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Negation-Aware Weighted Information Fusion for Reliable Evidential Reasoning

arXiv:2509.00754v3 Announce Type: replace Abstract: Dempster--Shafer theory (DST) provides an attractive framework for multi-source information fusion. However, its effectiveness critically depends on

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Human DGX agent

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NeuIDO: Neural Intrinsic Dynamics Operator for Physics-Informed 4D World Models

DGX agent

arXiv:2609.24313v1 Announce Type: new Abstract: World models aim to capture environmental dynamics and predict future trajectories, showing growing potential for embodied intelligence. Physics-informe

tutorialsarxiv-cs-cv

22 Sept 2026

Local Ai

Neural Residual Modeling for Scientific Data Compression under Guaranteed Error Bounds

arXiv:2609.23185v1 Announce Type: new Abstract: Lossy compression of scientific simulation data increasingly relies on learned, latent-space architectures such as Residual Vector Quantization (RVQ), w

local-aiarxiv-cs-lg

Neural Spectral Capacity: Measuring and Designing Architectures from Network Specification Alone

arXiv:2609.23087v1 Announce Type: new Abstract: Modern Transformer design and compression both reduce to allocating capacity under a budget. The standard scalars for these decisions, #Params and #FLOP

NLPCC 2026 Task 10: Citation-Level Faithfulness Verification with DeBERTa Ensembles and Class-Wise Calibration

arXiv:2609.22774v1 Announce Type: new Abstract: This paper presents our system for Track 2 of the NLPCC 2026 Shared Task 10 on citation-level faithfulness in AI-assisted scientific reporting. Given an

researcharxiv-cs-cl

Not All Ranks Are Equal: Budget-Aware LoRA Merging Across Tasks

arXiv:2609.22237v1 Announce Type: new Abstract: Merging low-rank adapters (LoRAs) promises to eliminate the overhead of swapping task-specific weights at inference time. However, existing merging meth

Not All Task Vectors Need Equal Rank: Energy-Proportional Allocation for Model Merging

arXiv:2609.24517v1 Announce Type: cross Abstract: Model merging aims to combine multiple fine-tuned models derived from a common pretrained model into a single multi-task model without additional join

Object-Centered Reconstruction for Vision-Based 3D Force Estimation

arXiv:2609.23856v1 Announce Type: new Abstract: Excessive force may damage tissue and increase the risk of anastomotic leakage in robotic colorectal surgery. Although the da Vinci 5 provides force sen

researcharxiv-cs-ro

Object-Centric Conditioning for Visuomotor Flow Matching

arXiv:2609.24155v1 Announce Type: new Abstract: Robot visuomotor policies are commonly formulated as autoregressive, diffusion-based, or more recently, flow matching models. Among them, Action-to-Acti

safetyarxiv-cs-ro

Observational Equivalence of LLM and Human Annotation

arXiv:2609.22133v1 Announce Type: new Abstract: In this paper, we show that LLM and human coding are observationally equivalent in terms of annotation quality: recent LLMs agree with expert coders at

researcharxiv-cs-cl

Observing and Controlling Features in Vision-Language-Action Models

arXiv:2603.05487v2 Announce Type: replace Abstract: Vision-Language-Action models (VLAs) have shown remarkable progress towards embodied intelligence. While their architecture partially resembles that

safetyarxiv-cs-ro

Odometry-Aided Real-Time Mapping for Underwater Robots Using Forward-Looking Sonar

arXiv:2609.24195v1 Announce Type: new Abstract: Reliable perception is essential for underwater vehicles operating in complex environments, where light attenuation and scattering often degrade visibil

researcharxiv-cs-ro

Agents

Offline Reinforcement Learning for Distribution-Grid Protection

arXiv:2609.24703v1 Announce Type: cross Abstract: Data-driven protection may complement conventional relays in distribution grids whose operating conditions vary with distributed generation, switching

agentsarxiv-cs-lg

Tutorials

OJOx: Specification-Conditioned Demonstrations for Embodied AI in Construction

arXiv:2609.22289v1 Announce Type: new Abstract: Large-scale egocentric and whole-body human demonstrations are becoming a primary source of data for embodied intelligence. They record what people perc

tutorialsarxiv-cs-ro

Omni2Web: Benchmarking Audiovisual Website Development

model-releasesarxiv-cs-cv

arXiv:2609.23417v1 Announce Type: cross Abstract: Screen-recorded web editing requests contain weak deictic expressions such as ``this'' and ``there,'' whose referents depend on speech, cursor traject

