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In-Context Learning

Papers

Showing 20762100 of 2297 papers

TitleStatusHype
Inductive-bias Learning: Generating Code Models with Large Language ModelCode0
Exploring Demonstration Ensembling for In-context LearningCode0
Building Emotional Support Chatbots in the Era of LLMs0
RAVEN: In-Context Learning with Retrieval-Augmented Encoder-Decoder Language ModelsCode0
The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation EvaluationCode0
Large Language Model Prompt Chaining for Long Legal Document Classification0
FLIRT: Feedback Loop In-context Red Teaming0
Automated Distractor and Feedback Generation for Math Multiple-choice Questions via In-context LearningCode0
Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models0
Investigating the Learning Behaviour of In-context Learning: A Comparison with Supervised LearningCode0
Reasoning before Responding: Integrating Commonsense-based Causality Explanation for Empathetic Response Generation0
Exploiting the Potential of Seq2Seq Models as Robust Few-Shot Learners0
Metric-Based In-context Learning: A Case Study in Text SimplificationCode0
In-Context Learning Learns Label Relationships but Is Not Conventional LearningCode0
Controlling Equational Reasoning in Large Language Models with Prompt Interventions0
SINC: Self-Supervised In-Context Learning for Vision-Language Tasks0
Mega-TTS 2: Boosting Prompting Mechanisms for Zero-Shot Speech Synthesis0
The Power of Large Language Models for Wireless Communication System Development: A Case Study on FPGA Platforms0
Exploring the Integration of Large Language Models into Automatic Speech Recognition Systems: An Empirical Study0
AutoHint: Automatic Prompt Optimization with Hint GenerationCode0
Unsupervised Calibration through Prior Adaptation for Text Classification using Large Language ModelsCode0
Towards Understanding In-Context Learning with Contrastive Demonstrations and Saliency MapsCode0
Large Language Models as General Pattern Machines0
Assessing the efficacy of large language models in generating accurate teacher responses0
One Step of Gradient Descent is Provably the Optimal In-Context Learner with One Layer of Linear Self-Attention0
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