Search: “research”

Job Skill Extraction via LLM-Centric Multi-Module Framework

arXiv:2604.21525v1 Announce Type: new Abstract: Span-level skill extraction from job advertisements underpins candidate-job matching and labor-market analytics, yet generative large language models (L

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KGiRAG: An Iterative GraphRAG Approach for Responding Sensemaking Queries

DGX agent

arXiv:2604.20859v1 Announce Type: cross Abstract: Recent literature highlights the potential of graph-based approaches within large language model (LLM) retrieval-augmented generation (RAG) pipelines

researcharxiv-cs-ai

24 Apr 2026

KinetiDiff: Docking-Guided Diffusion for De Novo ACVR1 Inhibitor Design in Fibrodysplasia Ossificans Progressiva

arXiv:2604.20886v1 Announce Type: cross Abstract: We present KinetiDiff, a structure-based framework for de novo kinase inhibitor design that integrates a Geometry-Complete Diffusion Model with real-t

Large-Scale Data Parallelization of Product Quantization and Inverted Indexing Using Dask

arXiv:2604.21645v1 Announce Type: new Abstract: Large-scale Nearest Neighbor (NN) search, though widely utilized in the similarity search field, remains challenged by the computational limitations inh

LatRef-Diff: Latent and Reference-Guided Diffusion for Facial Attribute Editing and Style Manipulation

arXiv:2604.21279v1 Announce Type: new Abstract: Facial attribute editing and style manipulation are crucial for applications like virtual avatars and photo editing. However, achieving precise control

Learning State-Tracking from Code Using Linear RNNs

arXiv:2602.14814v2 Announce Type: replace-cross Abstract: Over the last years, state-tracking tasks, particularly permutation composition, have become a testbed to understand the limits of sequence mo

Linear Image Generation by Synthesizing Exposure Brackets

arXiv:2604.21008v1 Announce Type: new Abstract: The life of a photo begins with photons striking the sensor, whose signals are passed through a sophisticated image signal processing (ISP) pipeline to

Listen and Chant Before You Read: The Ladder of Beauty in LM Pre-Training

arXiv:2604.21265v1 Announce Type: new Abstract: We show that pre-training a Transformer on music before language significantly accelerates language acquisition. Using piano performances (MAESTRO datas

Long-Horizon Manipulation via Trace-Conditioned VLA Planning

arXiv:2604.21924v1 Announce Type: new Abstract: Long-horizon manipulation remains challenging for vision-language-action (VLA) policies: real tasks are multi-step, progress-dependent, and brittle to c

researcharxiv-cs-ro

Losing our Tail, Again: (Un)Natural Selection & Multilingual LLMs

arXiv:2507.03933v3 Announce Type: replace Abstract: Multilingual Large Language Models considerably changed how technologies influence language. While previous technologies could mediate or assist hum

Low Cost, High Efficiency: LiDAR Place Recognition in Vineyards with Matryoshka Representation Learning

arXiv:2601.18714v2 Announce Type: replace-cross Abstract: Localization in agricultural environments is challenging due to their unstructured nature and lack of distinctive landmarks. Although agricult

LRDUN: A Low-Rank Deep Unfolding Network for Efficient Spectral Compressive Imaging

arXiv:2511.18513v2 Announce Type: replace Abstract: Deep unfolding networks (DUNs) have achieved remarkable success and become the mainstream paradigm for spectral compressive imaging (SCI) reconstruc

M-CARE: Standardized Clinical Case Reporting for AI Model Behavioral Disorders, with a 20-Case Atlas and Experimental Validation

arXiv:2604.20871v1 Announce Type: cross Abstract: We introduce M-CARE (Model Clinical Assessment and Reporting for Evaluation), a clinical case report framework for AI model behavioral disorders adapt

Machine learning and digital pragmatics: Which word category influences emoji use most?

arXiv:2604.21108v1 Announce Type: new Abstract: This study investigates Machine Learning (ML) in the prediction of emojis in Arabic tweets employing the (state-of-the-art) MARBERT model. A corpus of 1

Materialistic RIR: Material Conditioned Realistic RIR Generation

arXiv:2604.21119v1 Announce Type: cross Abstract: Rings like gold, thuds like wood! The sound we hear in a scene is shaped not only by the spatial layout of the environment but also by the materials o

mcdok at SemEval-2026 Task 13: Finetuning LLMs for Detection of Machine-Generated Code

arXiv:2604.21365v1 Announce Type: cross Abstract: Multi-domain detection of the machine-generated code snippets in various programming languages is a challenging task. SemEval-2026 Task~13 copes with