OmniEdu: Open Foundation Models for Learning and Teaching

arXiv:2609.23088v1 Announce Type: new Abstract: Educational foundation models must solve problems, understand curriculum structure, diagnose learner difficulties, and provide appropriate instructional

On attention heads and bilinear forms

arXiv:2609.22990v1 Announce Type: new Abstract: We study the symmetric and antisymmetric parts of bilinear forms in the attention heads of trained large language models. We introduce an orthogonally i

On Emergent Capabilities and Model Merging

arXiv:2609.24504v1 Announce Type: new Abstract: Fine-tuned checkpoints and adapters now fill public repositories, and the most common operation applied to these artifacts is model merging: arithmetic

On Generalized Naive Bayes with Continuous Features

arXiv:2609.23819v1 Announce Type: cross Abstract: The Generalized Naive Bayes (GNB) model was introduced for discrete and categorical random variables as an extension of classic Naive Bayes. We now ac

On Learning Spatial Structure from Pre-Beamforming Per-Antenna Range-Doppler Radar Measurements

arXiv:2604.01921v2 Announce Type: replace Abstract: Automotive radar perception pipelines commonly construct angle-domain representations via beamforming before applying learning-based models. This wo

On Mitigation of Subliminal Learning in Large Language Models

arXiv:2609.22215v1 Announce Type: new Abstract: Knowledge distillation can transmit unintended behavioral traits from a teacher model to a student through training data that appear semantically unrela

On Policy Stochasticity in Mutual Information Optimal Control of Linear Systems

arXiv:2507.21543v3 Announce Type: replace-cross Abstract: Mutual information regularization has recently been studied in reinforcement learning (RL) as an extension of entropy regularization, in which

Agents

On the Control of Mobile Ad-Hoc Agent Deployments in Partially Observed Space

arXiv:2609.23060v1 Announce Type: new Abstract: We study the online deployment of mobile ad hoc networks in unknown orthogonal environments, formalized as the Partially Observable Cooperative Guard Ar

agentsarxiv-cs-ro

On the Efficiency-Safety Dilemma in Large Reasoning Models

arXiv:2609.23587v1 Announce Type: new Abstract: Large reasoning models (LRMs) incur high inference costs, often mitigated by efficiency techniques like quantization and pruning. However, the impact of

safetyarxiv-cs-cl

On the Information-Theoretic Limits of Latent-Space Watermarking Through Pretrained Generators

arXiv:2609.24377v1 Announce Type: cross Abstract: We study latent-space watermarking through a pretrained generator using a prescribed latent-to-output stochastic mapping, called the renderer. A water

On The Robustness-Resolution Tradeoff In Temporal Quantization Of Event Streams

arXiv:2609.22295v1 Announce Type: new Abstract: Event pipelines often discretize asynchronous timestamps before learning. This step looks harmless, but its stability depends directly on temporal resol

One Patch, Three Roles: What Is Actually Coupled in Autoregressive Time-Series Forecasting?

arXiv:2609.23686v1 Announce Type: new Abstract: Patch-based autoregressive time-series forecasting often ties input representation, learned transitions, and recursive execution to one patch length. We

One to More, More to One: Category-Aware Iterative Expert Training for Software Engineering Agents

arXiv:2609.23377v1 Announce Type: cross Abstract: Repository-level software engineering (SWE) comprises heterogeneous task categories, whose progress under pooled agentic reinforcement learning can be

safetyarxiv-cs-cl

OnlineWM: Causality-Aware Active Online Learning for Effective World Modeling

arXiv:2609.23753v1 Announce Type: new Abstract: Generative world models aim to predict future states conditioned on actions, where action controllability is fundamental for reliable dynamics modeling.

onPanda: Efficient Annotation of On-Policy Alignment Data for LLMs and Agents via Token-Level Correction

arXiv:2609.24983v1 Announce Type: new Abstract: We present onPanda, an interactive tool for efficiently annotating LLM alignment data and agent trajectories. onPanda adopts token-level correction as i

Hardware

Open-Jev Judgments on CallScreenBench: Calibrated One-Pass Scam Screening with a Small Language Model

arXiv:2609.23959v1 Announce Type: new Abstract: Screening a phone call for fraud needs a trustworthy probability after every caller turn, in milliseconds. Jev-style typed decisions promise exactly tha

hardwarearxiv-cs-cl

Agents

OpenBlock: Constructive and Verified Content Generation for Adaptive Tile-Matching Games

arXiv:2609.22177v1 Announce Type: new Abstract: Tile-matching puzzle games serve hundreds of millions of players, yet the content-generation algorithms that decide which pieces to present at each turn

agentsarxiv-cs-lg

OpenFlyScan: A Quality-Guided Aerial Reconstruction System for Consumer Drones

arXiv:2609.24253v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) provides high-fidelity scenes for large-scale embodied simulation, but constructing large-scale urban assets remains cons

