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In-Context Learning

436 papers

Papers per year

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Papers

Think Twice: Perspective-Taking Improves Large Language Models’ Theory-of-Mind Capabilities ACL 2024
Revisiting Demonstration Selection Strategies in In-Context Learning 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
In-Context Symbolic Regression: Leveraging Large Language Models for Function Discovery ACL 2024
Improving In-Context Learning with Prediction Feedback for Sentiment Analysis 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
RECOST: External Knowledge Guided Data-efficient Instruction Tuning ACL 2024
Zero-shot Scientific Claim Verification Using LLMs and Citation Text ACL 2024
ZZU-NLP at SIGHAN-2024 dimABSA Task: Aspect-Based Sentiment Analysis with Coarse-to-Fine In-context Learning ACL 2024
DS-Group at SIGHAN-2024 dimABSA Task: Constructing In-context Learning Structure for Dimensional Aspect-Based Sentiment Analysis ACL 2024
Subjectivity Detection in English News using Large Language Models ACL 2024
Enhancing In-context Learning via Linear Probe Calibration AISTATS 2024
Improving Recall of Large Language Models: A Model Collaboration Approach for Relational Triple Extraction COLING 2024
Locally Differentially Private In-Context Learning COLING 2024
MemoryPrompt: A Light Wrapper to Improve Context Tracking in Pre-trained Language Models COLING 2024
Generative Multimodal Models are In-Context Learners CVPR 2024
In-Context Matting CVPR 2024