Search: “research”

When Does Adversarial Refinement Help? A Negative Result and Open Problem in Adapting R3GAN to Time Series Imputation

arXiv:2609.23102v1 Announce Type: new Abstract: Diffusion models and transformers have supplanted GANs for multivariate time series imputation, largely on grounds of GAN training instability. R3GAN (N

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Research

When Evidence Conflicts: Reliability-aware Meta-review Generation

DGX agent

arXiv:2609.24028v1 Announce Type: new Abstract: Generating coherent meta-reviews from multiple peer reviews is challenging when reviewer evidence conflicts and varies in reliability. Existing approach

researcharxiv-cs-cl

22 Sept 2026

When is a closed-form RGB->S/P ratio adequate? A hyperspectral characterization on natural scenes for mesopic display

arXiv:2609.24819v1 Announce Type: cross Abstract: Mesopic and low-light display transforms require, as their driving signal, a per-pixel scotopic-to-photopic luminance ratio (S/P); the exact spectral

When Quantization Preserves Accuracy but Not Evidence: Explanation-Aware Post-Training Quantization for Medical LLMs

arXiv:2609.24799v1 Announce Type: new Abstract: Post-training quantization (PTQ) enables efficient deployment of large language models, and PTQ methods are usually optimized and evaluated with generic

When Wider Views Fail: Stress-Testing Feed-Forward 3D Reconstruction

arXiv:2609.24839v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models enable efficient geometry estimation from sparse images, but their pretrained nature can make them vulnerable to d

Which Terrain Is Better? Preference Learning with VLM Prototypes for Off-Road Traversability Ranking

arXiv:2609.23673v1 Announce Type: new Abstract: In vision-based off-road navigation, a robot needs to know not only which obstacles to avoid but also which terrain is better. The first is handled by f

Whitening Inverts the Hierarchy: What the Norm of a Whitened Embedding Measures

arXiv:2609.23117v1 Announce Type: new Abstract: Whitening a foundation-model embedding and using its squared norm as a training-free likelihood surrogate is motivated by the observation that whitened

Why Ghost Outputs Teach: A Kernel-Based Understanding of Subliminal Learning

arXiv:2609.23260v1 Announce Type: new Abstract: Subliminal Learning (SL) is a recently identified phenomenon in which a student model acquires downstream task capabilities by matching seemingly unrela

WildfireSpreadBench: The Metric Decides the Model in Wildfire Spread Prediction

arXiv:2609.22191v1 Announce Type: cross Abstract: Machine learning is being increasingly used to predict where active wildfires will burn the following day, helping inform evacuation boundaries and co

WorldCrafter: Consistent Video World Model with Implicit 3D-aware Memory

arXiv:2609.24984v1 Announce Type: new Abstract: Video world models enable interactive exploration of dynamic environments, yet struggle to respect prior observations over long horizons and across view

Yarn tracking of large-scale 3D textile reinforcements using topological material features

arXiv:2609.22315v1 Announce Type: new Abstract: Automated segmentation of CT images has become increasingly important to enhance the reliability of simulations through the generation of high fidelity

You Can Tell Who's Asking: What the Web's Questions Are Made Of, and Where They Come From

arXiv:2609.24106v1 Announce Type: new Abstract: Questions scraped from the web are used across academia and industry as a proxy for what people want to know. Across QA training data, retrieval benchma

ZoAQ: Adaptive Zeroth-Order Querying via Query-Reuse Coupling

arXiv:2609.22115v1 Announce Type: new Abstract: Zeroth-order optimization (ZOO) estimates updates from function evaluations, making perturbation queries a primary cost. Fixed budgets spend the same nu

2D GauSS-MI: Efficient Active Scene Reconstruction with Balanced Visual and Geometric Quality

arXiv:2609.21516v1 Announce Type: new Abstract: Active reconstruction requires efficient active view selection to achieve high-quality reconstruction within limited onboard computational resources. Ex

Hardware

5 Companies Using NVIDIA AI for Clean Energy

Clean energy isn’t hard to come by, but the pace of large-scale adoption has historically been slow due to bottlenecks — including out-of-date infrastructure, elongated research and development timeli

hardwarenvidia-blog

A Differentiable Ray-Wave Framework for Hybrid Refractive-Diffractive System Modeling and Optimization

arXiv:2605.15418v2 Announce Type: cross Abstract: Hybrid optical systems combining refractive and diffractive optical responses have the potential to support new types of optical behavior, but they ar

