Imagen de Portada

Venn Diagram Prompting : Accelerating Comprehension with Scaffolding Effect

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Mahendru, Sakshi, Pandit, Tejul
Formato:	Preprint
Publicado:	2024
Materias:	Computation and Language Artificial Intelligence Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

SecureNet: A Comparative Study of DeBERTa and Large Language Models for Phishing Detection
por: Mahendru, Sakshi, et al.
Publicado: (2024)

The Evolution of Reranking Models in Information Retrieval: From Heuristic Methods to Large Language Models
por: Pandit, Tejul, et al.
Publicado: (2025)

Multi-Domain ABSA Conversation Dataset Generation via LLMs for Real-World Evaluation and Model Comparison
por: Pandit, Tejul, et al.
Publicado: (2025)

MetaSynth: Meta-Prompting-Driven Agentic Scaffolds for Diverse Synthetic Data Generation
por: Riaz, Haris, et al.
Publicado: (2025)

On the Diagram of Thought
por: Zhang, Yifan, et al.
Publicado: (2024)

MedHallu: A Comprehensive Benchmark for Detecting Medical Hallucinations in Large Language Models
por: Pandit, Shrey, et al.
Publicado: (2025)

Superposition Prompting: Improving and Accelerating Retrieval-Augmented Generation
por: Merth, Thomas, et al.
Publicado: (2024)

Eigen Attention: Attention in Low-Rank Space for KV Cache Compression
por: Saxena, Utkarsh, et al.
Publicado: (2024)

Speaking the Same Language: Leveraging LLMs in Standardizing Clinical Data for AI
por: Sett, Arindam, et al.
Publicado: (2024)

Prompt Engineering a Prompt Engineer
por: Ye, Qinyuan, et al.
Publicado: (2023)

Automatic Prompt Optimization with Prompt Distillation
por: Dyagin, Ernest A., et al.
Publicado: (2025)

Working Memory Constraints Scaffold Learning in Transformers under Data Scarcity
por: Madhyastha, Pranava, et al.
Publicado: (2026)

User Intent Recognition and Semantic Cache Optimization-Based Query Processing Framework using CFLIS and MGR-LAU
por: Mahendru, Sakshi
Publicado: (2024)

PromptWizard: Task-Aware Prompt Optimization Framework
por: Agarwal, Eshaan, et al.
Publicado: (2024)

DynaPrompt: Dynamic Test-Time Prompt Tuning
por: Xiao, Zehao, et al.
Publicado: (2025)

Scaf-GRPO: Scaffolded Group Relative Policy Optimization for Enhancing LLM Reasoning
por: Zhang, Xichen, et al.
Publicado: (2025)

MolLangBench: A Comprehensive Benchmark for Language-Prompted Molecular Structure Recognition, Editing, and Generation
por: Cai, Feiyang, et al.
Publicado: (2025)

Efficient Prompt Tuning by Multi-Space Projection and Prompt Fusion
por: Lan, Pengxiang, et al.
Publicado: (2024)

You Don't Need Prompt Engineering Anymore: The Prompting Inversion
por: Khan, Imran
Publicado: (2025)

Hard2Verify: A Step-Level Verification Benchmark for Open-Ended Frontier Math
por: Pandit, Shrey, et al.
Publicado: (2025)

Salient Information Prompting to Steer Content in Prompt-based Abstractive Summarization
por: Xu, Lei, et al.
Publicado: (2024)

Prompt-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression
por: Ali, Muhammad Asif, et al.
Publicado: (2024)

Green Prompting: Characterizing Prompt-driven Energy Costs of LLM Inference
por: Adamska, Marta, et al.
Publicado: (2025)

Local Prompt Optimization
por: Jain, Yash, et al.
Publicado: (2025)

Plug and Play with Prompts: A Prompt Tuning Approach for Controlling Text Generation
por: Ajwani, Rohan Deepak, et al.
Publicado: (2024)

Hard Prompts Made Interpretable: Sparse Entropy Regularization for Prompt Tuning with RL
por: Choi, Yunseon, et al.
Publicado: (2024)

RePrompt: Planning by Automatic Prompt Engineering for Large Language Models Agents
por: Chen, Weizhe, et al.
Publicado: (2024)

CP-Prompt: Composition-Based Cross-modal Prompting for Domain-Incremental Continual Learning
por: Feng, Yu, et al.
Publicado: (2024)

Revisiting Prompt Sensitivity in Large Language Models for Text Classification: The Role of Prompt Underspecification
por: Pecher, Branislav, et al.
Publicado: (2026)

FaithEval: Can Your Language Model Stay Faithful to Context, Even If "The Moon is Made of Marshmallows"
por: Ming, Yifei, et al.
Publicado: (2024)

Self-Supervised Prompt Optimization
por: Xiang, Jinyu, et al.
Publicado: (2025)

PromptKD: Distilling Student-Friendly Knowledge for Generative Language Models via Prompt Tuning
por: Kim, Gyeongman, et al.
Publicado: (2024)

Symbolic Prompt Program Search: A Structure-Aware Approach to Efficient Compile-Time Prompt Optimization
por: Schnabel, Tobias, et al.
Publicado: (2024)

How Susceptible are LLMs to Influence in Prompts?
por: Anagnostidis, Sotiris, et al.
Publicado: (2024)

The Unreasonable Effectiveness of Eccentric Automatic Prompts
por: Battle, Rick, et al.
Publicado: (2024)

PRewrite: Prompt Rewriting with Reinforcement Learning
por: Kong, Weize, et al.
Publicado: (2024)

Subgraph-level Universal Prompt Tuning
por: Lee, Junhyun, et al.
Publicado: (2024)

Continuous QA Learning with Structured Prompts
por: Zheng, Yinhe
Publicado: (2022)

Error Taxonomy-Guided Prompt Optimization
por: Singh, Mayank, et al.
Publicado: (2026)

System Prompt Optimization with Meta-Learning
por: Choi, Yumin, et al.
Publicado: (2025)