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Cybflight: An Embedded Rust Autopilot for Aerial Robotics Research

arXiv:2609.31232v1 Announce Type: new Abstract: Bringing an aerial robotics method from simulation to flight should not require rebuilding a mature autopilot or adding a companion computer. Cybflight

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CytoSPM: Open-Vocabulary Cytopathology Detection with Structured Prompt Bank

DGX agent

arXiv:2609.31314v1 Announce Type: new Abstract: Cytopathology detection requires open-vocabulary recognition because cellular categories are fine-grained, long-tailed, and continuously evolving across

model-releasesarxiv-cs-cv

28 Sept 2026

DanLing NestedTensor: Composable Multi-Ragged Tensors for Deep Learning

arXiv:2609.30379v1 Announce Type: cross Abstract: Variable-size inputs are common in deep learning, but dense batching allocates a shared envelope and spends computation on padding. The cost multiplie

DAPEVO: Deep Adaptive Patch Frame-Event Visual Odometry

arXiv:2609.30947v1 Announce Type: new Abstract: Visual odometry is essential for autonomous navigation in GPS-denied environments, yet RGB-based methods remain vulnerable to motion blur, challenging i

agentsarxiv-cs-cv

Decodable In-Context State and Model Output Across Training

arXiv:2609.31401v1 Announce Type: new Abstract: Prior work established that a probe can decode an in-context binding on model errors and that probe-guided steering can repair some of them. We follow p

Deep-Learning Solvers and Surrogates for Infinity and p-Laplace Problems

arXiv:2609.30809v1 Announce Type: cross Abstract: We investigate the use of neural network solvers for infinity and p-Laplace problems, which are fundamental in nonlinear analysis and have practical a

Local Ai

DeepEdu-v1: Efficient and Scalable Agentic LLMs for Vietnamese Education

arXiv:2609.31568v1 Announce Type: new Abstract: AI tutoring could markedly improve learning outcomes for students in developing regions such as Vietnam, yet the two obvious paths both fall short. Clou

local-aiarxiv-cs-ai

Demo: Generative AI helps Radiotherapy Planning with User Preference

arXiv:2512.08996v2 Announce Type: replace-cross Abstract: Radiotherapy planning is a highly complex process that often varies significantly across institutions and individual planners. Most existing d

safetyarxiv-cs-ai

DepthEvidence: Unifying Metric Depth Prediction and Geometric Reasoning in Multimodal Language Models

arXiv:2609.31103v1 Announce Type: cross Abstract: Spatial reasoning with metric constraints requires linking objects to geometric measurements and preserving their numerical content during language re

Design and Characterization of a Variable-Length Continuum Mechanism with Force Locking

arXiv:2609.30759v1 Announce Type: new Abstract: The utility of flexible continuum mechanisms for dexterous navigation is often impaired by their low stiffness, making them ineffective at manipulation

Detecting Time Series Anomalies Like an Expert: A Multi-Agent LLM Framework with Specialized Analyzers

arXiv:2605.05725v2 Announce Type: replace Abstract: Time-series anomaly detection often returns scores or intervals, while analysts need to understand the abnormal behavior and the evidence supporting

agentsarxiv-cs-ai

Deterministic Regime Switching and Feasibility Inversion in Dynamic Tensor Rematerialization

arXiv:2609.31250v1 Announce Type: new Abstract: We report fine-grained, deterministic instability in Dynamic Tensor Rematerialization (DTR), an online eviction policy for memory-constrained DNN traini

safetyarxiv-cs-lg

Developing a Roadmap to an AI-first Organization: A Case Study in Embedded Software Development

arXiv:2609.30863v1 Announce Type: cross Abstract: The emergence of AI agents is expected to reshape software engineering by moving beyond AI as assistants towards systems capable of planning, executin

agentsarxiv-cs-ai

DGT-Map: Directional Global Traversability Mapping Utilizing Multi-Task Learning for Heterogeneous Vehicles

arXiv:2609.30461v1 Announce Type: new Abstract: Off-road traversability is direction-dependent and vehicle specific, yet most global maps assign a single isotropic cost to each location. Existing lear

Diagnosing the Sources of Compositional Failure in Vision-Language Models: A Controlled Analysis

arXiv:2609.31456v1 Announce Type: new Abstract: Vision-language models (VLMs) often struggle with compositional reasoning tasks, but the reasons for this underperformance remain unclear. A common hypo

researcharxiv-cs-cv

DIAL: Position-Debiased LLM Judges with Adaptive Human Preference Calibration

arXiv:2609.31215v1 Announce Type: new Abstract: Large language models (LLMs) as a judge enable scalable evaluation, but their judgments can be sensitive to response order and, even after removing such

safetyarxiv-cs-ai

Didn't expect this 🤯 We replaced embeddings with Jev in GPT Researcher's RAG pipeline and tested both on 28 research tasks from SimpleQA an…

