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In-Context Learning

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Showing 1751–1775 of 2297 papers

TitleStatusHype
PhaseEvo: Towards Unified In-Context Prompt Optimization for Large Language Models—0
Navigating the Dual Facets: A Comprehensive Evaluation of Sequential Memory Editing in Large Language Models—0
Measuring and Reducing LLM Hallucination without Gold-Standard Answers—0
LinkNER: Linking Local Named Entity Recognition Models to Large Language Models using UncertaintyCode0
Understanding In-Context Learning with a Pelican Soup Framework—0
Improving Demonstration Diversity by Human-Free Fusing for Text-to-SQLCode0
The Evolution of Statistical Induction Heads: In-Context Learning Markov Chains—0
Crafting a Good Prompt or Providing Exemplary Dialogues? A Study of In-Context Learning for Persona-based Dialogue Generation—0
Self-Augmented In-Context Learning for Unsupervised Word TranslationCode0
Chain-of-Planned-Behaviour Workflow Elicits Few-Shot Mobility Generation in LLMs—0
Prompt-Based Bias Calibration for Better Zero/Few-Shot Learning of Language Models—0
Bridging Associative Memory and Probabilistic Modeling—0
HGOT: Hierarchical Graph of Thoughts for Retrieval-Augmented In-Context Learning in Factuality EvaluationCode0
GrounDial: Human-norm Grounded Safe Dialog Response Generation—0
Large Language Model-Based Interpretable Machine Learning Control in Building Energy Systems—0
The dynamic interplay between in-context and in-weight learning in humans and neural networksCode0
Universal Link Predictor By In-Context Learning on Graphs—0
VisLingInstruct: Elevating Zero-Shot Learning in Multi-Modal Language Models with Autonomous Instruction OptimizationCode0
Text-centric Alignment for Multi-Modality Learning—0
Assessing Generalization for Subpopulation Representative Modeling via In-Context Learning—0
Step-On-Feet Tuning: Scaling Self-Alignment of LLMs via Bootstrapping—0
In-Context Data Distillation with TabPFN—0
On the Out-Of-Distribution Generalization of Multimodal Large Language Models—0
NICE: To Optimize In-Context Examples or Not?Code0
In-Context Learning Can Re-learn Forbidden Tasks—0
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