:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Ono, Kyoka, Lee, Simon A.
Format:	Preprint
Published:	2024
Subjects:	Computation and Language Machine Learning
Online Access:	https://arxiv.org/abs/2406.13846
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

In-Context Learning Learns Label Relationships but Is Not Conventional Learning
by: Kossen, Jannik, et al.
Published: (2023)

TabSTAR: A Tabular Foundation Model for Tabular Data with Text Fields
by: Arazi, Alan, et al.
Published: (2025)

MulTaBench: Benchmarking Multimodal Tabular Learning with Text and Image
by: Arazi, Alan, et al.
Published: (2026)

Accept or Deny? Evaluating LLM Fairness and Performance in Loan Approval across Table-to-Text Serialization Approaches
by: Azime, Israel Abebe, et al.
Published: (2025)

Detecting AI Generated Text Based on NLP and Machine Learning Approaches
by: Prova, Nuzhat
Published: (2024)

Tabular Transfer Learning via Prompting LLMs
by: Nam, Jaehyun, et al.
Published: (2024)

ClinicRealm: Re-evaluating Large Language Models with Conventional Machine Learning for Non-Generative Clinical Prediction Tasks
by: Zhu, Yinghao, et al.
Published: (2024)

Debugging Tabular Log as Dynamic Graphs
by: Liang, Chumeng, et al.
Published: (2025)

Magic Words or Methodical Work? Challenging Conventional Wisdom in LLM-Based Political Text Annotation
by: McLaren, Lorcan, et al.
Published: (2026)

Detection of Machine-Generated Text: Literature Survey
by: Valiaiev, Dmytro
Published: (2024)

When 2D Tasks Meet 1D Serialization: On Serialization Friction in Structured Tasks
by: Lo, Chung-Hsiang, et al.
Published: (2026)

Can MLLMs Perform Text-to-Image In-Context Learning?
by: Zeng, Yuchen, et al.
Published: (2024)

Transfer Learning of Tabular Data by Finetuning Large Language Models
by: Rabbani, Shourav B., et al.
Published: (2025)

An Automatic Prompt Generation System for Tabular Data Tasks
by: Akella, Ashlesha, et al.
Published: (2024)

Not All Features Deserve Attention: Graph-Guided Dependency Learning for Tabular Data Generation with Language Models
by: Zhang, Zheyu, et al.
Published: (2025)

Reducing and Exploiting Data Augmentation Noise through Meta Reweighting Contrastive Learning for Text Classification
by: Mou, Guanyi, et al.
Published: (2024)

iGAiVA: Integrated Generative AI and Visual Analytics in a Machine Learning Workflow for Text Classification
by: Jin, Yuanzhe, et al.
Published: (2024)

On the Relationship Between the Choice of Representation and In-Context Learning
by: Marinescu, Ioana, et al.
Published: (2025)

Making Pre-trained Language Models Great on Tabular Prediction
by: Yan, Jiahuan, et al.
Published: (2024)

Small Models are LLM Knowledge Triggers on Medical Tabular Prediction
by: Yan, Jiahuan, et al.
Published: (2024)

Large Scale Transfer Learning for Tabular Data via Language Modeling
by: Gardner, Josh, et al.
Published: (2024)

Unsupervised Text Embedding Space Generation Using Generative Adversarial Networks for Text Synthesis
by: Lee, Jun-Min, et al.
Published: (2023)

Personalized Product Search Ranking: A Multi-Task Learning Approach with Tabular and Non-Tabular Data
by: Morishetti, Lalitesh, et al.
Published: (2025)

Locate&Edit: Energy-based Text Editing for Efficient, Flexible, and Faithful Controlled Text Generation
by: Son, Hye Ryung, et al.
Published: (2024)

Predicting Decisions of AI Agents from Limited Interaction through Text-Tabular Modeling
by: Shapira, Eilam, et al.
Published: (2026)

Mitigating Paraphrase Attacks on Machine-Text Detectors via Paraphrase Inversion
by: Soto, Rafael Rivera, et al.
Published: (2024)

Few-Shot Detection of Machine-Generated Text using Style Representations
by: Soto, Rafael Rivera, et al.
Published: (2024)

An Evaluation of Explanation Methods for Black-Box Detectors of Machine-Generated Text
by: Schoenegger, Loris, et al.
Published: (2024)

EdiText: Controllable Coarse-to-Fine Text Editing with Diffusion Language Models
by: Lee, Che Hyun, et al.
Published: (2025)

Elephants Never Forget: Testing Language Models for Memorization of Tabular Data
by: Bordt, Sebastian, et al.
Published: (2024)

Beyond Extraction: Contextualising Tabular Data for Efficient Summarisation by Language Models
by: Allu, Uday, et al.
Published: (2024)

Harnessing LLMs Explanations to Boost Surrogate Models in Tabular Data Classification
by: Shi, Ruxue, et al.
Published: (2025)

Towards Universal Debiasing for Language Models-based Tabular Data Generation
by: Li, Tianchun, et al.
Published: (2025)

Efficient Uncertainty Estimation for LLM-based Entity Linking in Tabular Data
by: Bono, Carlo, et al.
Published: (2025)

Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Models
by: Bordt, Sebastian, et al.
Published: (2024)

Stress Detection on Code-Mixed Texts in Dravidian Languages using Machine Learning
by: Ramos, L., et al.
Published: (2024)

Smaller Language Models are Better Black-box Machine-Generated Text Detectors
by: Mireshghallah, Niloofar, et al.
Published: (2023)

Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis
by: An, Seunghwan, et al.
Published: (2024)

IRIS: An Iterative and Integrated Framework for Verifiable Causal Discovery in the Absence of Tabular Data
by: Feng, Tao, et al.
Published: (2025)

SAFT: Structure-Aware Fine-Tuning of LLMs for AMR-to-Text Generation
by: Kamel, Rafiq, et al.
Published: (2025)