applications

Conformal Prediction for Time Series with Deep Sequence Models

arXiv:2610.02357v1 Announce Type: cross Abstract: Recent advances in deep learning for time series prediction have amplified the need for reliable uncertainty quantification. Conformal prediction has

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Diffusion-Based Synthetic Data Pretraining for Enhancing Activity Recognition

DGX agent

arXiv:2610.02292v1 Announce Type: cross Abstract: Human activity recognition (HAR) is increasingly important for healthcare, well-being, and daily monitoring ap- plications, for which detecting alimen

applicationsarxiv-cs-ai

5 Oct 2026

Dual-Context Analog Retrieval for Time Series Forecasting

arXiv:2610.03491v1 Announce Type: new Abstract: Most long-term time-series forecasting models map the look-back window directly to the full horizon in a single pass. While efficient, this design does

High-Dimensional Asymptotics and Dataset Selection for Private Transfer Learning

arXiv:2610.02578v1 Announce Type: cross Abstract: To commit to buying external data or participate in collaborative learning, one must decide whether the additional data will improve prediction enough

I've been complaining about some OpenAI choices tonight, so, on the plus side, I will say there is still no equivalent to GPT-6 Pro (just as…

applicationsethan-mollick--x

I've been complaining about some OpenAI choices tonight, so, on the plus side, I will say there is still no equivalent to GPT-6 Pro (just as there wasn't with previous Pro models). It both does really

Jumping the Line: Exploiting Length Predictions in LLM Scheduling

arXiv:2610.03430v1 Announce Type: new Abstract: Efficient request scheduling is increasingly important for reducing completion time in large language model (LLM) serving. Size-based policies such as S

Learning Query Encoders Can Be Hard Even When Vector Retrieval Is Geometrically Easy

arXiv:2610.02749v1 Announce Type: cross Abstract: Efficient vector retrieval requires both a corpus geometry that supports retrieving the right documents through vector similarity, and a query encoder

Learning the Latent Structure: A Feature-Centric Approach to Graph Data Augmentation

arXiv:2610.02517v1 Announce Type: new Abstract: Graph-structured data plays a pivotal role in modeling complex relationships. However, real-world graphs are often incomplete due to data collection and

Learning to Assess Heartbeat Observability for mmWave Heart-Rate Sensing

arXiv:2610.03570v1 Announce Type: new Abstract: Contactless heart-rate sensing with millimeter-wave (mmWave) radar requires assessing whether individual measurements support reliable estimation. We st

Light Entropic Optimal Transport on Riemannian Manifolds

arXiv:2610.03085v1 Announce Type: new Abstract: Entropic Optimal Transport (EOT) has become a practical framework for learning stochastic couplings between complex distributions, with applications in

LOCUS: Landmark-Oriented Container Discrimination Using Spatial Graphs

arXiv:2610.02803v1 Announce Type: new Abstract: As robots are increasingly deployed in unstructured, real-world environments, the ability to reason about complex spatial and semantic relationships amo

Mapping and Advancing the Scalability-Accuracy Frontier of Nonlinear Causal Discovery

arXiv:2610.03258v1 Announce Type: cross Abstract: Scalable nonlinear causal discovery requires methods that combine flexible mechanism estimators with efficient search over large graph spaces. Several

MoSE3: Learning World-Space SE(3) at Every Pixel

arXiv:2610.03716v1 Announce Type: new Abstract: Dense 3D point tracking has been a prominent paradigm for modeling motion in dynamic scenes, but a point track is just a 3-DoF translation curve per pix

Most-Recent Anchoring with Recurrent Ordering for Time Series Forecasting

arXiv:2610.03494v1 Announce Type: new Abstract: Long-term forecasting models commonly process all patches in a look-back window using the same fixed stack. Older contextual patches and recent evidence

Predictor-Guided Latent Space Codon Optimization for Maximizing Protein Expression

arXiv:2610.03098v1 Announce Type: new Abstract: Codon optimization, the process of selecting synonymous codons to improve mRNA translation efficiency and protein expression, is central to therapeutic

Proprioceptive Sketches as Long-Horizon Intent for Generative Action Policies

arXiv:2610.02759v1 Announce Type: new Abstract: Generative robot policies predict short action chunks but lack explicit long-horizon intent. Recent methods expose longer-horizon structure through lang

RATE: Risk-Aware Tactile Encoding for Contact-rich Robotic Manipulation

arXiv:2610.03538v1 Announce Type: new Abstract: Tactile sensing is particularly valuable for contact-rich robotic manipulation. Recent work has made substantial progress in tactile representation lear

