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In-Context Learning

Papers

Showing 10261050 of 2297 papers

TitleStatusHype
DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking TaskCode0
Finding Transformer Circuits with Edge PruningCode2
Token-based Decision Criteria Are Suboptimal in In-context LearningCode0
Distributed Rule Vectors is A Key Mechanism in Large Language Models' In-Context Learning0
Uncovering Hidden Intentions: Exploring Prompt Recovery for Deeper Insights into Generated Texts0
Shortcomings of LLMs for Low-Resource Translation: Retrieval and Understanding are Both the Problem0
Automated radiotherapy treatment planning guided by GPT-4Vision0
ICLEval: Evaluating In-Context Learning Ability of Large Language ModelsCode1
Multimodal Task Vectors Enable Many-Shot Multimodal In-Context LearningCode1
VLM Agents Generate Their Own Memories: Distilling Experience into Embodied Programs of Thought0
Learning to Retrieve Iteratively for In-Context Learning0
Can LLMs Learn by Teaching for Better Reasoning? A Preliminary StudyCode2
Improving Expert Radiology Report Summarization by Prompting Large Language Models with a Layperson Summary0
Data-Centric AI in the Age of Large Language Models0
Investigating the Pre-Training Dynamics of In-Context Learning: Task Recognition vs. Task LearningCode0
SeCoKD: Aligning Large Language Models for In-Context Learning with Fewer Shots0
Connecting the Dots: LLMs can Infer and Verbalize Latent Structure from Disparate Training DataCode1
When Parts Are Greater Than Sums: Individual LLM Components Can Outperform Full ModelsCode0
Learning to Generate Answers with Citations via Factual Consistency ModelsCode1
In-Context Learning on a Budget: A Case Study in Token Classification0
LIVE: Learnable In-Context Vector for Visual Question AnsweringCode1
In-Context In-Context Learning with Transformer Neural Processes0
ZeroDL: Zero-shot Distribution Learning for Text Clustering via Large Language Models0
Enhancing Collaborative Semantics of Language Model-Driven Recommendations via Graph-Aware Learning0
Can Few-shot Work in Long-Context? Recycling the Context to Generate Demonstrations0
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