Didn't expect this 🤯 We replaced embeddings with Jev in GPT Researcher's RAG pipeline and tested both on 28 research tasks from SimpleQA and open ended research. Jev beat embeddings on every quality m

agentsharrison-chase--x

Different Corruptions, Different Signals: Uncertainty and Loss in Federated Data Quality

arXiv:2609.31454v1 Announce Type: cross Abstract: Federated learning (FL) data corruption can affect either inputs or labels, but it remains unclear whether input-conditional uncertainty and predictio

researcharxiv-cs-ai

Differentiable RNA Secondary Structure Extraction for Deep Learning

arXiv:2609.30752v1 Announce Type: new Abstract: Many deep learning approaches to RNA secondary structure prediction have recently been proposed. They typically output a weight matrix W where W_{ij} is

Differential Attention Unlocks Complementary EEG and Speech Fusion for Emotion Recognition

arXiv:2609.31399v1 Announce Type: new Abstract: Multimodal emotion recognition (MER) increasingly pairs EEG with speech, treating internal neural signals and external vocal expression as informative v

Differentially-Private Decision Trees and Provable Robustness to Data Poisoning

arXiv:2305.15394v3 Announce Type: replace Abstract: Decision trees are interpretable models that are well-suited to non-linear learning problems. Much work has been done on extending decision tree lea

DiffusionShadow: Diffusion-based Shadow Caching for Neural Volume Rendering

arXiv:2609.30658v1 Announce Type: cross Abstract: Implicit neural representations (INRs) have gained momentum in scientific visualization due to their compactness and scalability to large datasets, ma

Local Ai

Distributed Learning as a Service: The Developer's Perspective

arXiv:2609.31061v1 Announce Type: new Abstract: Application developers of distributed learning services face challenges that a typical federated learning loop does not address. Specifically, the model

local-aiarxiv-cs-lg

Distribution-Conditioned Transport

arXiv:2603.04736v2 Announce Type: replace Abstract: Learning a transport model that maps a source distribution to a target distribution is a canonical problem in machine learning, but scientific appli

Distribution of hitting times for dissipative random dynamical systems on R^d, with application to stochastic gradient descent

arXiv:2609.30274v1 Announce Type: cross Abstract: Machine Learning and more specifically Deep Learning involves solving large scale nonconvex optimization problems. Several algorithms have been propos

Do LLMs Understand Context? A Knowledge Graph-Based Evaluation Framework

arXiv:2609.30484v1 Announce Type: new Abstract: While large language models (LLMs) have achieved remarkable linguistic capabilities, a profound question lingers at their core: do these models truly co

researcharxiv-cs-ai

Applications

Do Neural Networks Preserve Case Structure? Case-Based Decomposition, Interpretation, and Decision Consistency

arXiv:2607.11347v2 Announce Type: replace Abstract: Neural networks increasingly inform consequential decisions, making their reliability increasingly important. Yet their internal mechanisms provide

applicationsarxiv-cs-ai

Do we need to answer that question? Salience and Answerability of Potential Questions in Naturalistic Dialogue

arXiv:2609.31130v1 Announce Type: new Abstract: We empirically investigate Question Under Discussion based modelling in naturalistic dialogue by studying whether the salience of generated potential qu

safetyarxiv-cs-cl

Does Thinking Help Fairness? Reasoning Tokens Resolve Some Biases but Create More

arXiv:2609.30768v1 Announce Type: new Abstract: Thinking in reasoning language models (RLMs) has been subject to debate on whether it resolves or amplifies bias. Prior works have shown competing concl

Does Understanding Inform Generation in Unified Multimodal Models? From Analysis to Path Forward

arXiv:2511.20561v3 Announce Type: replace-cross Abstract: Recent years have witnessed significant progress in Unified Multimodal Models, yet a fundamental question remains: Does understanding truly in

researcharxiv-cs-cl

Does Uniform Discrete Diffusion Need Time?

arXiv:2609.30977v1 Announce Type: cross Abstract: Uniform discrete diffusion models (UDMs) commonly use explicit time conditioning, but we find that it can often be unnecessary in practice. In this pa

researcharxiv-cs-ai

Don't CLAP: Are Music-Text Models Bag-of-Words?

