Search: “research”

Consequentialist Objectives and Catastrophe

arXiv:2603.15017v3 Announce Type: replace Abstract: Because human preferences are too complex to codify, AIs operate with misspecified objectives. Optimizing such objectives often produces undesirable

CRAFT: Clustered Regression for Adaptive Filtering of Training data

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DGX agent

arXiv:2604.22693v1 Announce Type: cross Abstract: Selecting a small, high-quality subset from a large corpus for fine-tuning is increasingly important as corpora grow to tens of millions of datapoints

researcharxiv-cs-ai

27 Apr 2026

Cross-Domain Offshore Wind Power Forecasting: Transfer Learning Through Meteorological Clusters

arXiv:2601.19674v2 Announce Type: replace-cross Abstract: Ambitious decarbonisation targets are rapidly increasing the commission of new offshore wind farms. For these newly commissioned plants to run

CrystalX: High-accuracy Crystal Structure Analysis Using Deep Learning

arXiv:2410.13713v2 Announce Type: replace Abstract: Atomic structure analysis of crystalline materials is a paramount endeavor in both chemical and material sciences. This sophisticated technique nece

da4ml: Distributed Arithmetic for Real-time Neural Networks on FPGAs

arXiv:2507.04535v2 Announce Type: replace-cross Abstract: Neural networks with a latency requirement on the order of microseconds, like the ones used at the CERN Large Hadron Collider, are typically d

Data-Driven Analysis of AI in Medical Device Software in China: Trends of Deep Learning and Traditional AI Based on Regulatory Data

arXiv:2411.07378v3 Announce Type: replace Abstract: Artificial intelligence (AI) in medical device software (MDSW) represents a transformative clinical technology, attracting increasing attention with

Decomposed Attention Fusion in MLLMs for Training-Free Video Reasoning Segmentation

arXiv:2510.19592v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) demonstrate strong video understanding by attending to visual tokens relevant to textual queries. To direct

Detecting Cognitive Signatures in Typing Behavior for Non-Intrusive Authorship Verification

arXiv:2603.00177v2 Announce Type: replace-cross Abstract: The proliferation of AI-generated text has intensified the need for reliable authorship verification, yet current output-based methods are inc

Detecting Concept Drift in Evolving Malware Families Using Rule-Based Classifier Representations

arXiv:2604.22629v1 Announce Type: cross Abstract: This work proposes a structural approach to concept drift detection in malware classification using decision tree rulesets. Classifiers are trained ac

Dissociating Decodability and Causal Use in Bracket-Sequence Transformers

arXiv:2604.22128v1 Announce Type: new Abstract: When trained on tasks requiring an understanding of hierarchical structure, transformers have been found to represent this hierarchy in distinct ways: i

DocPrune:Efficient Document Question Answering via Background, Question, and Comprehension-aware Token Pruning

arXiv:2604.22281v1 Announce Type: new Abstract: Recent advances in vision-language models have demonstrated remarkable performance across diverse multi-modal tasks, including document question answeri

Dynamic Coupling and Indirect Control of Jointed Robots Rolling Atop A Moving Platform

arXiv:2604.22104v1 Announce Type: new Abstract: An asymmetric two-link robot supported atop a flat platform by wheels that roll and pivot freely, but do not slip laterally, will develop forward moment

researcharxiv-cs-ro

Edit-aware RAW Reconstruction

arXiv:2512.05859v2 Announce Type: replace Abstract: Users frequently edit camera images post-capture to achieve their preferred photofinishing style. While editing in the RAW domain provides greater a

Eidolon: A Post-Quantum Signature Scheme Based on k-Colorability in the Age of Graph Neural Networks

arXiv:2602.02689v2 Announce Type: replace-cross Abstract: We propose Eidolon, a post-quantum signature scheme grounded on the NP-complete k-colorability problem. Our construction generalizes the Goldr

Equivariant Asynchronous Diffusion: An Adaptive Denoising Schedule for Accelerated Molecular Conformation Generation

arXiv:2603.10093v2 Announce Type: replace-cross Abstract: Recent 3D molecular generation methods primarily use asynchronous auto-regressive or synchronous diffusion models. While auto-regressive model

