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arXiv:2609.24784v1 Announce Type: new Abstract: AI governance increasingly requires providers and public authorities to reason about multiple AI instantiations, alternative versions, and deployment co

applicationsarxiv-cs-ai

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Correcting Within-Group Self-Selection Bias in Prioritized Replay

DGX agent

arXiv:2609.25297v1 Announce Type: new Abstract: Prioritized experience replay (PER) improves sample efficiency by replaying high-priority transitions, usually according to absolute temporal-difference

model-releasesarxiv-cs-lg

23 Sept 2026

Local Ai

Cosserat Modeling of Trimmed Helicoid Soft Arms with a Separated-Section Constitutive Law

arXiv:2609.25264v1 Announce Type: new Abstract: Cosserat rod models for soft robots usually construct sectional stiffness by summing material properties over a common cross-section. This assumption be

local-aiarxiv-cs-ro

COVER: Codec-Robust Video Watermarking with Generative Video Priors

arXiv:2609.26236v1 Announce Type: new Abstract: Video watermarking underpins copyright protection and provenance for generated media, yet almost every video is compressed by a codec before it is store

researcharxiv-cs-cv

CoVeR: Coverage-Based Routing of Verifier Calls in Agentic Retrieval

model-releasesarxiv-cs-cl

arXiv:2609.26086v1 Announce Type: new Abstract: An agentic retrieval system issues a sequence of search queries and must decide, at each step, whether the evidence collected so far is enough to stop.

CraftBench-UE: Deterministic Evaluation for Coding Agents in Unreal Engine

arXiv:2609.23142v1 Announce Type: new Abstract: Building gameplay features in a game engine requires more than code, as code that compiles and runs does not necessarily implement the requested gamepla

Local Ai

CREDO: Variance-Guided Rubric Evolution for Replay-Corrected Credit Assignment

arXiv:2609.24174v1 Announce Type: new Abstract: Long-horizon language agents receive sparse terminal feedback, while intermediate rubrics provide structured but potentially misspecified assessments of

local-aiarxiv-cs-ai

CricRAG: Retrieval Augmented Vision-Language Models for Personalized Cricket Coaching

arXiv:2609.26056v1 Announce Type: new Abstract: Vision-Language Models (VLMs) offer promising capabilities for automated sports coaching but face a fundamental limitation: they implicitly compare agai

safetyarxiv-cs-cv

Custom Node for Extract Prompt & Target Aspect Ratio/Dimensions from Qwen Image 2.1 PE

model-releasesr-stablediffusion

Hey everyone! I've been experimenting with Qwen Image 2.1 Prompt Enhancer (PE) lately and noticed an interesting detail in Qwen's official system prompts. The PE models output structured JSON containi

Applications

Damage Predicts Recovery: When Calibration Data Matters in Compressing Financial LLMs

arXiv:2609.26241v1 Announce Type: new Abstract: Post-training quantization and pruning rely on a small calibration corpus. Whether specialized domains such as finance require domain-matched calibratio

applicationsarxiv-cs-cl

DeceptionAnalyser: A Web-Based AI Tool for Performing Structured Deception Analysis with Argumentation Schemes and LLMs

arXiv:2609.24369v1 Announce Type: cross Abstract: Deception plays a central role in Intelligence operations, yet it remains difficult to analyse systematically without expert knowledge of reasoning pa

Decoding Guardrails: XAI-Guided Perturbation Analysis of Prompt Injection Detection

arXiv:2609.24801v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in production systems, raising concerns about their exposure to adversarial manipulation throug

safetyarxiv-cs-ai

Decoding Order Matters in Autoregressive Speech Synthesis

arXiv:2601.08450v2 Announce Type: replace-cross Abstract: Autoregressive speech synthesis often adopts a left-to-right order, yet generation order is a modelling choice. We investigate decoding order

researcharxiv-cs-ai

Decoupling Disease, Covariates, and Individual Variability: A Unified Disentanglement Framework for Medical Image Classification

arXiv:2609.25650v1 Announce Type: new Abstract: Accurately isolating disease-related features from confounding covariates (e.g., age, gender, site) and individual variations remains a fundamental chal

safetyarxiv-cs-cv

Deep Generative Crystal Structure Prediction: A Benchmark Study and a Controlled Test of Prototype Dependence

arXiv:2609.26502v1 Announce Type: cross Abstract: Deep generative models are widely reported to enable de novo crystal structure prediction (CSP), but their capability has not been measured consistent

Deep Reinforcement Learning on Item-Compatibility Graphs for One-Dimensional Bin Packing

arXiv:2609.25397v1 Announce Type: new Abstract: The one-dimensional bin packing problem (1D-BPP) is a classical NP-hard combinatorial optimization problem with applications ranging from logistics and

