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In-Context Learning

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Showing 1726–1750 of 2297 papers

TitleStatusHype
Studying LLM Performance on Closed- and Open-source Data—0
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?—0
In-Context Learning of a Linear Transformer Block: Benefits of the MLP Component and One-Step GD Initialization—0
A Simple Framework Uniting Visual In-context Learning with Masked Image Modeling to Improve Ultrasound SegmentationCode0
Is ChatGPT the Future of Causal Text Mining? A Comprehensive Evaluation and Analysis—0
Unsupervised Text Style Transfer via LLMs and Attention Masking with Multi-way Interactions—0
CAMELoT: Towards Large Language Models with Training-Free Consolidated Associative Memory—0
Se^2: Sequential Example Selection for In-Context Learning—0
Unlocking Instructive In-Context Learning with Tabular Prompting for Relational Triple Extraction—0
The Impact of Demonstrations on Multilingual In-Context Learning: A Multidimensional AnalysisCode0
Harnessing Large Language Models as Post-hoc CorrectorsCode0
Identifying Semantic Induction Heads to Understand In-Context Learning—0
On Sensitivity of Learning with Limited Labelled Data to the Effects of Randomness: Impact of Interactions and Systematic ChoicesCode0
Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even PerformanceCode0
Self-AMPLIFY: Improving Small Language Models with Self Post Hoc Explanations—0
Enabling Weak LLMs to Judge Response Reliability via Meta Ranking—0
Standardize: Aligning Language Models with Expert-Defined Standards for Content GenerationCode0
Parallel Structures in Pre-training Data Yield In-Context LearningCode0
Do Large Language Models Understand Logic or Just Mimick Context?—0
Modularized Networks for Few-shot Hateful Meme DetectionCode0
In-Context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness—0
GNNavi: Navigating the Information Flow in Large Language Models by Graph Neural NetworkCode0
Visual In-Context Learning for Large Vision-Language Models—0
In-Context Example Ordering Guided by Label Distributions—0
C-ICL: Contrastive In-context Learning for Information Extraction—0
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