Copertina

Dynamic Demonstrations Controller for In-Context Learning

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Zhao, Fei, Pang, Taotian, Wu, Zhen, Ma, Zheng, Huang, Shujian, Dai, Xinyu
Natura:	Preprint
Pubblicazione:	2023
Soggetti:	Computation and Language Artificial Intelligence
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

AlignGPT: Multi-modal Large Language Models with Adaptive Alignment Capability
di: Zhao, Fei, et al.
Pubblicazione: (2024)

Demonstration Selection for In-Context Learning via Reinforcement Learning
di: Wang, Xubin, et al.
Pubblicazione: (2024)

In-Context Learning with Iterative Demonstration Selection
di: Qin, Chengwei, et al.
Pubblicazione: (2023)

Rectifying Demonstration Shortcut in In-Context Learning
di: Jang, Joonwon, et al.
Pubblicazione: (2024)

Persona-Aware Alignment Framework for Personalized Dialogue Generation
di: Li, Guanrong, et al.
Pubblicazione: (2025)

Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning
di: Zhu, Wenhao, et al.
Pubblicazione: (2025)

Comparable Demonstrations are Important in In-Context Learning: A Novel Perspective on Demonstration Selection
di: Fan, Caoyun, et al.
Pubblicazione: (2023)

Beyond Demonstrations: Dynamic Vector Construction from Latent Representations
di: Cai, Wang, et al.
Pubblicazione: (2025)

Towards Understanding In-Context Learning with Contrastive Demonstrations and Saliency Maps
di: Liu, Fuxiao, et al.
Pubblicazione: (2023)

The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis
di: Zhang, Miaoran, et al.
Pubblicazione: (2024)

DemoShapley: Valuation of Demonstrations for In-Context Learning
di: Xie, Shan, et al.
Pubblicazione: (2024)

Demonstration Notebook: Finding the Most Suited In-Context Learning Example from Interactions
di: Tang, Yiming, et al.
Pubblicazione: (2024)

Unraveling the Mechanics of Learning-Based Demonstration Selection for In-Context Learning
di: Liu, Hui, et al.
Pubblicazione: (2024)

Demonstrations Are All You Need: Advancing Offensive Content Paraphrasing using In-Context Learning
di: Som, Anirudh, et al.
Pubblicazione: (2023)

Optimizing In-Context Demonstrations for LLM-based Automated Grading
di: Chu, Yucheng, et al.
Pubblicazione: (2026)

Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval
di: Xu, Hao, et al.
Pubblicazione: (2026)

From Introspection to Best Practices: Principled Analysis of Demonstrations in Multimodal In-Context Learning
di: Xu, Nan, et al.
Pubblicazione: (2024)

Comparative Analysis of Demonstration Selection Algorithms for LLM In-Context Learning
di: Shu, Dong, et al.
Pubblicazione: (2024)

CLAUSE: Agentic Neuro-Symbolic Knowledge Graph Reasoning via Dynamic Learnable Context Engineering
di: Zhao, Yang, et al.
Pubblicazione: (2025)

Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models
di: Wen, Xumeng, et al.
Pubblicazione: (2025)

Measuring Meaning Composition in the Human Brain with Composition Scores from Large Language Models
di: Gao, Changjiang, et al.
Pubblicazione: (2024)

AdaComp: Extractive Context Compression with Adaptive Predictor for Retrieval-Augmented Large Language Models
di: Zhang, Qianchi, et al.
Pubblicazione: (2024)

D-GARA: A Dynamic Benchmarking Framework for GUI Agent Robustness in Real-World Anomalies
di: Chen, Sen, et al.
Pubblicazione: (2025)

Optimizing RAG Rerankers with LLM Feedback via Reinforcement Learning
di: Wu, Yuhang, et al.
Pubblicazione: (2026)

Extroversion or Introversion? Controlling The Personality of Your Large Language Models
di: Chen, Yanquan, et al.
Pubblicazione: (2024)

Problem-Solving Logic Guided Curriculum In-Context Learning for LLMs Complex Reasoning
di: Ma, Xuetao, et al.
Pubblicazione: (2025)

Linear-Time Demonstration Selection for In-Context Learning via Gradient Estimation
di: Zhang, Ziniu, et al.
Pubblicazione: (2025)

ACC: Compiling Agent Trajectories for Long-Context Training
di: Su, Qisheng, et al.
Pubblicazione: (2026)

Babysit A Language Model From Scratch: Interactive Language Learning by Trials and Demonstrations
di: Ma, Ziqiao, et al.
Pubblicazione: (2024)

Meta-Sel: Efficient Demonstration Selection for In-Context Learning via Supervised Meta-Learning
di: Wang, Xubin, et al.
Pubblicazione: (2026)

Context-level Language Modeling by Learning Predictive Context Embeddings
di: Dai, Beiya, et al.
Pubblicazione: (2025)

Lost in the Source Language: How Large Language Models Evaluate the Quality of Machine Translation
di: Huang, Xu, et al.
Pubblicazione: (2024)

Learn to Select: Exploring Label Distribution Divergence for In-Context Demonstration Selection in Text Classification
di: Jiang, Ye, et al.
Pubblicazione: (2025)

The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential Recommendation
di: Wang, Lei, et al.
Pubblicazione: (2024)

Retrieval Meets Reasoning: Dynamic In-Context Editing for Long-Text Understanding
di: Fei, Weizhi, et al.
Pubblicazione: (2024)

Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning
di: Wang, Jianing, et al.
Pubblicazione: (2023)

Switchable Decision: Dynamic Neural Generation Networks
di: Zhang, Shujian, et al.
Pubblicazione: (2024)

Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning
di: Wang, Xinyi, et al.
Pubblicazione: (2023)

Out-of-Domain Intent Detection Considering Multi-Turn Dialogue Contexts
di: Lang, Hao, et al.
Pubblicazione: (2023)

Advancing Multimodal In-Context Learning in Large Vision-Language Models with Task-aware Demonstrations
di: Li, Yanshu
Pubblicazione: (2025)