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In-Context Learning

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Showing 651–675 of 2297 papers

TitleStatusHype
Unsupervised Prompting for Graph Neural Networks—0
IRONIC: Coherence-Aware Reasoning Chains for Multi-Modal Sarcasm DetectionCode0
Any Large Language Model Can Be a Reliable Judge: Debiasing with a Reasoning-based Bias Detector—0
Meta-Learning an In-Context Transformer Model of Human Higher Visual Cortex—0
Large Language Models as Computable Approximations to Solomonoff Induction—0
Agentic Feature Augmentation: Unifying Selection and Generation with Teaming, Planning, and Memories—0
Bridging Sign and Spoken Languages: Pseudo Gloss Generation for Sign Language Translation—0
Adversarially Pretrained Transformers may be Universally Robust In-Context LearnersCode0
Mechanistic Fine-tuning for In-context Learning—0
In-Context Learning Boosts Speech Recognition via Human-like Adaptation to Speakers and Language Varieties—0
Out-of-Distribution Generalization of In-Context Learning: A Low-Dimensional Subspace Perspective—0
Reinforcing Question Answering Agents with Minimalist Policy Gradient Optimization—0
EmoGist: Efficient In-Context Learning for Visual Emotion Understanding—0
QA-prompting: Improving Summarization with Large Language Models using Question-AnsweringCode0
DSMentor: Enhancing Data Science Agents with Curriculum Learning and Online Knowledge Accumulation—0
FinePhys: Fine-grained Human Action Generation by Explicitly Incorporating Physical Laws for Effective Skeletal Guidance—0
AutoMathKG: The automated mathematical knowledge graph based on LLM and vector database—0
CIE: Controlling Language Model Text Generations Using Continuous SignalsCode0
Causal Head Gating: A Framework for Interpreting Roles of Attention Heads in Transformers—0
Improving LLM Outputs Against Jailbreak Attacks with Expert Model Integration—0
Bridging Generative and Discriminative Learning: Few-Shot Relation Extraction via Two-Stage Knowledge-Guided Pre-trainingCode0
Transformer learns the cross-task prior and regularization for in-context learning—0
Induction Head Toxicity Mechanistically Explains Repetition Curse in Large Language Models—0
Transformers as Unsupervised Learning Algorithms: A study on Gaussian MixturesCode0
Do different prompting methods yield a common task representation in language models?—0
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