SOTAVerified

In-Context Learning

Papers

Showing 501525 of 2297 papers

TitleStatusHype
Unified Demonstration Retriever for In-Context LearningCode1
Why So Gullible? Enhancing the Robustness of Retrieval-Augmented Models against Counterfactual NoiseCode1
ARC: A Generalist Graph Anomaly Detector with In-Context LearningCode1
Unmasking Trees for Tabular DataCode1
Unveiling In-Context Learning: A Coordinate System to Understand Its Working MechanismCode1
Unveiling the Generalization Power of Fine-Tuned Large Language ModelsCode1
AppBench: Planning of Multiple APIs from Various APPs for Complex User InstructionCode1
VICON: Vision In-Context Operator Networks for Multi-Physics Fluid Dynamics PredictionCode1
Exploring Multimodal Challenges in Toxic Chinese Detection: Taxonomy, Benchmark, and FindingsCode1
Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and EvaluationCode1
ExDDV: A New Dataset for Explainable Deepfake Detection in VideoCode1
Explainable Claim Verification via Knowledge-Grounded Reasoning with Large Language ModelsCode1
Evolutionary Prompt Design for LLM-Based Post-ASR Error CorrectionCode1
Does GPT-3 Generate Empathetic Dialogues? A Novel In-Context Example Selection Method and Automatic Evaluation Metric for Empathetic Dialogue GenerationCode1
Evaluating Knowledge Generation and Self-Refinement Strategies for LLM-based Column Type AnnotationCode1
Evolving Prompts In-Context: An Open-ended, Self-replicating PerspectiveCode1
Explore In-Context Learning for 3D Point Cloud UnderstandingCode1
Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical StudyCode1
Entropy-Regularized Token-Level Policy Optimization for Language Agent ReinforcementCode1
Improving Planning with Large Language Models: A Modular Agentic ArchitectureCode1
BoostStep: Boosting mathematical capability of Large Language Models via improved single-step reasoningCode1
Evaluating Named Entity Recognition Using Few-Shot Prompting with Large Language ModelsCode1
ArabLegalEval: A Multitask Benchmark for Assessing Arabic Legal Knowledge in Large Language ModelsCode1
Ensemble-Instruct: Generating Instruction-Tuning Data with a Heterogeneous Mixture of LMsCode1
eP-ALM: Efficient Perceptual Augmentation of Language ModelsCode1
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