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In-Context Learning

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Showing 601–625 of 2297 papers

TitleStatusHype
When can in-context learning generalize out of task distribution?—0
Using In-Context Learning for Automatic Defect Labelling of Display Manufacturing Data—0
Are LLMs Reliable Translators of Logical Reasoning Across Lexically Diversified Contexts?Code0
Delta-KNN: Improving Demonstration Selection in In-Context Learning for Alzheimer's Disease Detection—0
BEAR: BGP Event Analysis and ReportingCode0
Relational reasoning and inductive bias in transformers trained on a transitive inference task—0
Does Prompt Design Impact Quality of Data Imputation by LLMs?—0
Large Language Models Can Achieve Explainable and Training-Free One-shot HRRP ATR—0
Adaptive Task Vectors for Large Language Models—0
On the Robustness of Tabular Foundation Models: Test-Time Attacks and In-Context Defenses—0
Retrieval-Augmented Generation as Noisy In-Context Learning: A Unified Theory and Risk Bounds—0
Probing the Geometry of Truth: Consistency and Generalization of Truth Directions in LLMs Across Logical Transformations and Question Answering TasksCode0
Enhancing Speech Instruction Understanding and Disambiguation in Robotics via Speech Prosody—0
A Large Language Model-Supported Threat Modeling Framework for Transportation Cyber-Physical Systems—0
Towards Predicting Any Human Trajectory In Context—0
G2S: A General-to-Specific Learning Framework for Temporal Knowledge Graph Forecasting with Large Language ModelsCode0
CodeSense: a Real-World Benchmark and Dataset for Code Semantic Reasoning—0
ArtiScene: Language-Driven Artistic 3D Scene Generation Through Image Intermediary—0
Discl-VC: Disentangled Discrete Tokens and In-Context Learning for Controllable Zero-Shot Voice Conversion—0
CrossICL: Cross-Task In-Context Learning via Unsupervised Demonstration Transfer—0
Transformers Are Universally Consistent—0
From Parameters to Prompts: Understanding and Mitigating the Factuality Gap between Fine-Tuned LLMs—0
LLM Agents for Bargaining with Utility-based Feedback—0
Generating Diverse Training Samples for Relation Extraction with Large Language Models—0
Neither Stochastic Parroting nor AGI: LLMs Solve Tasks through Context-Directed Extrapolation from Training Data Priors—0
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