in-context learning

The Learnability of In-Context Learning NeurIPS 2023 The Transient Nature of Emergent In-Context Learning in Transformers NeurIPS 2023 The Unreasonable Effectiveness of Few-shot Learning for Machine Translation ICML 2023 ThinkSum: Probabilistic reasoning over sets using large language models ACL 2023 ToolkenGPT: Augmenting Frozen Language Models with Massive Tools via Tool Embeddings NeurIPS 2023 Towards Concept-Aware Large Language Models EMNLP 2023 Towards Effective Disambiguation for Machine Translation with Large Language Models EMNLP 2023 Towards In-context Scene Understanding NeurIPS 2023 Towards Informative Few-Shot Prompt with Maximum Information Gain for In-Context Learning EMNLP 2023 Towards Interpretable Mental Health Analysis with Large Language Models EMNLP 2023 Towards Making the Most of ChatGPT for Machine Translation EMNLP 2023 Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters ACL 2023 Towards Zero-Shot Persona Dialogue Generation with In-Context Learning ACL 2023 Training Trajectories of Language Models Across Scales ACL 2023 Transformers as Algorithms: Generalization and Stability in In-context Learning ICML 2023 Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection NeurIPS 2023 Transformers Learn In-Context by Gradient Descent ICML 2023 Transformers learn to implement preconditioned gradient descent for in-context learning NeurIPS 2023 Two Examples are Better than One: Context Regularization for Gradient-based Prompt Tuning ACL 2023 UL2: Unifying Language Learning Paradigms ICLR 2023 Understanding In-Context Learning via Supportive Pretraining Data ACL 2023 Unified Demonstration Retriever for In-Context Learning ACL 2023 Universal Self-Adaptive Prompting EMNLP 2023 Using In-Context Learning to Improve Dialogue Safety EMNLP 2023 Visual Programming: Compositional Visual Reasoning Without Training CVPR 2023