Reasoning with Evidence, Not Merely Rationales: Verifiable Preference Proofs for LLM-Based Recommendation

arXiv:2610.02968v1 Announce Type: new Abstract: Large language models (LLMs) can infer user preferences from interaction histories and reviews, yet the rationales they generate may not reflect the inf

ReSCUE: Re-translation with Sentence Commitment for Unsegmented Long-Form Simultaneous Sign Language Translation

arXiv:2610.03022v1 Announce Type: cross Abstract: Simultaneous Sign Language Translation (SLT) is critical for real-time communication, yet existing methods remain largely confined to sentence-level,

applicationsarxiv-cs-cl

RIFAR: Reliability and Forgetting-Aware Replay for Continual Robot Learning

arXiv:2610.03079v1 Announce Type: new Abstract: Genuine embodied agency requires robots to turn continuous real-world experience into lasting, transferable skills. This demands continual learning that

ROVE: Unlocking Human Interventions for Humanoid Manipulation via Reinforcement Learning

arXiv:2606.17011v2 Announce Type: replace-cross Abstract: Human interventions provide crucial corrective signals for post-training Vision-Language-Action (VLA) models. However, enabling seamless human

SCION: Scene Composition with Instanced Neural Primitives

arXiv:2610.02322v1 Announce Type: new Abstract: Real-world scenes are compositional: bricks, blades of grass, pebbles, and tree leaves recur across human-built and natural environments. Existing neura

Seer: Maximum Likelihood Regression for Learning-Speed Curves

arXiv:2610.02610v1 Announce Type: new Abstract: The research presented here focuses on modeling machine-learning performance. The thesis introduces Seer, a system that generates empirical observations

Social bot detection in the age of ChatGPT: Challenges and opportunities

arXiv:2610.02386v1 Announce Type: cross Abstract: We present a comprehensive overview of the challenges and opportunities in social bot detection in the context of the rise of sophisticated AI-based c

applicationsarxiv-cs-cl

Sona: one transformer replaced our 15+ candidate generators, pre-ranker and ranker in an A/B test [R]

applicationsr-machinelearning

Our production recommender at Yandex Music has 15+ candidate generators feeding pre-ranking and ranking models with hundreds of features. LLMs showed that one end-to-end model can take over work that

strata-swift-iq3_xxs randomly interjecting completely unrelated information in thoughts

I have been using Qwen3.8-27b-iq4xs variants for the past few weeks, tweaking parameters and running random tasks, but I dove into using https://github.com/Niko1221/Strata today and it has given me 2~

applicationsr-localllama

The Price of Greenwashing: Algorithmic Verification and Market Discipline using Conformal Machine Learning

arXiv:2610.02225v1 Announce Type: new Abstract: While corporate sustainability mandates are expanding, the systemic reliance on self-reported emissions data exposes financial markets to pervasive gree

Time Series Forecasting Benchmarks Need Scenario-Grounded Stress Testing

arXiv:2610.02608v1 Announce Type: new Abstract: Time series forecasting (TSF) increasingly drives decisions in transportation, energy, finance, healthcare, and infrastructure, yet current evaluation r

Uncertainty Quantification for Flow-Based Generalist Robot Policies

arXiv:2606.18043v2 Announce Type: replace-cross Abstract: Generalist robot policies, such as vision-language-action models (VLAs) and world-action models (WAMs), combine powerful pretrained backbones

A spiralling legal crisis threatens to engulf OpenAI after its AI agents hacked dozens of companies and governments worldwide, with the pros…

applicationsgary-marcus--x

A spiralling legal crisis threatens to engulf OpenAI after its AI agents hacked dozens of companies and governments worldwide, with the prospect of a barrage of lawsuits marking the latest test of Sam

4 Oct 2026

Here are some pictures of a robot costume wearing high-specularity edge-case mirror suit, a dataset (425 RAW/JPEGs) for benchmarking CV & depth-estimation algorithms against extreme mirror reflections [D]

applicationsr-machinelearning

Purpose-built to stress-test computer vision models, depth cameras, and spatial AI against severe specular glare and geometric reflections. This 425-asset production archive features a custom faceted

4 Oct 2026

Toshiba plans to double HDD production capacity for AI data centers within FY2027 from its 2025 level, targeting a 30% share by storage capacity, up from ~10% (Keigo Yoshida/Nikkei Asia)

