Search: “research”

Non-Crossing Deep Quantile Regression for Distributional Survival Prediction

arXiv:2608.16864v1 Announce Type: cross Abstract: In survival analysis the way covariates act on the risk of an event often differs between early and late failure times, yet hazard- and mean-based sum

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Not All Neighbors Matter: Understanding the Impact of Graph Sparsification on GNN Pipelines

DGX agent

arXiv:2603.06952v2 Announce Type: replace Abstract: As graphs scale to billions of nodes and edges, graph Machine Learning workloads are constrained by the cost of multi-hop traversals over exponentia

researcharxiv-cs-lg

18 Aug 2026

OceanDepths: A Global Dataset of Paired Subsurface and Surface Ocean Observations

arXiv:2608.16373v1 Announce Type: cross Abstract: Despite comprising over 70% of its surface, the world's oceans are critically underobserved compared to the land surface or the atmosphere.Understandi

On Stopping Rules and Spatial Adaptation for CART

arXiv:2608.15649v1 Announce Type: cross Abstract: The popular CART algorithm for regression trees combines a greedy splitting rule with a stopping rule, but while the splitting rule has been well stud

On Stopping Times of Power-one Sequential Tests: Tight Lower and Upper Bounds

arXiv:2504.19952v2 Announce Type: replace-cross Abstract: We present two general lower bounds for stopping times of sequential tests between arbitrary composite nulls mathcal P and alternatives mathca

On the Principles Behind Neural Network Optimizers

arXiv:2608.16760v1 Announce Type: new Abstract: Reliable optimization is central to neural network (NN) training, yet Adam, the default optimizer for modern LLMs, rests on a fragile foundation. This t

One Score, Two Decisions: Selective Prediction on the Rare-Disease Tail

arXiv:2608.14683v1 Announce Type: new Abstract: Given a patient's clinical findings, a diagnostic system ranks possible diseases and must decide when to endorse its first prediction or defer it for re

One-shot Robust Federated Learning of Independent Component Analysis

arXiv:2505.20532v2 Announce Type: replace Abstract: This paper studies robust one-shot aggregation for distributed and federated Independent Component Analysis (ICA). In this setting, each client comp

Online Convex Optimization with Dueling Feedback

arXiv:2608.15050v1 Announce Type: new Abstract: We study online convex optimization with dueling (pairwise comparison) feedback, where the learner observes only a binary preference between two queried

Operator-Theoretic Generalization Bounds for Multitask Deep Learning

arXiv:2608.15982v1 Announce Type: new Abstract: We develop operator-theoretic generalization bounds for deep multi-output function classes by representing network layers as Koopman composition operato

Optimal Lower Bounds for Networked Information Aggregation

arXiv:2608.15472v1 Announce Type: cross Abstract: The problem of networked information aggregation, studied in Kearns et al. (2026), involves a group of learners situated on the vertices of a directed

Optimizing Multi-Market Participation of Battery and Electrolyser Systems Based on Field Performance

arXiv:2608.16238v1 Announce Type: new Abstract: The increasing share of renewable energy in power systems creates a need for fast-response and flexible resources to maintain system stability. With the

Orbit-Planner: Towards Latent World Models for On-Orbit Obstacle Avoidance of Satellite Agents

arXiv:2608.16651v1 Announce Type: cross Abstract: Satellite agents for on-orbit navigation tasks need to predict collision risks using limited onboard observations. However, conventional planners ofte

P2E-VQ: ECG-linked representation augmentation for PPG via discrete patch retrieval

arXiv:2608.14656v1 Announce Type: cross Abstract: Photoplethysmography (PPG) is widely used in consumer wearables because of its low cost and ease of acquisition. However, unlike electrocardiography (

Paired Exact-Reset Evaluation of a Prediction-Derived Medium-to-Full World-Model Cascade

arXiv:2608.14650v1 Announce Type: new Abstract: Existing adaptive-inference and world-action-model systems use cheap-stage outputs or predicted futures to allocate additional computation. We study a n

ParaTempo: Efficient Parallel Reasoning via Temporal Confidence

arXiv:2608.16425v1 Announce Type: new Abstract: Parallel reasoning improves the accuracy and robustness of large reasoning models by exploring multiple solution paths, but its computational cost grows

