Cover Image

Advancing Scientific Text Classification: Fine-Tuned Models with Dataset Expansion and Hard-Voting

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Rostam, Zhyar Rzgar K, Kertész, Gábor
Format:	Preprint
Published:	2025
Subjects:	Computation and Language Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Fine-Tuning Large Language Models for Scientific Text Classification: A Comparative Study
by: Rostam, Zhyar Rzgar K, et al.
Published: (2024)

EQ-5D Classification Using Biomedical Entity-Enriched Pre-trained Language Models and Multiple Instance Learning
by: Rostam, Zhyar Rzgar K, et al.
Published: (2026)

Advances in Pre-trained Language Models for Domain-Specific Text Classification: A Systematic Review
by: Rostam, Zhyar Rzgar K., et al.
Published: (2025)

Achieving Peak Performance for Large Language Models: A Systematic Review
by: Rostam, Zhyar Rzgar K, et al.
Published: (2024)

Exploring Variability in Fine-Tuned Models for Text Classification with DistilBERT
by: Lorenzoni, Giuliano, et al.
Published: (2024)

SmoothRot: Combining Channel-Wise Scaling and Rotation for Quantization-Friendly LLMs
by: Czakó, Patrik, et al.
Published: (2025)

Turning LLM Activations Quantization-Friendly
by: Czakó, Patrik, et al.
Published: (2025)

State of the Art in Text Classification for South Slavic Languages: Fine-Tuning or Prompting?
by: Pungeršek, Taja Kuzman, et al.
Published: (2025)

A Comparative Analysis of Instruction Fine-Tuning LLMs for Financial Text Classification
by: Fatemi, Sorouralsadat, et al.
Published: (2024)

Advancing Single and Multi-task Text Classification through Large Language Model Fine-tuning
by: Zhao, Hang, et al.
Published: (2024)

Enhancing Clinical Text Classification via Fine-Tuned DRAGON Longformer Models
by: Yang, Mingchuan, et al.
Published: (2025)

Fine-Tuning Causal LLMs for Text Classification: Embedding-Based vs. Instruction-Based Approaches
by: Yousefiramandi, Amirhossein, et al.
Published: (2025)

GPT-4 for Occlusion Order Recovery
by: Saleh, Kaziwa, et al.
Published: (2025)

Parameter-Efficient Fine-Tuning for Medical Text Summarization: A Comparative Study of Lora, Prompt Tuning, and Full Fine-Tuning
by: Shernazarov, Ulugbek, et al.
Published: (2026)

CrisisSense-LLM: Instruction Fine-Tuned Large Language Model for Multi-label Social Media Text Classification in Disaster Informatics
by: Yin, Kai, et al.
Published: (2024)

Prompting and Fine-Tuning Open-Sourced Large Language Models for Stance Classification
by: Cruickshank, Iain J., et al.
Published: (2023)

AnyTaskTune: Advanced Domain-Specific Solutions through Task-Fine-Tuning
by: Cui, Jiaxi, et al.
Published: (2024)

Advancing Interpretability in Text Classification through Prototype Learning
by: Wei, Bowen, et al.
Published: (2024)

SPFT-SQL: Enhancing Large Language Model for Text-to-SQL Parsing by Self-Play Fine-Tuning
by: Zhang, Yuhao, et al.
Published: (2025)

Fine-Tuned 'Small' LLMs (Still) Significantly Outperform Zero-Shot Generative AI Models in Text Classification
by: Bucher, Martin Juan José, et al.
Published: (2024)

A New Pipeline For Generating Instruction Dataset via RAG and Self Fine-Tuning
by: Song, Chih-Wei, et al.
Published: (2024)

Overtrained Language Models Are Harder to Fine-Tune
by: Springer, Jacob Mitchell, et al.
Published: (2025)

Memorization in Fine-Tuned Large Language Models
by: Savine, Danil
Published: (2025)

SyntheT2C: Generating Synthetic Data for Fine-Tuning Large Language Models on the Text2Cypher Task
by: Zhong, Ziije, et al.
Published: (2024)

Quantifying and Mitigating Selection Bias in LLMs: A Transferable LoRA Fine-Tuning and Efficient Majority Voting Approach
by: Guda, Blessed, et al.
Published: (2025)

Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models
by: Barnett, Scott, et al.
Published: (2024)

dVoting: Fast Voting for dLLMs
by: Feng, Sicheng, et al.
Published: (2026)

Safety-Aware Fine-Tuning of Large Language Models
by: Choi, Hyeong Kyu, et al.
Published: (2024)

Phased Instruction Fine-Tuning for Large Language Models
by: Pang, Wei, et al.
Published: (2024)

Classification of Radiological Text in Small and Imbalanced Datasets in a Non-English Language
by: Beliveau, Vincent, et al.
Published: (2024)

InfiMed-Foundation: Pioneering Advanced Multimodal Medical Models with Compute-Efficient Pre-Training and Multi-Stage Fine-Tuning
by: Zhu, Guanghao, et al.
Published: (2025)

A System for Automatic English Text Expansion
by: Méndez, Silvia García, et al.
Published: (2024)

Natural Language Fine-Tuning
by: Liu, Jia, et al.
Published: (2024)

Schema on the Inside: A Two-Phase Fine-Tuning Method for High-Efficiency Text-to-SQL at Scale
by: Soni, Chinmay, et al.
Published: (2026)

Model Fusion through Bayesian Optimization in Language Model Fine-Tuning
by: Jang, Chaeyun, et al.
Published: (2024)

Towards Efficient Large Language Models for Scientific Text: A Review
by: To, Huy Quoc, et al.
Published: (2024)

Reversing Large Language Models for Efficient Training and Fine-Tuning
by: Gal, Eshed, et al.
Published: (2025)

Impact of Fine-Tuning Methods on Memorization in Large Language Models
by: Hou, Jie, et al.
Published: (2025)

Fine-Tuned Language Models for Domain-Specific Summarization and Tagging
by: Wang, Jun, et al.
Published: (2025)

EvalYaks: Instruction Tuning Datasets and LoRA Fine-tuned Models for Automated Scoring of CEFR B2 Speaking Assessment Transcripts
by: Scaria, Nicy, et al.
Published: (2024)