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In-Context Learning

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TitleStatusHype
Towards Making the Most of ChatGPT for Machine TranslationCode1
Fairness-guided Few-shot Prompting for Large Language Models—0
DeID-GPT: Zero-shot Medical Text De-Identification by GPT-4Code1
eP-ALM: Efficient Perceptual Augmentation of Language ModelsCode1
The Scope of In-Context Learning for the Extraction of Medical Temporal Constraints—0
A Theory of Emergent In-Context Learning as Implicit Structure Induction—0
How Many Demonstrations Do You Need for In-context Learning?—0
The Learnability of In-Context Learning—0
ICL-D3IE: In-Context Learning with Diverse Demonstrations Updating for Document Information ExtractionCode1
MenuCraft: Interactive Menu System Design with Large Language ModelsCode0
Larger language models do in-context learning differently—0
Speak Foreign Languages with Your Own Voice: Cross-Lingual Neural Codec Language ModelingCode5
OpenICL: An Open-Source Framework for In-context LearningCode2
Finding Support Examples for In-Context Learning—0
ProofNet: Autoformalizing and Formally Proving Undergraduate-Level MathematicsCode1
Language Model Crossover: Variation through Few-Shot PromptingCode2
How Does In-Context Learning Help Prompt Tuning?—0
In-context Example Selection with InfluencesCode1
Few-shot Multimodal Multitask Multilingual Learning—0
Conversation Style Transfer using Few-Shot Learning—0
Do We Still Need Clinical Language Models?Code0
ScatterShot: Interactive In-context Example Curation for Text TransformationCode0
Distinguishability Calibration to In-Context LearningCode0
Stabilized In-Context Learning with Pre-trained Language Models for Few Shot Dialogue State Tracking—0
Compositional Exemplars for In-context LearningCode1
Context Understanding in Computer Vision: A Survey—0
In-Context Learning with Many Demonstration ExamplesCode1
Controlling Personality Style in Dialogue with Zero-Shot Prompt-Based Learning—0
CrossCodeBench: Benchmarking Cross-Task Generalization of Source Code Models—0
Towards Few-Shot Identification of Morality Frames using In-Context Learning—0
Using In-Context Learning to Improve Dialogue Safety—0
Collaborating with language models for embodied reasoning—0
What Makes Good Examples for Visual In-Context Learning?Code1
Grounding Language Models to Images for Multimodal Inputs and OutputsCode2
Adaptive Machine Translation with Large Language ModelsCode1
Looped Transformers as Programmable ComputersCode0
Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context LearningCode1
Batch Prompting: Efficient Inference with Large Language Model APIsCode1
Human-Timescale Adaptation in an Open-Ended Task Space—0
Transformers as Algorithms: Generalization and Stability in In-context LearningCode0
Neural Codec Language Models are Zero-Shot Text to Speech SynthesizersCode7
SegGPT: Towards Segmenting Everything in Context—0
A Survey on In-context LearningCode2
Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLPCode7
Parallel Context Windows for Large Language ModelsCode1
Prompt-Augmented Linear Probing: Scaling beyond the Limit of Few-shot In-Context Learners—0
In-context Learning Distillation: Transferring Few-shot Learning Ability of Pre-trained Language Models—0
Ontologically Faithful Generation of Non-Player Character Dialogues—0
Why Can GPT Learn In-Context? Language Models Implicitly Perform Gradient Descent as Meta-Optimizers—0
Data Curation Alone Can Stabilize In-context LearningCode1
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