arXiv:2609.30540v1 Announce Type: cross Abstract: Text-to-music systems are assessed on audio quality and on how faithfully the music follows its prompt, and the CLAP score, the cosine similarity betw

researcharxiv-cs-cl

Double-stream registration with pyramid fusion for HDR video with alternating exposures

arXiv:2609.31108v1 Announce Type: new Abstract: High dynamic range (HDR) video reconstruction from al-ter-na-ting-exposure sequences remains challenging, especially in regions with extreme luminance v

researcharxiv-cs-cv

dRVG: Quadtree-Guided, Resolution-Complete Online Motion Planning for Polygonal Robots in Unknown Environments

arXiv:2609.31412v1 Announce Type: new Abstract: We present the dynamic rotation-stacked visibility graph (dRVG), an online motion planner that guides polygonal robots to specified goals in initially u

DualManip: Agentic Dynamic Manipulation via Dual-Path Semantic Reasoning and Geometric Adaptation

arXiv:2609.31112v1 Announce Type: new Abstract: Vision-language models (VLMs) enable open-vocabulary reasoning for robot manipulation, but their high inference latency limits responsiveness in dynamic

agentsarxiv-cs-ro

Local Ai

DyMD: Preserving Interaction Dynamics through Distribution Matching Distillation in Few-Step Video World Models

arXiv:2609.31349v1 Announce Type: cross Abstract: Large video diffusion models offer expressive priors for embodied prediction and learning, yet their many-step sampling remains costly for interactive

local-aiarxiv-cs-ai

Dynamic Regret in Online Convex Optimization with Indicator Switching Costs

arXiv:2609.30556v1 Announce Type: new Abstract: We study dynamic regret in online convex optimization with an indicator switching cost: a fixed penalty incurred whenever two consecutive decisions diff

Dynamic Welfare-Maximizing Pooled Testing

arXiv:2601.22419v2 Announce Type: replace-cross Abstract: Pooled testing uses one test to certify several agents as healthy when the pooled result is negative. We study a budget-constrained welfare pr

safetyarxiv-cs-ai

DynBranch: Speculative Subgraph Reuse for Dynamic Agentic LLM Serving

arXiv:2609.31047v1 Announce Type: cross Abstract: Agentic LLM workflows decide their execution paths at runtime. Downstream computation may be predictable, or may have run before, yet it cannot begin

agentsarxiv-cs-ai

Hardware

EAServe: Encode-Aware Disaggregated Serving for Multimodal Large Language Models

arXiv:2609.31551v1 Announce Type: cross Abstract: Disaggregating the two stages, Prefill and Decode, onto separate GPU pools is now a standard optimization for (text-only) LLM serving. However, multim

hardwarearxiv-cs-lg

Effects of Transcript Compression on LLM-based Medical Misinformation Detection in Japanese YouTube Videos

arXiv:2609.30882v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to assess long-form medical videos, but their effectiveness may depend on whether transcripts are pro

researcharxiv-cs-cl

Efficient Constrained Graph Search for Post-hoc Error Correction in Binary Classifiers

arXiv:2401.04282v2 Announce Type: replace Abstract: We introduce a model-agnostic framework for constrained post-hoc error correction in binary classifiers. Given a frozen base classifier, the method

Efficient Safety Benchmarking via Item Response Theory

arXiv:2606.20626v2 Announce Type: replace-cross Abstract: Safety benchmarks for language models are typically evaluated using static paradigms that treat all items as equally informative for all model

Electric Vehicle Charging Station Location Selection using Geospatial Artificial Intelligence (GeoAI)

arXiv:2609.30417v1 Announce Type: new Abstract: As electric vehicle (EV) adoption increases, ensuring efficient and well-distributed charging infrastructure has become a critical challenge. While many

safetyarxiv-cs-lg

EmoZone-Talker: Regional Semantic Control of Audio-Driven 3DGS Talking Heads via Facial Action Units

model-releasesarxiv-cs-cv

arXiv:2606.15848v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has shown strong potential for high-fidelity talking head synthesis. However, enabling fine-grained, interpretable, and

Enabling a Unified Cross-Domain Representation for Two-Finger Gripper Manipulation via Interaction-Centric Modeling

model-releasesarxiv-cs-cv

arXiv:2609.31207v1 Announce Type: cross Abstract: Achieving robust cross-embodiment generalization in imitation learning demands overcoming a critical representation flaw that inextricably entangles t

Hardware

ENAS: An Efficient Hardware-Aware Neural Architecture Search Framework for TinyML on Resource-Constrained Microcontrollers

arXiv:2609.30272v1 Announce Type: cross Abstract: We present extbf{ENAS}, a hardware-aware Neural Architecture Search (NAS) framework that combines a static feasibility check, a cell-based search spac

hardwarearxiv-cs-ai

Encryptability As a Coordinate Choice: Depth-One Homomorphic Federated Learning of Quantum Neural Networks

arXiv:2609.30581v1 Announce Type: cross Abstract: Encrypted training relies on keeping server-side updates low-degree. This constraint traditionally excludes models whose weights inhabit a compact Lie