PAS-QFL: Personalized Ansatz Selection for Quantum Federated Learning under Client Data Heterogeneity

arXiv:2608.14995v1 Announce Type: cross Abstract: Quantum federated learning (QFL) lets multiple quantum clients collaboratively train quantum neural networks (QNNs) without sharing private local data

PathFinder: Joint Decompositions of Linked Multimodal Datasets

arXiv:2608.14951v1 Announce Type: new Abstract: Low-rank matrix decompositions can uncover patterns and structure in data and have a number of different applications across many disciplines. Extension

PCA-guided Activation Scaling for Monotonic Bidirectional Control over LLM Sycophancy

arXiv:2608.16650v1 Announce Type: new Abstract: Large language models (LLMs) exhibit sycophancy, a tendency to agree with user beliefs regardless of factual accuracy. This can reinforce misconceptions

researcharxiv-cs-cl

PertMind: Eliciting Emergent Biological Reasoning in LLM via Reinforcement Learning on Cellular Perturbation Data

arXiv:2608.16419v1 Announce Type: cross Abstract: Large language models can describe mechanisms, yet scalable post-training still depends on costly, manually curated biological reasoning traces. Here

Phase-Aware CNN for Real-Time 5G/6G Channel Estimation with Hardware-in-the-loop Validation

arXiv:2608.14676v1 Announce Type: cross Abstract: In 5G/6G wireless systems, accurate and timely channel estimation is critical to ensure reliable communication under complex, fast-changing radio cond

Physics-informed VAE-EVT for Tail Aware Radio Map Prediction

arXiv:2608.15314v1 Announce Type: new Abstract: Ultra-reliable low-latency communication (URLLC) requires precise identification of spatial regions where the signal-to-noise ratio (SNR) falls below an

PixelControl: Fine-Grained Condition Fidelity in Text-to-Image Diffusion

arXiv:2608.15705v1 Announce Type: new Abstract: Controllable text-to-image diffusion models can often follow the global layout of spatial conditions, yet still violate fine-grained structures such as

Population Structure Analysis of an Inbred Population using Quantitative Shape Phenotyping from Stereo Retinal Photographs

arXiv:2608.15471v1 Announce Type: cross Abstract: The population structure of an inbred population of 781 people on Norfolk Island in the Pacific, 318 of which are descendants of the original Mutineer

PoseAdapter: Dual-Stream 2.5D Controllable Image Generation for Complex Multi-Object Scenes

arXiv:2608.15583v1 Announce Type: new Abstract: While Text-to-Image (T2I) diffusion models have achieved remarkable success, precise spatial and orientational control in multi-object scenes remains a

Safety

Position: AI Lock-In Is in Progress, and We Must Be Prepared

arXiv:2608.14565v1 Announce Type: new Abstract: AI safety research has mainly focused on two areas: technical alignment (ensuring AI systems produce human-aligned outputs) and the regulation of genera

safetyarxiv-cs-ai

Position: Medical AI Neglects Real Treatment Outcomes

arXiv:2608.14598v1 Announce Type: new Abstract: Medical AI has rapidly improved its ability to perform diagnostic and prognostic tasks that lead to treatment decisions. But understanding of treatment

Position: Want Better ML Reviews? Stop Asking Nicely and Start Incentivizing with a Credit System

arXiv:2608.14571v1 Announce Type: new Abstract: With soaring submission counts, stricter reciprocal review policies, widespread adoption of platforms like OpenReview, and without the offsetting pressu

Predicting, Evaluating, and Explaining Top Misinformation Spreaders via Archetypal User Behavior

arXiv:2608.16323v1 Announce Type: cross Abstract: The spread of misinformation on social networks poses a significant challenge to online communities and society at large. Not all users contribute equ

Prediction Inference of Time Series with Standard ReLU Deep Neural Networks

arXiv:2608.15362v1 Announce Type: cross Abstract: We propose a methodology based on the standard ReLU Deep Neural Networks (DNN) to make predictions and quantify their uncertainty. Classically, people

Prior Audit-Repair Context Shifts LLM Verifier Thresholds Toward Leniency

arXiv:2608.16003v1 Announce Type: new Abstract: Automated checking pipelines increasingly place one language model as the checker and another (or the same one) as the fixer. We ask whether that wiring

Probability-Preserving Transformer for the Time-Dependent Schrodinger Equation

arXiv:2608.15112v1 Announce Type: new Abstract: Solving the time-dependent Schrodinger equation (TDSE) via traditional numerical methods is computationally intensive. Transformer models offer a compel

