Search: “research”

Delayed Assignments in Online Non-Centroid Clustering with Stochastic Arrivals

arXiv:2601.16091v2 Announce Type: replace-cross Abstract: Clustering is a fundamental problem, aiming to partition a set of elements, like agents or data points, into clusters such that elements in th

Research

Design, Control, and Motion Strategy for DELTA: Transformable Multilink Multirotor for Air-Ground Hybrid Locomotion and Manipulation

DGX agent

arXiv:2403.06636v2 Announce Type: replace Abstract: In recent years, multimodal locomotion capabilities have enabled robots to maneuver in both terrestrial and aerial domains. However, most of these r

researcharxiv-cs-ro

26 May 2026

Detecting Metastable Basins in High Dimensions via Marginal Trajectory Distribution Discrimination

arXiv:2605.24136v1 Announce Type: cross Abstract: We study the problem of identifying dynamically distinct basins of attraction in high dimensional time-homogeneous Markov processes using only traject

Detecting Unfaithful Chain-of-Thought via Circuit-Guided Internal-External Discrepancy

arXiv:2605.25603v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning improves the problem-solving ability of large language models (LLMs), but generated reasoning traces may not faithfully

Developer productivity is hard to manage.

researchfrancois-chollet--x

Developer productivity is hard to manage. Uber’s COO has said that it’s getting “harder to justify” its AI costs because there was no way to show a link between AI spend and any meaningful increase in

Does Continued Pretraining on a Learner Corpus Improve Automated Essay Scoring on English Proficiency Tests? Evidence from EFCAMDAT

arXiv:2605.25924v1 Announce Type: new Abstract: Recent automated essay scoring (AES) studies increasingly use pretrained transformer models, but these models are usually pretrained on general-domain E

Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Models

arXiv:2605.25681v1 Announce Type: cross Abstract: Designing a single molecule that modulates two targets is a promising strategy for polypharmacology, but it remains substantially harder than standard

DriftingMol: Decoder-Coupled Drift for One-Pass Property-Conditional Molecular Generation

arXiv:2605.24841v1 Announce Type: new Abstract: Property-conditional molecular generation should produce valid, diverse molecules while responding to continuous target values at low sampling cost. We

DRIVE: Modeling Skills at the Reasoning and Interaction Levels for Web Agents under Continual Learning

arXiv:2605.23939v1 Announce Type: new Abstract: Web agents require both high-level reasoning (for task decomposition) and low-level interactions (for page elements manipulation) to conduct different t

DUEL: Adversarial Self-Play for Multimodal Reasoning

arXiv:2605.24794v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as an effective paradigm for improving the reasoning capability of vision-language models (VLMs). However, RL-

Efficient and Scalable Neural Symbolic Search for Knowledge Graph Complex Query Answering

arXiv:2505.08155v4 Announce Type: replace Abstract: Complex Query Answering (CQA) is a crucial reasoning task over Knowledge Graphs (KGs), which aims to answer first-order logical queries from incompl

Efficient Imputation for Patch-based Missing Single-cell Data via Cluster-regularized Optimal Transport

arXiv:2601.14653v2 Announce Type: replace Abstract: Missing data in single-cell sequencing datasets poses significant challenges for extracting meaningful biological insights. However, existing imputa

End-to-End Intracortical Speech Decoding from Neural Activity

arXiv:2605.24313v1 Announce Type: new Abstract: Current high-performing intracortical speech neuroprostheses achieve low word error rates but typically rely on external language models during inferenc

Estimating Mixture Distributions via Stochastic Mirror Descent

arXiv:2605.24929v1 Announce Type: cross Abstract: We revisit the classical problem of estimating an unknown distribution from its samples by fitting a mixture model that minimizes cross-entropy loss.