Micro-DualNet: Dual-Path Spatio-Temporal Network for Micro-Action Recognition

arXiv:2604.21011v1 Announce Type: new Abstract: Micro-actions are subtle, localized movements lasting 1-3 seconds such as scratching one's head or tapping fingers. Such subtle actions are essential fo

MiMIC: Mitigating Visual Modality Collapse in Universal Multimodal Retrieval While Avoiding Semantic Misalignment

arXiv:2604.21326v1 Announce Type: cross Abstract: Universal Multimodal Retrieval (UMR) aims to map different modalities (e.g., visual and textual) into a shared embedding space for multi-modal retriev

MKJ at SemEval-2026 Task 9: A Comparative Study of Generalist, Specialist, and Ensemble Strategies for Multilingual Polarization

arXiv:2604.21370v1 Announce Type: new Abstract: We present a systematic study of multilingual polarization detection across 22 languages for SemEval-2026 Task 9 (Subtask 1), contrasting multilingual g

Multiscale Super Resolution without Image Priors

arXiv:2604.21810v1 Announce Type: new Abstract: We address the ambiguities in the super-resolution problem under translation. We demonstrate that combinations of low-resolution images at different sca

Neuro-Symbolic Manipulation Understanding with Enriched Semantic Event Chains

arXiv:2604.21053v1 Announce Type: cross Abstract: Robotic systems operating in human environments must reason about how object interactions evolve over time, which actions are currently being performe

Not-a-Bandit: Provably No-Regret Drafter Selection in Speculative Decoding for LLMs

arXiv:2510.20064v2 Announce Type: replace Abstract: Speculative decoding is widely used in accelerating large language model (LLM) inference. In this work, we focus on the online draft model selection

NPU Design for Diffusion Language Model Inference

arXiv:2601.20706v2 Announce Type: replace-cross Abstract: Diffusion-based LLMs (dLLMs) fundamentally depart from traditional autoregressive (AR) LLM inference: they leverage bidirectional attention, b

On the algebra of Koopman eigenfunctions and on some of their infinities

arXiv:2604.21825v1 Announce Type: cross Abstract: For continuous-time dynamical systems with reversible trajectories, the nowhere-vanishing eigenfunctions of the Koopman operator of the system form a

On the Relationship between Bayesian Networks and Probabilistic Structural Causal Models

arXiv:2603.27406v2 Announce Type: replace Abstract: In this paper, the relationship between probabilistic graphical models, in particular Bayesian networks, and causal diagrams, also called structural

Optimal Aggregation of LLM and PRM Signals for Efficient Test-Time Scaling

arXiv:2510.13918v2 Announce Type: replace Abstract: Process reward models (PRMs) are a cornerstone of test-time scaling (TTS), designed to verify and select the best responses from large language mode

PanGuide3D: Cohort-Robust Pancreas Tumor Segmentation via Probabilistic Pancreas Conditioning and a Transformer Bottleneck

arXiv:2604.20981v1 Announce Type: cross Abstract: Pancreatic tumor segmentation in contrast-enhanced computed tomography (CT) is clinically important yet technically challenging: lesions are often sma

Partially Lazy Gradient Descent for Smoothed Online Learning

arXiv:2601.15984v2 Announce Type: replace Abstract: We introduce extsc{k-lazyGD}, an online learning algorithm that bridges the gap between greedy Online Gradient Descent (OGD, for k{=}1) and lazy GD/

PAT3D: Physics-Augmented Text-to-3D Scene Generation

arXiv:2511.21978v2 Announce Type: replace Abstract: We introduce PAT3D, the first physics-augmented text-to-3D scene generation framework that integrates vision-language models with physics-based simu

PDGMM-VAE: A Variational Autoencoder with Adaptive Per-Dimension Gaussian Mixture Model Priors for Nonlinear ICA

arXiv:2603.23547v2 Announce Type: replace-cross Abstract: Independent component analysis is a core framework within blind source separation for recovering latent source signals from observed mixtures

PercHead: Perceptual Head Model for Single-Image 3D Head Reconstruction & Editing

arXiv:2511.02777v2 Announce Type: replace Abstract: We present PercHead, a model for single-image 3D head reconstruction and disentangled 3D editing - two tasks that are inherently challenging due to

