SOTAVerified

In-Context Learning

Papers

Showing 451475 of 2297 papers

TitleStatusHype
ReLIC: A Recipe for 64k Steps of In-Context Reinforcement Learning for Embodied AICode1
Data-Efficient Operator Learning via Unsupervised Pretraining and In-Context LearningCode1
Exploring Diverse In-Context Configurations for Image CaptioningCode1
Data Whisperer: Efficient Data Selection for Task-Specific LLM Fine-Tuning via Few-Shot In-Context LearningCode1
EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language ModelsCode1
AICL: Action In-Context Learning for Video Diffusion ModelCode1
Benchmarking Cognitive Biases in Large Language Models as EvaluatorsCode1
Retrieval-enhanced Knowledge Editing in Language Models for Multi-Hop Question AnsweringCode1
Revisiting Out-of-distribution Robustness in NLP: Benchmark, Analysis, and LLMs EvaluationsCode1
ExDDV: A New Dataset for Explainable Deepfake Detection in VideoCode1
RuleRAG: Rule-guided retrieval-augmented generation with language models for question answeringCode1
A Closer Look at In-Context Learning under Distribution ShiftsCode1
Evolutionary Prompt Design for LLM-Based Post-ASR Error CorrectionCode1
LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language ModelsCode1
Are Human-generated Demonstrations Necessary for In-context Learning?Code1
Evolving Prompts In-Context: An Open-ended, Self-replicating PerspectiveCode1
Self-Adaptive In-Context Learning: An Information Compression Perspective for In-Context Example Selection and OrderingCode1
Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language ModelsCode1
Self-prompted Chain-of-Thought on Large Language Models for Open-domain Multi-hop ReasoningCode1
DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4Code1
Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language ModelsCode1
Eliciting In-Context Learning in Vision-Language Models for Videos Through Curated Data Distributional PropertiesCode1
BERTs are Generative In-Context LearnersCode1
Fool Your (Vision and) Language Model With Embarrassingly Simple PermutationsCode1
Bring Your Own KG: Self-Supervised Program Synthesis for Zero-Shot KGQACode1
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