Deepfakes and Synthetic Media: Generation, Detection, and Governance

arXiv:2609.25017v1 Announce Type: new Abstract: Deepfakes, synthetic audiovisual content produced by deep generative models, have escalated into a critical threat across civilian and military domains,

safetyarxiv-cs-cv

DeepFEAv2: Deep Learning for Transient Finite Element Analysis Beyond Structured Meshes

arXiv:2609.26426v1 Announce Type: new Abstract: Finite Element Analysis (FEA) is widely used for transient mechanical simulations, but its high computational cost limits real-time and high-resolution

DeepSeek and Moonshot AI face Beijing's probe over potential data leaks to Anthropic

model-releasesr-localllama

The rumor about Kimi execs getting arrested finally has some legs. I believe the reality is more like under investigation for potential arrests or fine. submitted by /u/Ok_Warning2146 [link] [comments

DeepSPoC: A Deep Learning Based Sequential Propagation of Chaos

arXiv:2408.16403v2 Announce Type: replace Abstract: Classical particle methods based on propagation of chaos (PoC) have been developed for solving mean-field stochastic differential equations and thei

Applications

DefaultGNN: A Dual-Perspective GNN Framework for Predicting Corporate Default from Buyer-Seller Transaction Networks

arXiv:2609.25542v1 Announce Type: new Abstract: Corporate default prediction is a core problem in financial risk management, yet traditional credit models rely heavily on financial statements that are

applicationsarxiv-cs-lg

Delving into Asymmetric Information Dynamics for High-Fidelity Virtual Try-On

arXiv:2609.25881v1 Announce Type: new Abstract: Virtual try-on (VTON) requires precise pixel-level fidelity, yet mainstream Diffusion Transformers (DiTs) often suffer from texture degradation and stru

researcharxiv-cs-cv

Deploying Foundation Models for Embodied Navigation

arXiv:2609.25666v1 Announce Type: new Abstract: We present and tackle two problems associated with deploying Foundation Models (FMs) on Embodied Agents performing navigation: 1) Training bias in FMs l

safetyarxiv-cs-ro

Design and Implementation of an Ultra-Low-Cost Wall-Climbing Robot for Infrastructure Crack Detection

arXiv:2609.26130v1 Announce Type: new Abstract: Crack detection is a crucial process to ensure the safety and longevity of buildings and other infrastructure. In this paper, we developed a low-cost, a

safetyarxiv-cs-ro

Designing an Efficient Excavator Bucket for Lunar ISRU: A Comparative Study with Vision-Based Fill and Displacement Analysis

arXiv:2609.25724v1 Announce Type: new Abstract: This paper present a spiral-cavity wheel for lunar regolith excavation and a sensor-light evaluation stack that jointly estimates fill ratio (vision), s

researcharxiv-cs-ro

Designing and Analysing Argument Mining Pipelines: Towards a Comprehensive Assessment

arXiv:2609.26338v1 Announce Type: new Abstract: Argument Mining (AM) transforms natural language into its underlying argument structures. This transformation is typically realized through a sequence o

researcharxiv-cs-cl

Designing Task-Induced Arousal: A Multimodal Stress Induction Method for Interactive Experiments

arXiv:2609.26156v1 Announce Type: cross Abstract: HCI and HRI studies often require short, repeatable arousal manipulations that can run while participants continue interacting with a device or robot.

researcharxiv-cs-ro

Destination Support Restoration for Finite-Set Multimodal Trajectory Prediction

arXiv:2609.25942v1 Announce Type: new Abstract: Robots operating around pedestrians often reason over a finite set of predicted human futures. Repeated online updates can concentrate this limited pred

researcharxiv-cs-ro

Detecting GPT-Assisted Writing Using Interpretable Stylometric Features

arXiv:2609.26687v1 Announce Type: new Abstract: Distinguishing GPT-assisted from independently authored student writing has become a critical challenge in academia. This paper evaluates the discrimina

researcharxiv-cs-cl

Differentiable Fuzzy Inference Layer: A Monotone, Compositional Ordinal Reasoning Head for Large Language Models

arXiv:2609.26113v1 Announce Type: new Abstract: A state-of-the-art language model asked to interpret 'most of most students passed' typically answers 'most,' though composing two instances of 'most' y

researcharxiv-cs-cl

Differentiable Policy Transport over Multi-Layer Network Feasibility Geometry

arXiv:2609.26068v1 Announce Type: cross Abstract: Learning-based control is increasingly central to automating network operations. A learned policy, however, must satisfy cross-layer constraints on in

safetyarxiv-cs-lg

Diffusion Drafts, AR Verifies: Accelerating Document OCR with Self-Speculative Decoding

model-releasesarxiv-cs-cl

arXiv:2609.26638v1 Announce Type: new Abstract: Autoregressive OCR vision-language models accurately convert document images into text and structured markup, but require one sequential decoding step p

