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In-Context Learning

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Showing 1776–1800 of 2297 papers

TitleStatusHype
From Style to Facts: Mapping the Boundaries of Knowledge Injection with Finetuning—0
From Summary to Action: Enhancing Large Language Models for Complex Tasks with Open World APIs—0
From Text to Emoji: How PEFT-Driven Personality Manipulation Unleashes the Emoji Potential in LLMs—0
From Words to Actions: Unveiling the Theoretical Underpinnings of LLM-Driven Autonomous Systems—0
GAMformer: In-Context Learning for Generalized Additive Models—0
Gated recurrent neural networks discover attention—0
Gating is Weighting: Understanding Gated Linear Attention through In-context Learning—0
GEC-RAG: Improving Generative Error Correction via Retrieval-Augmented Generation for Automatic Speech Recognition Systems—0
GeMQuAD : Generating Multilingual Question Answering Datasets from Large Language Models using Few Shot Learning—0
Gender-specific Machine Translation with Large Language Models—0
Generalization from Starvation: Hints of Universality in LLM Knowledge Graph Learning—0
Generalization to New Sequential Decision Making Tasks with In-Context Learning—0
Generating Diverse Training Samples for Relation Extraction with Large Language Models—0
Controlling Equational Reasoning in Large Language Models with Prompt Interventions—0
Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass—0
Generative AI as a Service in 6G Edge-Cloud: Generation Task Offloading by In-context Learning—0
Generative Model for Less-Resourced Language with 1 billion parameters—0
Generative Reliability-Based Design Optimization Using In-Context Learning Capabilities of Large Language Models—0
Generative Speech Recognition Error Correction with Large Language Models and Task-Activating Prompting—0
Geo-LLaVA: A Large Multi-Modal Model for Solving Geometry Math Problems with Meta In-Context Learning—0
GersteinLab at MEDIQA-Chat 2023: Clinical Note Summarization from Doctor-Patient Conversations through Fine-tuning and In-context Learning—0
GLaM: Efficient Scaling of Language Models with Mixture-of-Experts—0
GMC: A General Framework of Multi-stage Context Learning and Utilization for Visual Detection Tasks—0
Going Beyond Word Matching: Syntax Improves In-context Example Selection for Machine Translation—0
Good Examples Make A Faster Learner: Simple Demonstration-based Learning for Low-resource NER—0
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