EVA: Accelerating LLM Decoding via an Efficient Vector Quantization Architecture

arXiv:2605.24144v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved impressive performance across diverse domains but remain inefficient during the autoregressive decoding pha

Evaluating passing decision-making in professional football: An enhanced MPNN approach to Receiver Selection

arXiv:2605.25696v1 Announce Type: new Abstract: The process of decision-making in football is characterized by a complex interplay between spatial positioning, opponent pressure, and player intent. Th

Everything at Every Scale: Scale-Invariant Diffusion with Continuous Super-Resolution

arXiv:2605.26032v1 Announce Type: cross Abstract: Creating images from noise is image generation; reconstructing fine details from coarse inputs is super-resolution. Despite their practical difference

Agents

EvoSci: A Bio-Inspired Multi-Agent Framework for the Evolution of Scientific Discovery

arXiv:2605.24018v1 Announce Type: new Abstract: Large language models (LLMs), have shown strong potential in scientific discovery, yet existing methods still face substantial challenges in the design

agentsarxiv-cs-ai

EXOTIC: An Exact, Optimistic, Tree-Based Algorithm for Min-Max Optimization

arXiv:2508.12479v2 Announce Type: replace-cross Abstract: Min-max optimization arises in many domains such as game theory, adversarial machine learning, etc. For these problems, gradient-based methods

Explainable Attention-Guided Stacked Graph Neural Networks for Malware Detection

arXiv:2508.09801v3 Announce Type: replace-cross Abstract: Malware detection in modern computing environments demands models that are not only accurate but also interpretable and robust to evasive tech

Explainable Retinal Imaging for Prediction of Multi-Organ Dysfunction in Type 2 Diabetes

arXiv:2605.24912v1 Announce Type: cross Abstract: Background: Type 2 diabetes mellitus (T2DM) is increasingly recognised as a systemic disease characterised by coordinated dysfunction across metabolic

Explaining Too Much? Understanding How Large Language Model Reasoning Traces Influence Performance and Metacognition

arXiv:2605.25856v1 Announce Type: cross Abstract: Large Language Model interfaces are increasingly verbose, exposing intermediate reasoning traces alongside final answers. Traces are framed as transpa

Extreme-value forest fire prediction A study of the Loss Function in an Ordinality Scheme

arXiv:2601.03327v3 Announce Type: replace-cross Abstract: Wildfires are highly imbalanced natural hazards in both space and severity, making the prediction of extreme events particularly challenging.

Feature Lottery? A Bifurcation Theory of Concept Emergence

arXiv:2605.24057v1 Announce Type: cross Abstract: Neural networks acquire structured representations at specific moments during training, yet identifying these transitions typically relies on retrospe

Feature Resemblance: Towards a Theoretical Understanding of Analogical Reasoning in Transformers

arXiv:2603.05143v3 Announce Type: replace Abstract: Understanding reasoning in large language models is complicated by evaluations that conflate multiple reasoning types. We isolate analogical reasoni

Federated Sketching LoRA: A Flexible Framework for Heterogeneous Collaborative Fine-Tuning of LLMs

arXiv:2501.19389v4 Announce Type: replace Abstract: Fine-tuning large language models (LLMs) on resource-constrained clients remains a challenging problem. Recent works have fused low-rank adaptation

Fine-Tuning Masked Diffusion for Provable Self-Correction

arXiv:2510.01384v4 Announce Type: replace Abstract: A natural desideratum for generative models is self-correction--detecting and revising low-quality tokens at inference. While Masked Diffusion Model

Fine-Tuning Over Architectural Complexity: Broad-Coverage PII Detection on PIIBench with DeBERTa

arXiv:2605.25816v1 Announce Type: cross Abstract: Personally identifiable information (PII) detection systems are frequently trained within narrow source or domain boundaries, limiting coverage when d

Forecasting Scientific Progress with Artificial Intelligence https://arxiv.org/abs/2605.22681 Turns out AI is just as bad at forecasting bio…

Forecasting Scientific Progress with Artificial Intelligence https://arxiv.org/abs/2605.22681 Turns out AI is just as bad at forecasting biology and physics breakthroughs as we are. To be fair, most b

researchdavid-ha--x

Forgettable Federated Linear Learning with Certified Data Unlearning

arXiv:2306.02216v3 Announce Type: replace Abstract: Federated Learning (FL) enables collaborative model training across distributed clients while preserving user privacy. Recently, Federated Unlearnin

Forgetting in Language Models: Capacity, Optimization, and Self-Generated Replay

arXiv:2605.26097v1 Announce Type: new Abstract: Models trained on a new task typically degrade on prior tasks, a phenomenon known as forgetting. Traditionally, mitigating forgetting has required repla

Forgotten Words: Benchmarking NeoBERT for Dementia Detection in Low-Resource Conversational Filipino and English Speech

arXiv:2605.26007v1 Announce Type: new Abstract: Dementia detection from spontaneous speech offers a scalable approach to cognitive screening, yet NLP systems remain predominantly English-centric. This

