:: Library Catalog

Copertina

Salvato in:

Dettagli Bibliografici
Autore principale:	Dehghani, Mohammad
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Computation and Language
Accesso online:	https://arxiv.org/abs/2402.15755
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

RIFF: Learning to Rephrase Inputs for Few-shot Fine-tuning of Language Models
di: Najafi, Saeed, et al.
Pubblicazione: (2024)

Revisit Few-shot Intent Classification with PLMs: Direct Fine-tuning vs. Continual Pre-training
di: Zhang, Haode, et al.
Pubblicazione: (2023)

Fine-tuning Pre-trained Language Models for Few-shot Intent Detection: Supervised Pre-training and Isotropization
di: Zhang, Haode, et al.
Pubblicazione: (2022)

SPARSEFIT: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations
di: Solano, Jesus, et al.
Pubblicazione: (2023)

A comprehensive cross-language framework for harmful content detection with the aid of sentiment analysis
di: Dehghani, Mohammad
Pubblicazione: (2024)

SBERT studies Meaning Representations: Decomposing Sentence Embeddings into Explainable Semantic Features
di: Opitz, Juri, et al.
Pubblicazione: (2022)

Cost-Efficient Subjective Task Annotation and Modeling through Few-Shot Annotator Adaptation
di: Golazizian, Preni, et al.
Pubblicazione: (2024)

FPT: Feature Prompt Tuning for Few-shot Readability Assessment
di: Wang, Ziyang, et al.
Pubblicazione: (2024)

QoSBERT: An Uncertainty-Aware Approach based on Pre-trained Language Models for Service Quality Prediction
di: Wang, Ziliang, et al.
Pubblicazione: (2025)

ILLUMINER: Instruction-tuned Large Language Models as Few-shot Intent Classifier and Slot Filler
di: Mirza, Paramita, et al.
Pubblicazione: (2024)

Detecting Reddit Users with Depression Using a Hybrid Neural Network SBERT-CNN
di: Chen, Ziyi, et al.
Pubblicazione: (2023)

Chem-FINESE: Validating Fine-Grained Few-shot Entity Extraction through Text Reconstruction
di: Wang, Qingyun, et al.
Pubblicazione: (2024)

Large Margin Prototypical Network for Few-shot Relation Classification with Fine-grained Features
di: Fan, Miao, et al.
Pubblicazione: (2024)

Learning to Learn for Few-shot Continual Active Learning
di: Ho, Stella, et al.
Pubblicazione: (2023)

On the Utility of Domain-Adjacent Fine-Tuned Model Ensembles for Few-shot Problems
di: Alam, Md Ibrahim Ibne, et al.
Pubblicazione: (2024)

Few Dimensions are Enough: Fine-tuning BERT with Selected Dimensions Revealed Its Redundant Nature
di: Fukuhata, Shion, et al.
Pubblicazione: (2025)

Enhancing Readmission Prediction with Deep Learning: Extracting Biomedical Concepts from Clinical Texts
di: Samani, Rasoul, et al.
Pubblicazione: (2024)

Persian Typographical Error Type Detection Using Deep Neural Networks on Algorithmically-Generated Misspellings
di: Dehghani, Mohammad, et al.
Pubblicazione: (2023)

Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
di: Guan, Zihan, et al.
Pubblicazione: (2025)

Retrieval-style In-Context Learning for Few-shot Hierarchical Text Classification
di: Chen, Huiyao, et al.
Pubblicazione: (2024)

Generative Retrieval with Few-shot Indexing
di: Askari, Arian, et al.
Pubblicazione: (2024)

Agent Fine-tuning through Distillation for Domain-specific LLMs in Microdomains
di: Xue, Yawen, et al.
Pubblicazione: (2025)

X-Shot: A Unified System to Handle Frequent, Few-shot and Zero-shot Learning Simultaneously in Classification
di: Xu, Hanzi, et al.
Pubblicazione: (2024)

Political DEBATE: Efficient Zero-shot and Few-shot Classifiers for Political Text
di: Burnham, Michael, et al.
Pubblicazione: (2024)

Explainable Few-shot Knowledge Tracing
di: Li, Haoxuan, et al.
Pubblicazione: (2024)

Few-shot text-based emotion detection
di: Marchitan, Teodor-George, et al.
Pubblicazione: (2025)

Learning or Self-aligning? Rethinking Instruction Fine-tuning
di: Ren, Mengjie, et al.
Pubblicazione: (2024)

Memento: Fine-tuning LLM Agents without Fine-tuning LLMs
di: Zhou, Huichi, et al.
Pubblicazione: (2025)

Few-shot Dialogue Strategy Learning for Motivational Interviewing via Inductive Reasoning
di: Xie, Zhouhang, et al.
Pubblicazione: (2024)

Bilingual Sexism Classification: Fine-Tuned XLM-RoBERTa and GPT-3.5 Few-Shot Learning
di: Azadi, AmirMohammad, et al.
Pubblicazione: (2024)

Pre-trained Language Models and Few-shot Learning for Medical Entity Extraction
di: Wang, Xiaokai, et al.
Pubblicazione: (2025)

Few Tokens, Big Leverage: Preserving Safety Alignment by Constraining Safety Tokens during Fine-tuning
di: Wang, Guoli, et al.
Pubblicazione: (2026)

Zero-shot and Few-shot Generation Strategies for Artificial Clinical Records
di: Frayling, Erlend, et al.
Pubblicazione: (2024)

Efficient Model Development through Fine-tuning Transfer
di: Lin, Pin-Jie, et al.
Pubblicazione: (2025)

Zero-shot and Few-shot Learning with Instruction-following LLMs for Claim Matching in Automated Fact-checking
di: Pisarevskaya, Dina, et al.
Pubblicazione: (2025)

Mechanistic Fine-tuning for In-context Learning
di: Cho, Hakaze, et al.
Pubblicazione: (2025)

Effectiveness of Pre-training for Few-shot Intent Classification
di: Zhang, Haode, et al.
Pubblicazione: (2021)

Adapting Knowledge for Few-shot Table-to-Text Generation
di: Guo, Zhixin, et al.
Pubblicazione: (2023)

Zero and Few-shot Semantic Parsing with Ambiguous Inputs
di: Stengel-Eskin, Elias, et al.
Pubblicazione: (2023)

Intent-driven In-context Learning for Few-shot Dialogue State Tracking
di: Yi, Zihao, et al.
Pubblicazione: (2024)