Agents

Evaluation of image simulation open source solutions for simulation of synthetic images in lunar environment

arXiv:2604.22296v1 Announce Type: new Abstract: Synthetic image generation is one of the crucial input for planetary missions. It enables researchers and engineers to visualize planned planetary missi

agentsarxiv-cs-cv

EvFlow-GS: Event Enhanced Motion Deblurring with Optical Flow for 3D Gaussian Splatting

arXiv:2604.22183v1 Announce Type: new Abstract: Achieving sharp 3D reconstruction from motion-blurred images alone becomes challenging, motivating recent methods to incorporate event cameras, benefiti

Expander Hierarchies for Normalized Cuts on Graphs

arXiv:2406.14111v2 Announce Type: replace-cross Abstract: Expander decompositions of graphs have significantly advanced the understanding of many classical graph problems and led to numerous fundament

Explanation of Dynamic Physical Field Predictions using WassersteinGrad: Application to Autoregressive Weather Forecasting

arXiv:2604.22580v1 Announce Type: cross Abstract: As the demand to integrate Artificial Intelligence into high-stakes environments continues to grow, explaining the reasoning behind neural-network pre

Exploiting Low-Rank Structure in Max-K-Cut Problems

arXiv:2602.20376v2 Announce Type: replace-cross Abstract: We approach the Max-3-Cut problem through the lens of maximizing complex-valued quadratic forms and demonstrate that low-rank structure in the

Fast, close, non-singular and property-preserving approximations of entropic measures

arXiv:2505.14234v2 Announce Type: replace-cross Abstract: Entropic measures like Shannon entropy (SE), its quantum mechanical analogue von Neumann entropy, and Kullback-Leibler divergence (KL) are key

Federated Nonlinear System Identification

arXiv:2508.15025v5 Announce Type: replace Abstract: We consider federated learning of linearly-parameterized nonlinear systems. We establish theoretical guarantees on the effectiveness of federated no

FedSPDnet: Geometry-Aware Federated Deep Learning with SPDnet

arXiv:2604.22494v1 Announce Type: cross Abstract: We introduce two federated learning frameworks for the classical SPDnet model operating on symmetric positive definite (SPD) matrices with Stiefel-con

FeudalNav: A Simple Framework for Visual Navigation

arXiv:2602.06974v2 Announce Type: replace-cross Abstract: Visual navigation for robotics is inspired by the human ability to navigate environments using visual cues and memory, eliminating the need fo

FixV2W: Correcting Invalid CVE-CWE Mappings with Knowledge Graph Embeddings

arXiv:2604.22176v1 Announce Type: cross Abstract: Accurate mapping between Common Vulnerabilities and Exposures (CVE) and Common Weakness Enumeration (CWE) entries is critical for effective vulnerabil

Focus Session: Hardware and Software Techniques for Accelerating Multimodal Foundation Models

arXiv:2604.21952v1 Announce Type: cross Abstract: This work presents a multi-layered methodology for efficiently accelerating multimodal foundation models (MFMs). It combines hardware and software co-

Forecasting Solar Energy Using a Single Image

arXiv:2604.21982v1 Announce Type: new Abstract: Solar panels are increasingly deployed in cities on rooftops, walls, and urban infrastructure. Although the panel costs have fallen in recent years, the

Foundation models for discovering robust biomarkers of neurological disorders from dynamic functional connectivity

arXiv:2604.22018v1 Announce Type: cross Abstract: Several brain foundation models (FM) have recently been proposed to predict brain disorders by modelling dynamic functional connectivity (FC). While t

From graphemic dependence to lexical structure: a Markovian perspective on Dante's Commedia

arXiv:2604.22626v1 Announce Type: new Abstract: This study investigates the structural organisation of Dante's Divina Commedia through a symbolic representation based on vowel-consonant (V/C) encoding

From Words to Amino Acids: Does the Curse of Depth Persist?

arXiv:2602.21750v2 Announce Type: replace Abstract: Protein language models (PLMs) have become widely adopted as general-purpose models, demonstrating strong performance in protein engineering and de

Generative Modeling of Neurodegenerative Brain Anatomy with 4D Longitudinal Diffusion Model

arXiv:2604.22700v1 Announce Type: new Abstract: Understanding and predicting the progression of neurodegenerative diseases remains a major challenge in medical AI, with significant implications for ea