Phonological Subspace Collapse Is Aetiology-Specific and Cross-Lingually Stable: Evidence from 3,374 Speakers

arXiv:2604.21706v1 Announce Type: new Abstract: We previously introduced a training-free method for dysarthria severity assessment based on d-prime separability of phonological feature subspaces in fr

Planning Beyond Text: Graph-based Reasoning for Complex Narrative Generation

arXiv:2604.21253v1 Announce Type: cross Abstract: While LLMs demonstrate remarkable fluency in narrative generation, existing methods struggle to maintain global narrative coherence, contextual logica

PLAS-Net: Pixel-Level Area Segmentation for UAV-Based Beach Litter Monitoring

arXiv:2604.21313v1 Announce Type: new Abstract: Accurate quantification of the physical exposure area of beach litter, rather than simple item counts, is essential for credible ecological risk assessm

Post-Training Augmentation Invariance

arXiv:2505.11702v2 Announce Type: replace Abstract: This work develops a framework for post-training augmentation invariance, in which our goal is to add invariance properties to a pretrained network

Pre-process for segmentation task with nonlinear diffusion filters

arXiv:2604.21422v1 Announce Type: new Abstract: This paper deals with the case of using nonlinear diffusion filters to obtain piecewise constant images as a previous process for segmentation technique

Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillation

arXiv:2604.21536v1 Announce Type: cross Abstract: Sequential recommender systems have achieved significant success in modeling temporal user behavior but remain limited in capturing rich user semantic

Predicting Scale-Up of Metal-Organic Framework Syntheses with Large Language Models

arXiv:2604.20899v1 Announce Type: cross Abstract: Scalable synthesis remains the gate between MOF discovery and industrial deployment, as scale-up know-how is fragmented across disparate reports. We i

Preferences of a Voice-First Nation: Large-Scale Pairwise Evaluation and Preference Analysis for TTS in Indian Languages

arXiv:2604.21481v1 Announce Type: new Abstract: Crowdsourced pairwise evaluation has emerged as a scalable approach for assessing foundation models. However, applying it to Text to Speech(TTS) introdu

Prefix Parsing is Just Parsing

arXiv:2604.21191v1 Announce Type: new Abstract: Prefix parsing asks whether an input prefix can be extended to a complete string generated by a given grammar. In the weighted setting, it also provides

Preserving Knowledge in Large Language Model with Model-Agnostic Self-Decompression

arXiv:2406.11354v3 Announce Type: replace-cross Abstract: Humans can retain old knowledge while learning new information, but Large Language Models (LLMs) often suffer from catastrophic forgetting whe

Probably Approximately Consensus: On the Learning Theory of Finding Common Ground

arXiv:2604.21811v1 Announce Type: cross Abstract: A primary goal of online deliberation platforms is to identify ideas that are broadly agreeable to a community of users through their expressed prefer

Projected Gradient Unlearning for Text-to-Image Diffusion Models: Defending Against Concept Revival Attacks

arXiv:2604.21041v1 Announce Type: new Abstract: Machine unlearning for text-to-image diffusion models aims to selectively remove undesirable concepts from pre-trained models without costly retraining.

Prototype-Based Test-Time Adaptation of Vision-Language Models

arXiv:2604.21360v1 Announce Type: new Abstract: Test-time adaptation (TTA) has emerged as a promising paradigm for vision-language models (VLMs) to bridge the distribution gap between pre-training and

ReaGeo: Reasoning-Enhanced End-to-End Geocoding with LLMs

arXiv:2604.21357v1 Announce Type: new Abstract: This paper proposes ReaGeo, an end-to-end geocoding framework based on large language models, designed to overcome the limitations of traditional multi-

Relocation of compact sets in R^n by diffeomorphisms and linear separability of datasets in R^n

arXiv:2604.21393v1 Announce Type: new Abstract: Relocation of compact sets in an n-dimensional manifold by self-diffeomorphism is of its own interest as well as significant potential applications to d

Replay-buffer engineering for noise-robust quantum circuit optimization

arXiv:2604.21863v1 Announce Type: cross Abstract: Deep reinforcement learning (RL) for quantum circuit optimization faces three fundamental bottlenecks: replay buffers that ignore the reliability of t

Reversible Deep Learning for 13C NMR in Chemoinformatics: On Structures and Spectra

arXiv:2602.03875v4 Announce Type: replace-cross Abstract: We introduce a reversible deep learning model for 13C NMR that uses a single conditional invertible neural network for both directions between