FragmentNet: Adaptive Graph Fragmentation for Graph-to-Sequence Molecular Representation Learning

arXiv:2502.01184v2 Announce Type: replace-cross Abstract: Molecular representation learning methods typically tokenize molecules as individual atoms or use rigid, rule-based fragment decompositions, l

Fredholm Neural Networks for inverse problems in elliptic PDEs

arXiv:2507.06038v4 Announce Type: replace-cross Abstract: Building on our previous work on Fredholm Neural Networks (Fredholm NNs/ FNNs) for solving integral equations, we extend the framework to inve

Frequency Matters: Fast Model-Agnostic Data Curation for Pruning and Quantization

arXiv:2603.16105v3 Announce Type: replace-cross Abstract: Post-training model compression is essential for enhancing the portability of Large Language Models (LLMs) while preserving their performance.

From Accounting to Coordination: A Virtual Water-Aware Electricity-Computation-Water Nexus Framework for Data Center Dispatch

arXiv:2605.25854v1 Announce Type: new Abstract: The expansion of data centers (DCs) drives a sustained increase in electricity demand and associated water withdrawals at generation sites. These withdr

From Latent Space to Training Data: Explainable Specialization in Minimal MLPs

arXiv:2605.25939v1 Announce Type: cross Abstract: We here study whether training biases can make hidden neurons specialize in minimal one-hidden-layer MLPs, and whether such specialization improves pr

Model Releases

FrontierOR: Benchmarking LLMs' Capacity for Efficient Algorithm Design in Large-Scale Optimization

model-releasesarxiv-cs-ai

arXiv:2605.25246v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for optimization modeling and solver-code generation, yet practical operations research and optimizat

Full-Spectrum Graph Neural Networks: Expressive and Scalable

arXiv:2605.05759v2 Announce Type: replace Abstract: It is well established that spectral graph neural networks (GNNs) can universally approximate node signals; however, their expressive power remains

Fundamental Limitation in Explaining AI

arXiv:2605.24727v1 Announce Type: new Abstract: While large-scale models such as LLMs and diffusion models have achieved practical success, public institutions have emphasized the importance of explai

Fundamental Limits for Sensor-Based Control via the Gibbs Variational Principle

arXiv:2603.18454v2 Announce Type: replace-cross Abstract: Fundamental limits on the performance of feedback controllers are essential for benchmarking algorithms, guiding sensor selection, and certify

researcharxiv-cs-ro

FuXi-Nowcast: Environment-conditioned deep learning for severe convection nowcasting

arXiv:2512.08974v2 Announce Type: replace-cross Abstract: Severe convection produces localized hazards that often require warnings before radar echoes fully reveal storm development. Convective initia

Fuzzy, Neutrosophic, and Uncertain Graph Theory: Properties and Applications

arXiv:2605.23936v1 Announce Type: new Abstract: This book presents a comprehensive and systematic survey of graph theory under uncertainty, with particular emphasis on the unifying role of the uncerta

Generalized Evidential Deep Learning: From a Bayesian Perspective

arXiv:2605.25599v1 Announce Type: new Abstract: Evidential Deep Learning (EDL) has emerged as an efficient, sampling-free strategy for uncertainty estimation. A series of EDL variants have been propos

Generation Enhances Understanding in Unified Multimodal Models via Multi-Representation Generation

arXiv:2601.21406v3 Announce Type: replace-cross Abstract: Unified Multimodal Models (UMMs) integrate both visual understanding and generation within a single framework. Their ultimate aspiration is to

Generative AI impacts on intra-urban inequality and skill premium in Beijing

arXiv:2605.25505v1 Announce Type: cross Abstract: Generative artificial intelligence (GenAI) is the first automation wave to reach high-cognitive tasks at scale, yet its effects on intra-urban inequal

Generative modeling of granular flow on inclined planes using conditional flow matching

arXiv:2604.04453v2 Announce Type: replace-cross Abstract: Granular flows govern many natural and industrial processes, yet their interior kinematics and mechanics remain largely unobservable, as exper

Generative Neural Operators through Diffusion Last Layer

arXiv:2602.04139v2 Announce Type: replace Abstract: Neural operators provide a powerful framework for learning discretization invariant mappings between function spaces, but standard deterministic mod