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In-Context Learning

419 directly classified papers

Papers per year

Papers

Prompt Optimization via Adversarial In-Context Learning ACL 2024
Think Twice: Perspective-Taking Improves Large Language Models’ Theory-of-Mind Capabilities ACL 2024
Language Models can Exploit Cross-Task In-context Learning for Data-Scarce Novel Tasks ACL 2024
LLMs Learn Task Heuristics from Demonstrations: A Heuristic-Driven Prompting Strategy for Document-Level Event Argument Extraction ACL 2024
What Do Language Models Learn in Context? The Structured Task Hypothesis. ACL 2024
Question-Analysis Prompting Improves LLM Performance in Reasoning Tasks ACL 2024
Identifying Semantic Induction Heads to Understand In-Context Learning ACL 2024
The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional Analysis ACL 2024
An Empirical Study of In-context Learning in LLMs for Machine Translation ACL 2024
LSTPrompt: Large Language Models as Zero-Shot Time Series Forecasters by Long-Short-Term Prompting ACL 2024
LLMCrit: Teaching Large Language Models to Use Criteria ACL 2024
Teaching Large Language Models an Unseen Language on the Fly ACL 2024
Unveiling In-Context Learning: A Coordinate System to Understand Its Working Mechanism EMNLP 2024
Retrieval-Augmented Code Generation for Situated Action Generation: A Case Study on Minecraft EMNLP 2024
Learning to Retrieve Iteratively for In-Context Learning EMNLP 2024
SCOI: Syntax-augmented Coverage-based In-context Example Selection for Machine Translation EMNLP 2024
Atomic Inference for NLI with Generated Facts as Atoms EMNLP 2024
PrExMe! Large Scale Prompt Exploration of Open Source LLMs for Machine Translation and Summarization Evaluation EMNLP 2024
LLMs learn governing principles of dynamical systems, revealing an in-context neural scaling law EMNLP 2024
Demonstration Selection Strategies for Numerical Time Series Data-to-Text EMNLP 2024
Generative Multimodal Models are In-Context Learners CVPR 2024
Policy-shaped prediction: avoiding distractions in model-based reinforcement learning NIPS 2024
The Representation Landscape of Few-Shot Learning and Fine-Tuning in Large Language Models NIPS 2024
DETAIL: Task DEmonsTration Attribution for Interpretable In-context Learning NIPS 2024
RoleAgent: Building, Interacting, and Benchmarking High-quality Role-Playing Agents from Scripts NIPS 2024