horizon Dexterous Robotics

model-releasesarxiv-cs-ro

arXiv:2609.27308v1 Announce Type: new Abstract: We study coding agents for long-horizon, dexterous robotics and ask whether their solutions can provide scalable supervision for learning general robot

Emergi-PersonaOS: A Persona Agent Operating System for Situational Adaptation and Controllable Evolution

arXiv:2609.27417v1 Announce Type: new Abstract: Symbiosis between humans and digital beings offers a vision for the future of human--machine interaction. In enduring human--machine relationships, pers

agentsarxiv-cs-ai

EnComp: Lightweight Encoder-Only Context Compression for Retrieval-Augmented Question Answering

arXiv:2603.09222v2 Announce Type: replace Abstract: Efficient context compression is critical for retrieval-augmented question answering in resource-constrained settings, where long retrieved contexts

Local Ai

Energy-guided Recursive Model

arXiv:2607.10128v3 Announce Type: replace Abstract: Recursive models show promise on reasoning and language tasks, yet their test-time scaling lacks a principled criterion for selecting trajectories o

local-aiarxiv-cs-lg

Enhancing Multiclass Malware Classification in Resource-Constrained Environments

arXiv:2609.27950v1 Announce Type: cross Abstract: The emergence of multi-class malware attacks such as ransomware, spyware, trojans, etc., presents an increasing and serious threat to cybersecurity, p

researcharxiv-cs-lg

Enhancing Small Language Models for Power Outage Report Generation via Minimum Risk Training

arXiv:2609.27197v1 Announce Type: new Abstract: Minimum Risk Training (MRT) enables neural machine translation models to directly optimize sequence-level evaluation metrics instead of relying only on

EnSIMem: Entity-Structured Indexing for Long-Term Agent Memory

arXiv:2609.27279v1 Announce Type: new Abstract: An agent that interacts with users over long periods must recall facts, preferences, events, and changes from a continuously growing interaction history

agentsarxiv-cs-ai

Escaping Python Dependency Hell: A Hybrid Replay-and-Repair Pipeline for Python Dependency Resolution

arXiv:2609.26952v1 Announce Type: new Abstract: Dependency conflicts in Python ecosystems arise from incompatible version constraints, missing packages, and undocumented compatibility relationships, c

Evaluating ADC-only deep learning pipelines for breast cancer detection and segmentation using standalone diffusion-weighted MRI

arXiv:2609.27815v1 Announce Type: cross Abstract: Dynamic contrast-enhanced (DCE) imaging is the gold standard technique for the detection and characterization of breast cancer using magnetic resonanc

Evaluating Feedback Focus and Pedagogical Adaptivity in LLM-Generated Feedback on Student Writing

arXiv:2609.28026v1 Announce Type: cross Abstract: We investigate whether state-of-the-art large language models (LLMs) generate feedback that reflects the pedagogical practices of expert teachers in t

Evaluating Open-Weight LLMs for Turkish Domain Documents Under Retrieval and Hardware Constraints

model-releasesarxiv-cs-cl

arXiv:2609.28007v1 Announce Type: new Abstract: Most Turkish-capable large language models (LLMs) are evaluated using general-purpose benchmarks rather than long, structurally complex domain documents

Evaluation Choices Decide the Forecasting Leaderboard: Evidence from a Production Marketplace Panel

arXiv:2609.27867v1 Announce Type: new Abstract: A forecasting benchmark reports which method won. We show that the answer is set by the evaluator's choices before any model is fitted. We benchmark 24

Evaluation of pre-trained models for pedagogical assessment of novel AI-assisted educational questions

arXiv:2609.27749v1 Announce Type: new Abstract: The surge in AI-assisted generation of educational materials has outpaced our capacity to validate their pedagogical quality. Automated evaluation using

EvEMTBench: An Open Benchmark for Machine Learning in Power System Protection

arXiv:2609.28149v1 Announce Type: cross Abstract: Studies of machine-learning-based power system protection are difficult to compare because task definitions, measurement access, data partitions, metr

Even Sharper Bounds for Transductive Learning and Its Applications

arXiv:2609.28459v1 Announce Type: new Abstract: We introduce Sharper Transductive Local Complexity (STLC), a localized complexity method for transductive learning under uniform sampling without replac

Every week I go through hundreds of new AI papers to pick the top ones for our Top AI Papers of the Week digest. Besides reading a lot of pa…

Every week I go through hundreds of new AI papers to pick the top ones for our Top AI Papers of the Week digest. Besides reading a lot of papers, I have started to use agent teams a lot. Here is what

agentsdair-ai--x