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In-Context Learning

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Showing 2101–2150 of 2297 papers

TitleStatusHype
Meta-Adaptive Prompt Distillation for Few-Shot Visual Question Answering—0
MetaICL: Learning to Learn In Context—0
Meta In-Context Learning Makes Large Language Models Better Zero and Few-Shot Relation Extractors—0
Meta-Learning an In-Context Transformer Model of Human Higher Visual Cortex—0
Meta-Learning Transformers to Improve In-Context Generalization—0
Meta-learning via Language Model In-context Tuning—0
Enabling Weak LLMs to Judge Response Reliability via Meta Ranking—0
Meta Reasoning for Large Language Models—0
MetaVL: Transferring In-Context Learning Ability From Language Models to Vision-Language Models—0
SMILE: Speech Meta In-Context Learning for Low-Resource Language Automatic Speech Recognition—0
MIBench: Evaluating Multimodal Large Language Models over Multiple Images—0
MICAS: Multi-grained In-Context Adaptive Sampling for 3D Point Cloud Processing—0
Mimicking or Reasoning: Rethinking Multi-Modal In-Context Learning in Vision-Language Models—0
MindAgent: Emergent Gaming Interaction—0
Mind the instructions: a holistic evaluation of consistency and interactions in prompt-based learning—0
Minimization of Boolean Complexity in In-Context Concept Learning—0
Mining Reasons For And Against Vaccination From Unstructured Data Using Nichesourcing and AI Data Augmentation—0
MIR-Bench: Can Your LLM Recognize Complicated Patterns via Many-Shot In-Context Reasoning?—0
Misconfidence-based Demonstration Selection for LLM In-Context Learning—0
Mitigating Copy Bias in In-Context Learning through Neuron Pruning—0
Mitigating Cross-Modal Distraction and Ensuring Geometric Feasibility via Affordance-Guided, Self-Consistent MLLMs for Food Preparation Task Planning—0
Mitigating Many-Shot Jailbreaking—0
Mixture of In-Context Prompters for Tabular PFNs—0
Mixtures of In-Context Learners—0
MiZero: The Shadowy Defender Against Text Style Infringements—0
MM1: Methods, Analysis & Insights from Multimodal LLM Pre-training—0
MMHQA-ICL: Multimodal In-context Learning for Hybrid Question Answering over Text, Tables and Images—0
MM-Narrator: Narrating Long-form Videos with Multimodal In-Context Learning—0
MMRAG: Multi-Mode Retrieval-Augmented Generation with Large Language Models for Biomedical In-Context Learning—0
MoConVQ: Unified Physics-Based Motion Control via Scalable Discrete Representations—0
MOKA: Open-World Robotic Manipulation through Mark-Based Visual Prompting—0
Monocle: Hybrid Local-Global In-Context Evaluation for Long-Text Generation with Uncertainty-Based Active Learning—0
Monte Carlo Sampling for Analyzing In-Context Examples—0
More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives—0
More Samples or More Prompts? Exploring Effective In-Context Sampling for LLM Few-Shot Prompt Engineering—0
mOSCAR: A Large-scale Multilingual and Multimodal Document-level Corpus—0
Multi-Layer Ranking with Large Language Models for News Source Recommendation—0
Multilingual Few-Shot Learning via Language Model Retrieval—0
Multilingual Fine-Grained News Headline Hallucination Detection—0
Multimodal Contrastive In-Context Learning—0
MULTI: Multimodal Understanding Leaderboard with Text and Images—0
Multi-Step Dialogue Workflow Action Prediction—0
MuVi: Video-to-Music Generation with Semantic Alignment and Rhythmic Synchronization—0
N2C2: Nearest Neighbor Enhanced Confidence Calibration for Cross-Lingual In-Context Learning—0
Narrowing the Gap between Zero- and Few-shot Machine Translation by Matching Styles—0
Navigating the Dual Facets: A Comprehensive Evaluation of Sequential Memory Editing in Large Language Models—0
Navigating the Labyrinth: Evaluating and Enhancing LLMs' Ability to Reason About Search Problems—0
Neither Stochastic Parroting nor AGI: LLMs Solve Tasks through Context-Directed Extrapolation from Training Data Priors—0
Neural Machine Translation Models Can Learn to be Few-shot Learners—0
Neural Network Reprogrammability: A Unified Theme on Model Reprogramming, Prompt Tuning, and Prompt Instruction—0
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