A Fully Differentiable Neuro-Soft-Symbolic Framework for Perceptual Task Planning

arXiv:2609.21221v1 Announce Type: new Abstract: Perceptual planning tasks require two key capabilities: accurately perceiving uncertain scenes and planning valid action sequences following logical rul

A High-Payload Wall-Climbing Robot Using Passive Bistable Suction Cups

arXiv:2609.21584v1 Announce Type: new Abstract: Wall-climbing robots capable of scaling vertical surfaces could help automate hazardous or labor intensive tasks such as window washing, inspection, mai

A Hybrid Computational Intelligence Framework for scRNA-seq Imputation: Integrating scRecover and Random Forests

arXiv:2511.16923v1 Announce Type: cross Abstract: Single-cell RNA sequencing (scRNA-seq) enables transcriptomic profiling at cellular resolution but suffers from pervasive dropout events that obscure

A regret minimization approach to fixed-point iterations

arXiv:2509.21653v2 Announce Type: replace-cross Abstract: We propose a conversion scheme that turns regret minimizing algorithms into fixed point iterations, with convergence guarantees following from

A Smoothed Discrepancy Principle for Random Feature Methods and Neural Networks

arXiv:2609.21017v1 Announce Type: cross Abstract: We study data-driven early stopping for spectral regularisation methods in the classical non-parametric regression setting. Building on the discrepanc

Abstention and Noise Filtering: Two Missing Primitives of Softmax Attention

arXiv:2609.22005v1 Announce Type: cross Abstract: Gating the value pathway of attention reportedly improves language model pretraining, and prior studies disagree on why. We argue and provide experime

Accelerating Dense LLMs via L0-regularized Mixture-of-Experts

arXiv:2609.21672v1 Announce Type: new Abstract: Large language models (LLMs) achieve strong performance but suffer from slow and costly inference. Existing acceleration methods often lead to noticeabl

Adaptive Color Grading

arXiv:2609.21169v1 Announce Type: cross Abstract: Independent control of tonescale regions (e.g., shadows, highlights) is essential for painters, photographers and cinematographers to bring 2D images

Adaptive Uncertainty-Aware Modeling and Stochastic Radial Basis Function Predictive Control for Personalized Fluid Resuscitation

arXiv:2609.21821v1 Announce Type: cross Abstract: This paper presents a novel framework integrating Bayesian physiological modeling with optimal control strategies to achieve uncertainty-aware, person

Aggregated Posterior Predictive Checks for Generative Modeling

arXiv:2609.20999v1 Announce Type: cross Abstract: Latent variable generative models are commonly fit using simple priors over latent variables, but draws from these priors often fail to produce realis

ALINA: Advanced Line Identification and Notation Algorithm

arXiv:2406.08775v2 Announce Type: replace Abstract: Labels are the cornerstone of supervised machine learning algorithms. Most visual recognition methods are fully supervised, using bounding boxes or

Allometric Scaling Laws for Bipedal Robots

arXiv:2603.22560v4 Announce Type: replace Abstract: Legged robots operate across a wide range of physical scales, but how their designs should be adapted as size changes remains unclear. Here, we tack

An Introduction to Compression-Based Machine Learning

arXiv:2609.21309v1 Announce Type: new Abstract: Any lossless compression algorithm (like gzip) may be converted into a machine learning method, via either Normalized Compression Distance or the Minimu

Analysing the Linearity of Linguistic Relations in Language Model Embedding Spaces

arXiv:2609.21655v1 Announce Type: new Abstract: We propose a framework to analyse how strongly different linguistic relations are linearly encoded in language model embedding spaces. We formalise line

ANNLib: A Development Framework for Efficient Approximate Nearest Neighbor Search

arXiv:2607.17582v2 Announce Type: replace Abstract: Approximate Nearest Neighbor Search (ANNS) plays a pivotal role in modern deep learning pipelines. Recently, many ANNS systems have been proposed to

Attention-Aware Routing: Coupling Routing and Attention in MoEs

arXiv:2609.20974v1 Announce Type: new Abstract: In Mixture-of-Experts language models, the router typically selects and weights experts based on the token's hidden state, utilizing limited contextual