Keigo Yoshida / Nikkei Asia: Toshiba plans to double HDD production capacity for AI data centers within FY2027 from its 2025 level, targeting a 30% share by storage capacity, up from ~10% — MANILA — J

applicationstechmeme

4 Oct 2026

A Meta-Prompt for YuE2

applicationsr-stablediffusion

I've come up with a meta-prompt for generating YuE2 prompts that seems to work pretty well. Copy-paste into an LLM (it should have internet searching capabilities, I mostly just use ChatGPT). Just to

3 Oct 2026

3DROID: A Renderable 3D Gaussian Dataset with Measured Per-Scene Reliability

arXiv:2610.01744v1 Announce Type: new Abstract: Robot manipulation models primarily reason from 2D observations while acting in the 3D physical world. To bridge this gap, recent work has augmented rob

4Director: Controlling Video World Models with Rigid 3D Geometry

arXiv:2610.02160v1 Announce Type: new Abstract: Precise control over camera and object motion is essential for professional video production. Existing methods control objects only coarsely, through im

A Hybrid Approach to Malware Detection: Integrating Few-Shot Model-Agnostic Meta-Learning with Autoencoders

arXiv:2610.01949v1 Announce Type: cross Abstract: Ransomware has emerged as a major cybersecurity threat, with incidents increasing in frequency and impact across critical sectors. These attacks are t

A Structured State Space Sequence Model for Multi-Class Classification of Malware

arXiv:2610.01893v1 Announce Type: cross Abstract: By 2030, Internet of Things (IoT) devices are projected to reach 40 billion, with fast-paced technological advancements in fields such as industry, he

BLT*: Informed Belief Localization Trees for Uncertainty-Aware Planning on Digital Twins

arXiv:2610.01972v1 Announce Type: new Abstract: We present Informed Belief Localization Trees* (Informed BLT*), a sampling-based belief space planning (BSP) algorithm that scales to large outdoor digi

Causal-Aware Tabular GANs with Reinforcement Learning

arXiv:2510.24046v2 Announce Type: replace-cross Abstract: Existing tabular data generation methods primarily focus on matching statistical distributions between real and synthetic data, often overlook

ChunkVLA-AM: Parallel Action Chunking for Vision-Language-Action Robot Control in Additive Manufacturing

arXiv:2610.01856v1 Announce Type: new Abstract: Vision-language-action (VLA) models unify visual perception, language understanding, and action generation, offering new opportunities for automation in

Continual Learning for 6-DoF Grasp Synthesis via Experience and Demonstrations

arXiv:2610.01301v1 Announce Type: cross Abstract: Most current grasp synthesis systems are trained offline and remain fixed during deployment. While this works well when deployment conditions resemble

DecomVoxel: Harnessing 3D-Native Priors with Guided In-situ Denoising Optimization for Decompositional Scene Reconstruction

arXiv:2610.01914v1 Announce Type: new Abstract: Decompositional scene reconstruction aims to reconstruct high-quality objects and background, yet existing methods still struggle with the level of qual

Dyna3: VLM-Guided Training-Free 4D Reconstruction via Depth Foundation Models

arXiv:2610.01286v1 Announce Type: new Abstract: Recent depth foundation models like Depth Anything 3 (DA3) achieve remarkable multi-view depth estimation but assume static 3D scenes, limiting their ap

Energy Time-Series Imputation with Differentially Private Diffusion Models via Clipping-Aware Objective Conditioning

arXiv:2610.00209v1 Announce Type: new Abstract: Reliable recovery of missing measurements is important for monitoring and analysis in energy time-series systems, where fine-grained measurements may co

Enterprise storage becomes AI memory as privately run models close in on the frontier

As open-weight models close in on the performance of proprietary frontier systems, enterprises are gaining a credible way to run generative AI on hardware they own. That shift puts the data already si

applicationssiliconangle

Evaluating LLM-Generated Preference Distributions

arXiv:2610.01000v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used as probabilistic generators for simulation, synthetic data generation, and decision support in settin

EvenSplat: Coupled 2D-3D Decomposition for Gaussian Splatting under Exposure and Illumination Variation

arXiv:2610.01876v1 Announce Type: new Abstract: A surface photographed under even light presents nearly the same appearance from every angle; the same surface under uneven light does not. Exposure cha

Exponential quantum advantage in processing massive classical data

arXiv:2604.07639v2 Announce Type: replace-cross Abstract: Broadly applicable quantum advantage, particularly in classical data processing and machine learning, has been a fundamental open problem. In