Image de couverture de livre

Assertion Enhanced Few-Shot Learning: Instructive Technique for Large Language Models to Generate Educational Explanations

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Shahriar, Tasmia, Ramos, Kelly, Matsuda, Noboru
Format:	Preprint
Publié:	2023
Sujets:	Computation and Language
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Beyond prior knowledge: The predictive role of knowledge-building in Tutor Learning
par: Shahriar, Tasmia, et autres
Publié: (2025)

Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
par: Kim, Taehyeon, et autres
Publié: (2023)

Assertion Detection Large Language Model In-context Learning LoRA Fine-tuning
par: Ji, Yuelyu, et autres
Publié: (2024)

Benchmarking Open-Source Large Language Models for Persian in Zero-Shot and Few-Shot Learning
par: Cherakhloo, Mahdi, et autres
Publié: (2025)

Enhancing Few-Shot Vision-Language Classification with Large Multimodal Model Features
par: Mitra, Chancharik, et autres
Publié: (2024)

Enhancing Vision-Language Few-Shot Adaptation with Negative Learning
par: Zhang, Ce, et autres
Publié: (2024)

Structured Gradient Guidance for Few-Shot Adaptation in Large Language Models
par: Zheng, Hongye, et autres
Publié: (2025)

How Large Language Models Balance Internal Knowledge with User and Document Assertions
par: Li, Shuowei, et autres
Publié: (2026)

Low-Resource Cross-Lingual Summarization through Few-Shot Learning with Large Language Models
par: Park, Gyutae, et autres
Publié: (2024)

ActiveLLM: Large Language Model-based Active Learning for Textual Few-Shot Scenarios
par: Bayer, Markus, et autres
Publié: (2024)

Leveraging Biases in Large Language Models: "bias-kNN'' for Effective Few-Shot Learning
par: Zhang, Yong, et autres
Publié: (2024)

Large Language Models for Few-Shot Named Entity Recognition
par: Zhao, Yufei, et autres
Publié: (2018)

Instructive Dialogue Summarization with Query Aggregations
par: Wang, Bin, et autres
Publié: (2023)

Large Language Models are Few-Shot Training Example Generators: A Case Study in Fallacy Recognition
par: Alhindi, Tariq, et autres
Publié: (2023)

FLEx: Language Modeling with Few-shot Language Explanations
par: Avsian, Adar, et autres
Publié: (2026)

Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategies
par: Kuila, Alapan, et autres
Publié: (2024)

PROMPTEVALS: A Dataset of Assertions and Guardrails for Custom Production Large Language Model Pipelines
par: Vir, Reya, et autres
Publié: (2025)

Refactoring Programs Using Large Language Models with Few-Shot Examples
par: Shirafuji, Atsushi, et autres
Publié: (2023)

Leveraging Prompts in LLMs to Overcome Imbalances in Complex Educational Text Data
par: McClure, Jeanne, et autres
Publié: (2024)

Few-Shot Knowledge Distillation of LLMs With Counterfactual Explanations
par: Hamman, Faisal, et autres
Publié: (2025)

Relic: Enhancing Reward Model Generalization for Low-Resource Indic Languages with Few-Shot Examples
par: Ghosal, Soumya Suvra, et autres
Publié: (2025)

Language Models are Few-Shot Graders
par: Zhao, Chenyan, et autres
Publié: (2025)

Bridging Language Gaps: Enhancing Few-Shot Language Adaptation
par: Borchert, Philipp, et autres
Publié: (2025)

Analyzing and Adapting Large Language Models for Few-Shot Multilingual NLU: Are We There Yet?
par: Razumovskaia, Evgeniia, et autres
Publié: (2024)

LLMs on Drugs: Language Models Are Few-Shot Consumers
par: Doudkin, Alexander
Publié: (2025)

GeMQuAD : Generating Multilingual Question Answering Datasets from Large Language Models using Few Shot Learning
par: Namboori, Amani, et autres
Publié: (2024)

Evaluation of Few-Shot Learning for Classification Tasks in the Polish Language
par: Hadeliya, Tsimur, et autres
Publié: (2024)

WikiChat: Stopping the Hallucination of Large Language Model Chatbots by Few-Shot Grounding on Wikipedia
par: Semnani, Sina J., et autres
Publié: (2023)

Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors
par: Li, Guozheng, et autres
Publié: (2024)

Few-Shot Recalibration of Language Models
par: Li, Xiang Lisa, et autres
Publié: (2024)

Seal: Advancing Speech Language Models to be Few-Shot Learners
par: Lei, Shuyu, et autres
Publié: (2024)

Group Preference Optimization: Few-Shot Alignment of Large Language Models
par: Zhao, Siyan, et autres
Publié: (2023)

DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines
par: Singhvi, Arnav, et autres
Publié: (2023)

ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models
par: Lin, Yujie, et autres
Publié: (2026)

AssertBench: A Benchmark for Evaluating Self-Assertion in Large Language Models
par: Lee, Jaeho, et autres
Publié: (2025)

llmNER: (Zero|Few)-Shot Named Entity Recognition, Exploiting the Power of Large Language Models
par: Villena, Fabián, et autres
Publié: (2024)

LLM-DA: Data Augmentation via Large Language Models for Few-Shot Named Entity Recognition
par: Ye, Junjie, et autres
Publié: (2024)

FewMMBench: A Benchmark for Multimodal Few-Shot Learning
par: Dogan, Mustafa, et autres
Publié: (2026)

Unlocking Instructive In-Context Learning with Tabular Prompting for Relational Triple Extraction
par: Li, Guozheng, et autres
Publié: (2024)

CLLMFS: A Contrastive Learning enhanced Large Language Model Framework for Few-Shot Named Entity Recognition
par: Zhang, Yafeng, et autres
Publié: (2024)