Authorization Revocation for Long-Running AI Agents: Root-Scoped Quiescence under Delegation and Asynchronous Execution

arXiv:2609.21284v1 Announce Type: cross Abstract: Long-running AI agents outlive initiating processes through credentials, delegated tasks, queues, callbacks, reservations, and provider-side operation

Model Releases

AutoRecLab: Describe the Experiment, Get the Code!

model-releasesarxiv-cs-ai

arXiv:2609.21863v1 Announce Type: new Abstract: Empirical evaluation is central to recommender-systems (RecSys) research, but turning experimental designs into executable code remains a manual and err

AVT-Fabric: Active Visuo-Tactile Perception via Adaptive Evidence Selection for Efficient Robotic Fabric Comparison

arXiv:2609.21377v1 Announce Type: new Abstract: Robotic fabric comparison needs to actively combine visual appearance and tactile cues. Here, we present AVT-Fabric, an RGB-first framework that allocat

Balanced Prompt Adaptation against Entropy-Induced Collapse for Test-Time Binary Segmentation

arXiv:2609.21743v1 Announce Type: cross Abstract: Entropy minimization is a standard objective for test-time adaptation (TTA), but it can fail in imbalanced binary segmentation. Unlike image classific

Bayesian classification of astronomical spectra with class uncertainties

arXiv:2609.21694v1 Announce Type: cross Abstract: Context: We developed a probabilistic machine learning method with the aim of performing the O(10)-way classification of low- and high-resolution spec

Model Releases

Benchmarking Autonomous Driving Planners Across Leaderboards: A Unified CARLA-Based Evaluation

model-releasesarxiv-cs-ai

arXiv:2509.22754v2 Announce Type: replace-cross Abstract: Autonomous driving remains a highly active research domain that seeks to enable vehicles to perceive dynamic environments, predict the future

Beyond Atomic Tokens: Factorizing Syllables for Language Model Pretraining

arXiv:2609.21362v1 Announce Type: new Abstract: Conventional tokenizers represent text as characters or statistically derived subwords, overlooking the internal phonological structure of syllables and

Beyond Reference-Based Evaluation: Reward Models for Meta-Evaluation of Grammatical Error Correction

arXiv:2609.21231v1 Announce Type: new Abstract: Reference-based metrics for Grammatical Error Correction (GEC) such as M^2 and ERRANT assume that the reference set enumerates all valid edits, and ther

Beyond WER: Entity and Disfluency Recall in Accented Conversational ASR

arXiv:2609.20828v1 Announce Type: new Abstract: ASR systems optimised for Word Error Rate (WER) often miss named entities and filled pauses in accented conversational English, both critical for langua

Bilevel Optimization of Topology and Hyperparameters (BOTH)

arXiv:2609.21758v1 Announce Type: new Abstract: Topology optimization (TO) represents a significant step towards automating the design process: given a working simulation, TO can produce a viable prot

Brownian Heads for Deep ReLU Representations: Activation Mass and the Cost of Same-Sample Selection

arXiv:2609.21422v1 Announce Type: cross Abstract: Deep representation learning often selects hidden features and fits the final predictor on the same sample, so fixed-feature analysis performed after

CASE: Contrastive Activation for Class-Sensitive Explanations

arXiv:2506.07327v4 Announce Type: replace Abstract: Saliency methods are widely used to visualize which input features are deemed relevant to a model's prediction. However, their visual plausibility c

Catch Me If You Can: Real-Time Feedback Denoising for Responsive VLAs

arXiv:2609.21022v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown strong generalization in robotic manipulation by combining semantic knowledge from pretrained vision-lang

Catena: A Comprehensive Software Suite for Large-Scale Connectomics

arXiv:2609.21887v1 Announce Type: new Abstract: The gold standard datasets for mapping connectomes are electron microscopy volumes of densely labeled neural tissue at nanometer resolution. Yet reconst

Chronosphere: Space-Time Tessellation of Local Climate Experts

arXiv:2609.21872v1 Announce Type: new Abstract: We introduce Chronosphere, a spatio-temporal neural field that learns representations of climate. A central challenge in geographic representation learn

CityLearn v3: A Configurable Simulation and Evaluation Framework for Realistic Control Studies of Renewable Energy Communities

arXiv:2609.21570v1 Announce Type: cross Abstract: Renewable energy communities (RECs) coordinate buildings, photovoltaic generation, batteries, electric vehicles and flexible loads. Controller studies