Cover Image

Text embedding models can be great data engineers

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Kazemian, Iman, Ramanan, Paritosh, Yildirim, Murat
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Attention is All You Need to Optimize Wind Farm Operations and Maintenance
by: Kazemian, Iman, et al.
Published: (2024)

AttenMfg: An Attention Network Based Optimization Framework for Sensor-Driven Operations & Maintenance in Manufacturing Systems
by: Kazemian, Iman, et al.
Published: (2025)

Learning Unknown Interdependencies for Decentralized Root Cause Analysis in Nonlinear Dynamical Systems
by: Mohanty, Ayush, et al.
Published: (2026)

Sensor-Driven Predictive Vehicle Maintenance and Routing Problem with Time Windows
by: Kazemian, Iman, et al.
Published: (2024)

Federated Granger Causality Learning for Interdependent Clients with State Space Representation
by: Mohanty, Ayush, et al.
Published: (2025)

SplitVAEs: Decentralized scenario generation from siloed data for stochastic optimization problems
by: Islam, H M Mohaimanul, et al.
Published: (2024)

Process Knowledge Driven Change Point Detection for Automated Calibration of Discrete Event Simulation Models Using Machine Learning
by: Yildirim, Suleyman, et al.
Published: (2020)

Pruned Adaptation Modules: A Simple yet Strong Baseline for Continual Foundation Models
by: Yildirim, Elif Ceren Gok, et al.
Published: (2026)

How can embedding models bind concepts?
by: Uselis, Arnas, et al.
Published: (2026)

Symbolic Imitation Learning: From Black-Box to Explainable Driving Policies
by: Sharifi, Iman, et al.
Published: (2023)

GenPluSSS: A Genetic Algorithm Based Plugin for Measured Subsurface Scattering Representation
by: Yıldırım, Barış, et al.
Published: (2024)

Unlocking [CLS] Features for Continual Post-Training
by: Yildirim, Murat Onur, et al.
Published: (2025)

Continual Learning on a Data Diet
by: Yildirim, Elif Ceren Gok, et al.
Published: (2024)

Automated Machine Learning for Unsupervised Tabular Tasks
by: Singh, Prabhant, et al.
Published: (2025)

Towards Safe Autonomous Driving Policies using a Neuro-Symbolic Deep Reinforcement Learning Approach
by: Sharifi, Iman, et al.
Published: (2023)

AdaCL:Adaptive Continual Learning
by: Yildirim, Elif Ceren Gok, et al.
Published: (2023)

Random Features Approximation for Control-Affine Systems
by: Kazemian, Kimia, et al.
Published: (2024)

Accelerating Distributed Optimization: A Primal-Dual Perspective on Local Steps
by: Yang, Junchi, et al.
Published: (2024)

Self-Regulated Neurogenesis for Online Data-Incremental Learning
by: Yildirim, Murat Onur, et al.
Published: (2024)

Causal Inference on Outcomes Learned from Text
by: Modarressi, Iman, et al.
Published: (2025)

Low-dimensional embeddings of high-dimensional data
by: de Bodt, Cyril, et al.
Published: (2025)

Multi Part Deployment of Neural Network
by: Ranjan, Paritosh, et al.
Published: (2025)

Airborne Neural Network
by: Ranjan, Paritosh, et al.
Published: (2025)

G-NeuroDAVIS: A Neural Network model for generalized embedding, data visualization and sample generation
by: Maitra, Chayan, et al.
Published: (2024)

Differentially Private Online Bayesian Estimation With Adaptive Truncation
by: Yıldırım, Sinan
Published: (2023)

MCMC for Bayesian estimation of Differential Privacy from Membership Inference Attacks
by: Yildirim, Ceren, et al.
Published: (2025)

CLAMS: A System for Zero-Shot Model Selection for Clustering
by: Singh, Prabhant, et al.
Published: (2024)

Hierarchical NeuroSymbolic Approach for Comprehensive and Explainable Action Quality Assessment
by: Okamoto, Lauren, et al.
Published: (2024)

A Linear Programming Enhanced Genetic Algorithm for Hyperparameter Tuning in Machine Learning
by: Sinha, Ankur, et al.
Published: (2024)

Machine learning for structural design models of continuous beam systems via influence zones
by: Gallet, Adrien, et al.
Published: (2024)

Harnessing the Full Potential of RRAMs through Scalable and Distributed In-Memory Computing with Integrated Error Correction
by: Vo, Huynh Q. N., et al.
Published: (2025)

The Lynchpin of In-Memory Computing: A Benchmarking Framework for Vector-Matrix Multiplication in RRAMs
by: Chowdhury, Md Tawsif Rahman, et al.
Published: (2024)

Distributed Bayesian Estimation in Sensor Networks: Consensus on Marginal Densities
by: Paritosh, Parth, et al.
Published: (2023)

Make Interval Bound Propagation great again
by: Krukowski, Patryk, et al.
Published: (2024)

Torus embeddings
by: Stowell, Dan
Published: (2026)

oRANS: Online optimisation of RANS machine learning models with embedded DNS data generation
by: Dehtyriov, Daniel, et al.
Published: (2025)

Efficient numeracy in language models through single-token number embeddings
by: Kreitner, Linus, et al.
Published: (2025)

Switch-Based Multi-Part Neural Network
by: Majumder, Surajit, et al.
Published: (2025)

Concentration bounds on response-based vector embeddings of black-box generative models
by: Acharyya, Aranyak, et al.
Published: (2025)

Prior shift estimation for positive unlabeled data through the lens of kernel embedding
by: Mielniczuk, Jan, et al.
Published: (2025)