Diffusion-Induced Spatial Attention Overlapping Community Detection

arXiv:2609.26737v1 Announce Type: cross Abstract: Detection of overlapping communities is essential for modelling networks in which nodes participate simultaneously in multiple structural or functiona

DIFTA-3D: Depth-Consistent Instance-Level Feature Transfer and Adaptation of DINOv3 for 3D Detection

arXiv:2609.26702v1 Announce Type: new Abstract: RGB-D 3D instance detectors benefit from visual semantics, but the task-specific Faster R-CNN/ResNet branch used by IIFNet3D couples feature extraction

researcharxiv-cs-cv

Digital Twin-Driven VR Teleoperation with Multi-View Spatial Perception for Surgical Robots

arXiv:2609.25527v1 Announce Type: new Abstract: Current robot-assisted minimally-invasive surgery (RMIS) platforms provide a fixed console for the surgeon to view stereo endoscopic images and teleoper

safetyarxiv-cs-ro

Directional Total Variation-Regularized Implicit Neural Representations (DTV-INR) for Continuous Super-Resolution in Degraded Imaging Domains

model-releasesarxiv-cs-cv

arXiv:2609.25429v1 Announce Type: new Abstract: In this paper, we introduce the Directional Total Variation-Regularized Implicit Neural Representation (DTV-INR), an advanced variational paradigm that

Disaggregated Quantization: Specializing LLM Prefill and Decode

arXiv:2609.26333v1 Announce Type: new Abstract: Prefill and decode reward different approaches to quantization: low-precision arithmetic accelerates prompt processing, while compact weights reduce mem

Discovering Data Manifold Geometry through Geometric Properties

arXiv:2602.02611v2 Announce Type: replace Abstract: A prevailing paradigm in modern representation learning is the map-first approach, in which a representation map is learned from reconstruction, emb

Local Ai

Discovery-Driven Integration of Disjoint Tables via Text

arXiv:2609.26658v1 Announce Type: cross Abstract: Integrating heterogeneous datasets within data lakes is a critical challenge, particularly for semantically related tables that lack the explicit attr

local-aiarxiv-cs-cl

Agents

Discovery of Interpretable Surrogates via Agentic AI: Application to Gravitational Waves

arXiv:2605.11280v2 Announce Type: replace-cross Abstract: Fast surrogate models for expensive simulations are now essential across the sciences, yet they typically operate as black boxes. We present e

agentsarxiv-cs-ai

Discrete vs. Continuous: A Comprehensive Study of Unified Audio Understanding in LALMs

arXiv:2609.22851v2 Announce Type: cross Abstract: Large Audio Language Models (LALMs) utilize either continuous features or discrete tokens, yet the optimal representation paradigm for general audio u

Disentangling Heterogeneous Traffic Dynamics for Multi-Step Traffic Forecasting via Adaptive Spectral Decomposition

arXiv:2609.25777v1 Announce Type: new Abstract: Accurate multi-step traffic forecasting remains challenging because observed traffic signals contain heterogeneous temporal dynamics with different char

Agents

Divergent strategies and convergent outcomes in autonomous materials discovery

arXiv:2609.23957v1 Announce Type: new Abstract: Scientific agents are mostly evaluated on whether they complete tasks or recover known results; we instead study variation across repeated open-ended ca

agentsarxiv-cs-ai

Agents

Divide by Question, Conquer by Agent: SPLIT-RAG with Question-Driven Graph Partitioning

arXiv:2505.13994v3 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) systems empower large language models (LLMs) with external knowledge, yet struggle with efficiency-accuracy tra

agentsarxiv-cs-ai

Djinnlang: Higher-Level Programming by Unambiguous Specification with an LLM in the Compiler

arXiv:2609.23954v1 Announce Type: cross Abstract: Programmers write formal specifications, and LLMs implement them, proving that each implementation matches its spec. Taken to its extreme, this makes

researcharxiv-cs-ai

Do Implicit Personalization and Explicit Styles Conflict? PsPLUG: A Lightweight Plug-in for Balancing Personalization and Style in Customized LLMs

arXiv:2601.06362v3 Announce Type: replace Abstract: Personalized large language models are often expected to follow explicit style instructions, yet we find that such instructions can undermine the us

researcharxiv-cs-ai

Do Not Trust the Benchmark: Limitations of General LLM Rankings and a Case for Task-Specific Evaluation

arXiv:2609.23201v1 Announce Type: new Abstract: Benchmark scores increasingly influence the development, marketing, and selection of large language models (LLMs). Yet an overall score is interpretable

Do Synthetic Personas Predict Real Audience Response? A Sim-to-Real Study Where a No-Persona Baseline Beats Persona-Based Copy Simulation

model-releasesarxiv-cs-cl

arXiv:2609.25010v1 Announce Type: cross Abstract: Marketers increasingly use large language models (LLMs) as 'synthetic personas' to predict how an audience will react to a piece of copy before it shi