Opinion Leader Dynamics: How Sparse Attention Shapes Token Clustering

arXiv:2609.24202v1 Announce Type: new Abstract: Sparse attention reduces the quadratic cost of global self-attention while retaining strong empirical performance, but how its restricted interactions s

Opt2VLA: Force-Aware Vision-Language-Action for Contact-Rich Humanoid Whole-Body Manipulation

arXiv:2609.23968v1 Announce Type: new Abstract: Humanoid robots are expected to perform diverse human-level tasks in daily environments, many of which require precise regulation of interaction forces.

safetyarxiv-cs-ro

Applications

Optimal Multi-way Decision Trees for Stratified Sampling in Online Controlled Experiments

arXiv:2609.23308v1 Announce Type: new Abstract: Online controlled experiments, or A/B tests, are widely used to estimate causal effects on digital platforms. A central challenge is to improve experime

applicationsarxiv-cs-lg

Optimal No-Regret Learning for Repeated Prophet Inequality

arXiv:2609.23265v1 Announce Type: new Abstract: We study repeated prophet inequalities under prefix feedback. In each of T rounds, a learner encounters fresh values drawn independently from n boxes wi

Optimal Sample Complexity of Stable Discounted Markov Decision Processes

arXiv:2302.07477v4 Announce Type: replace Abstract: We study the optimal sample complexity of tabular reinforcement learning for infinite-horizon discounted Markov decision processes. The unrestricted

Optimal Symmetries in Binary Classification

arXiv:2408.08823v2 Announce Type: replace Abstract: We develop a theoretical foundation for designing group-equivariant neural networks that align the choice of symmetries with the underlying probabil

Optimizers for Diffusion Models: A Controlled Benchmark

arXiv:2609.23055v1 Announce Type: new Abstract: Discrete diffusion models now match autoregressive language models on several benchmarks, while the question of how best to train them has received far

ORDER: A Fictitious-World Benchmark for Domain-Adaptive Embodied AI

model-releasesarxiv-cs-ro

arXiv:2609.22285v1 Announce Type: new Abstract: Adapting language models to new domains via continual pre-training raises a basic evaluation problem: if the training corpus overlaps with what the mode

Orientation-Aware Control and Trajectory Design for Aerial RIS-Assisted Wireless Communications

arXiv:2609.23157v1 Announce Type: cross Abstract: Aerial Reconfigurable Intelligent Surfaces (ARISs) can enhance wireless connectivity in obstructed environments by combining reconfigurable metasurfac

researcharxiv-cs-ro

Local Ai

ORION-CMR: On-scanner Reporting with Integrated Foundation Model for End-to-End Cardiac MRI Analysis and Interpretation

arXiv:2609.23950v1 Announce Type: cross Abstract: Cardiovascular magnetic resonance (CMR) provides comprehensive cardiac assessment but remains underutilized because of the complexity of acquisition,

local-aiarxiv-cs-cv

OSCAR: Order-aware Scoring and Calibration for AI Rankings

arXiv:2609.24128v1 Announce Type: cross Abstract: Judge-specific sensitivity is useful for aggregating pairwise LLM evaluations, but its interpretation depends on which systematic presentation effects

OSWorld-Pro: Process-based Evaluation for Computer Use Agents

arXiv:2609.24890v1 Announce Type: new Abstract: Evaluation of Computer-Use Agents (CUAs) is often limited to the final deliverables they create (at the end of hundreds of steps) and assessed with func

Overlay_dx - Automating forecasting evaluation

arXiv:2609.24586v1 Announce Type: new Abstract: Traditional evaluation metrics provides numerical values but often lack comprehensibility, hindering effective differentiation of model performances. Ou

P2Flow: Phoneme-aware Progressive Flow Matching for Extreme Speech Super-Resolution

arXiv:2609.24138v1 Announce Type: cross Abstract: Generative models have recently demonstrated considerable promise in speech super-resolution (SSR). Nevertheless, the majority of existing work has co

Tutorials

PAC-Bayesian Meta-Learning for Few-Shot Identification of Linear Dynamical Systems

arXiv:2609.24117v1 Announce Type: new Abstract: Identifying linear time-invariant (LTI) dynamical systems is challenging when trajectories are short, noisy, or high-dimensional. Traditional system ide

tutorialsarxiv-cs-lg