H-Sets: Hessian-Guided Discovery of Set-Level Feature Interactions in Image Classifiers

arXiv:2604.22045v1 Announce Type: cross Abstract: Feature attribution methods explain the predictions of deep neural networks by assigning importance scores to individual input features. However, most

HFS-TriNet: A Three-Branch Collaborative Feature Learning Network for Prostate Cancer Classification from TRUS Videos

arXiv:2604.22388v1 Announce Type: new Abstract: Transrectal ultrasound (TRUS) imaging is a cost-effective and non-invasive modality widely used in the diagnosis of prostate cancer. The computer-aided

Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair

arXiv:2604.22407v1 Announce Type: cross Abstract: Many continual-learning methods modify gradients upstream (e.g., projection, penalty rescaling, replay mixing) while treating Adam as a neutral backen

How attention simplifies mental representations for planning

arXiv:2506.09520v2 Announce Type: replace-cross Abstract: Human planning is efficient--it frugally deploys limited cognitive resources to accomplish difficult tasks--and flexible--adapting to novel pr

How Hard is it to Decide if a Fact is Relevant to a Query?

arXiv:2604.22422v1 Announce Type: cross Abstract: We consider the following fundamental problem: given a database D, Boolean conjunctive query (CQ) q, and fact f in D, decide whether f is relevant to

Identifying the Periodicity of Information in Natural Language

arXiv:2510.27241v2 Announce Type: replace Abstract: Recent theoretical advancement of information density in natural language has brought the following question on desk: To what degree does natural la

Initial results of the Digital Consciousness Model

arXiv:2601.17060v2 Announce Type: replace-cross Abstract: Artificially intelligent systems have become remarkably sophisticated. They hold conversations, write essays, and seem to understand context i

Interpretable Deep Learning for Stock Returns: A Consensus-Bottleneck Asset Pricing Model

arXiv:2512.16251v5 Announce Type: replace-cross Abstract: We introduce the Consensus-Bottleneck Asset Pricing Model (CB-APM), which embeds aggregate analyst consensus as a structural bottleneck, treat

Introducing Background Temperature to Characterise Hidden Randomness in Large Language Models

arXiv:2604.22411v1 Announce Type: new Abstract: Even when decoding with temperature T=0, large language models (LLMs) can produce divergent outputs for identical inputs. Recent work by Thinking Machin

Iterative Model-Learning Scheme via Gaussian Processes for Nonlinear Model Predictive Control of (Semi-)Batch Processes

arXiv:2604.22672v1 Announce Type: new Abstract: Batch processes are inherently transient and typically nonlinear, motivating nonlinear model predictive control (NMPC). However, adopting NMPC is hinder

Joint Embedding Variational Bayes

arXiv:2602.05639v4 Announce Type: replace Abstract: We introduce Variational Joint Embedding (VJE), a reconstruction-free latent-variable framework for non-contrastive self-supervised learning in repr

Large Language Models Decide Early and Explain Later

arXiv:2604.22266v1 Announce Type: new Abstract: Large Language Models often achieve strong performance by generating long intermediate chain-of-thought reasoning. However, it remains unclear when a mo

LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs

arXiv:2602.17681v2 Announce Type: replace-cross Abstract: Post-training quantization (PTQ) is a widely used approach for reducing the memory and compute costs of large language models (LLMs). Recent s

LayerBoost: Layer-Aware Attention Reduction for Efficient LLMs

arXiv:2604.22050v1 Announce Type: cross Abstract: Transformers are mostly relying on softmax attention, which introduces quadratic complexity with respect to sequence length and remains a major bottle

Lifting Unlabeled Internet-level Data for 3D Scene Understanding

arXiv:2604.01907v2 Announce Type: replace-cross Abstract: Annotated 3D scene data is scarce and expensive to acquire, while abundant unlabeled videos are readily available on the internet. In this pap

Measuring and Mitigating Persona Distortions from AI Writing Assistance

arXiv:2604.22503v1 Announce Type: new Abstract: Hundreds of millions of people use artificial intelligence (AI) for writing assistance. Here, we evaluated how AI writing assistance distorts writer per

Mechanistic Interpretability of Antibody Language Models Using SAEs

arXiv:2512.05794v2 Announce Type: replace-cross Abstract: Sparse autoencoders (SAEs) are a mechanistic interpretability technique that have been used to provide insight into learned concepts within la