Process-Constituted Intelligence: A Shared Criterion for Humans and Machines

arXiv:2608.16213v1 Announce Type: new Abstract: Intelligence is constituted by extit{process} (iterative activity through which output emerges), not in the output itself. Generative AI (GenAI) is trai

Projection-based multifidelity linear regression for data-scarce applications

arXiv:2508.08517v2 Announce Type: replace-cross Abstract: Surrogate modeling for systems with high-dimensional quantities of interest remains challenging, particularly when training data are costly to

ProjFormer: Point Cloud Completion via Geometric-Projective Transformer and Cross-Modal Semantic Constraints

arXiv:2608.15104v1 Announce Type: new Abstract: Point cloud completion is inherently ill-posed due to severe sparsity and ambiguity in partial observations. Existing multi-view methods alleviate this

ProteoKnight: Convolution-based Phage Virion Protein Classification and Uncertainty Analysis

arXiv:2508.07345v2 Announce Type: replace-cross Abstract: extbf{Introduction:} Accurate prediction of Phage Virion Proteins (PVP) is essential for genomic studies due to their crucial role as structur

PureTD: Reinforcement Learning for Backgammon Money Games with No Evaluation-time Search

arXiv:2608.15146v1 Announce Type: new Abstract: We revisit Tesauro's TD-Gammon for backgammon money games in the setting of no evaluation-time search. Both checker play and cube action (use of the dou

Pushing the Limits of High-Resolution Weather Forecasting through Data Scaling

arXiv:2608.14652v1 Announce Type: cross Abstract: The development of 0.1^{irc} global weather forecasting models based on machine learning (ML) is constrained by the limited availability of high-resol

QSMP: finding representative time series subsequences through Quick Shift+Matrix Profile

arXiv:2608.15492v1 Announce Type: new Abstract: Finding representative waveforms in long time series has scientific and practical value in many domains, as it enables summarization and visualization o

Quantifying Depth Sufficiency in Residual Neural Networks: A First-Order Criterion

arXiv:2608.14664v1 Announce Type: new Abstract: How can we determine whether a trained neural network is already deep enough? We study this under a fixed function-preserving residual-growth protocol s

Quantifying the Gap Between Laboratory Battery Test Patterns and Field Duty Profiles

arXiv:2608.16212v1 Announce Type: new Abstract: Laboratory battery tests provide the main empirical basis for battery performance and degradation studies, but their operating patterns do not directly

Quantum Large Language Models via Tensor Network Disentanglers

arXiv:2410.17397v2 Announce Type: replace-cross Abstract: We introduce a framework for seamlessly integrating quantum computing into pretrained large language models (LLMs). The key idea is to constru

Quantum Models with Multi-Stage Training for Compositional Concept Generalization

arXiv:2608.15601v1 Announce Type: new Abstract: Compositional Concept Generalization (CoCoGen), the ability to systematically recombine learned primitives in novel contexts, is a key challenge for mul

QUMem: Personalized Memory for Query-Conditioned User-State Inference in LLM Agents

arXiv:2608.16168v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly use external memory systems to support personalization by drawing on long and evolving interaction hist

RAIN-FIT: Learning of Fitting Surfaces and Noise Distribution from Large Data Sets

arXiv:2604.03491v2 Announce Type: replace-cross Abstract: This paper proposes a method for estimating a surface that contains a given set of points from noisy measurements. More precisely, by assuming

Random Quadratic Form on a Sphere: Synchronization by Common Noise

arXiv:2603.06187v2 Announce Type: replace-cross Abstract: We introduce the Random Quadratic Form (RQF): a stochastic differential equation which formally corresponds to the gradient flow of a random q

Randomly initialized autoencoders: fixed points and edge-of-chaos

arXiv:2608.14638v1 Announce Type: new Abstract: In this paper we study autoencoders, a special class of deep neural nets (DNNs) whose performance can be characterized via their fixed points. This pers

Real-Time State-of-Health Estimation and Online Degradation Prognosis from Partial Battery Discharge Using Physics-Informed Neural Networks

arXiv:2608.14764v1 Announce Type: new Abstract: With the increasing integration of renewable energy sources, energy storage systems have become essential, making the accurate estimation of their State