Cover Image

GRaSp: Automatic Example Optimization for In-Context Learning in Low-Data Tasks

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bihaug-Frøyland, Simen, Brådland, Henrik
Format:	Preprint
Published:	2026
Subjects:	Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Knowledge-Informed Automatic Feature Extraction via Collaborative Large Language Model Agents
by: Bradland, Henrik, et al.
Published: (2025)

A New HOPE: Domain-agnostic Automatic Evaluation of Text Chunking
by: Brådland, Henrik, et al.
Published: (2025)

BoRA: Bayesian Hierarchical Low-Rank Adaption for Multi-Task Large Language Models
by: Eide, Simen, et al.
Published: (2024)

NICE: To Optimize In-Context Examples or Not?
by: Srivastava, Pragya, et al.
Published: (2024)

Not All Demonstration Examples are Equally Beneficial: Reweighting Demonstration Examples for In-Context Learning
by: Yang, Zhe, et al.
Published: (2023)

Effective In-Context Example Selection through Data Compression
by: Sun, Zhongxiang, et al.
Published: (2024)

Learning to Search Effective Example Sequences for In-Context Learning
by: Gao, Xiang, et al.
Published: (2025)

CLaSp: In-Context Layer Skip for Self-Speculative Decoding
by: Chen, Longze, et al.
Published: (2025)

XAMPLER: Learning to Retrieve Cross-Lingual In-Context Examples
by: Lin, Peiqin, et al.
Published: (2024)

$Se^2$: Sequential Example Selection for In-Context Learning
by: Liu, Haoyu, et al.
Published: (2024)

Augmenting In-Context-Learning in LLMs via Automatic Data Labeling and Refinement
by: Shtok, Joseph, et al.
Published: (2024)

In-Context Example Selection via Similarity Search Improves Low-Resource Machine Translation
by: Zebaze, Armel, et al.
Published: (2024)

Learning Metadata-Agnostic Representations for Text-to-SQL In-Context Example Selection
by: Mai, Chuhong, et al.
Published: (2024)

Self-Generated In-Context Examples Improve LLM Agents for Sequential Decision-Making Tasks
by: Sarukkai, Vishnu, et al.
Published: (2025)

PLR: Plackett-Luce for Reordering In-Context Learning Examples
by: Batorski, Pawel, et al.
Published: (2026)

Learning to Retrieve In-Context Examples for Large Language Models
by: Wang, Liang, et al.
Published: (2023)

Multi-Task Learning with LLMs for Implicit Sentiment Analysis: Data-level and Task-level Automatic Weight Learning
by: Lai, Wenna, et al.
Published: (2024)

Monte Carlo Sampling for Analyzing In-Context Examples
by: Schoch, Stephanie, et al.
Published: (2025)

In-Context Example Ordering Guided by Label Distributions
by: Xu, Zhichao, et al.
Published: (2024)

GistScore: Learning Better Representations for In-Context Example Selection with Gist Bottlenecks
by: Gupta, Shivanshu, et al.
Published: (2023)

Improving Sentence Embeddings with Automatic Generation of Training Data Using Few-shot Examples
by: Sato, Soma, et al.
Published: (2024)

Task-Oriented Dialogue with In-Context Learning
by: Bocklisch, Tom, et al.
Published: (2024)

RICo: Refined In-Context Contribution for Automatic Instruction-Tuning Data Selection
by: Yang, Yixin, et al.
Published: (2025)

OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples
by: Koike, Ryuto, et al.
Published: (2023)

Beyond Examples: High-level Automated Reasoning Paradigm in In-Context Learning via MCTS
by: Wu, Jinyang, et al.
Published: (2024)

An Automatic Prompt Generation System for Tabular Data Tasks
by: Akella, Ashlesha, et al.
Published: (2024)

SMILE: Speech Meta In-Context Learning for Low-Resource Language Automatic Speech Recognition
by: Hsu, Ming-Hao, et al.
Published: (2024)

Localizing Task Recognition and Task Learning in In-Context Learning via Attention Head Analysis
by: Yang, Haolin, et al.
Published: (2025)

SAFE-SQL: Self-Augmented In-Context Learning with Fine-grained Example Selection for Text-to-SQL
by: Lee, Jimin, et al.
Published: (2025)

PACIT: Unlocking the Power of Examples for Better In-Context Instruction Tuning
by: Xue, Tianci, et al.
Published: (2023)

OptiSeq: Ordering Examples On-The-Fly for In-Context Learning
by: Bhope, Rahul Atul, et al.
Published: (2025)

From Unstructured Data to In-Context Learning: Exploring What Tasks Can Be Learned and When
by: Wibisono, Kevin Christian, et al.
Published: (2024)

RetICL: Sequential Retrieval of In-Context Examples with Reinforcement Learning
by: Scarlatos, Alexander, et al.
Published: (2023)

RISCORE: Enhancing In-Context Riddle Solving in Language Models through Context-Reconstructed Example Augmentation
by: Panagiotopoulos, Ioannis, et al.
Published: (2024)

One size doesn't fit all: Predicting the Number of Examples for In-Context Learning
by: Chandra, Manish, et al.
Published: (2024)

Demonstration Notebook: Finding the Most Suited In-Context Learning Example from Interactions
by: Tang, Yiming, et al.
Published: (2024)

Data Whisperer: Efficient Data Selection for Task-Specific LLM Fine-Tuning via Few-Shot In-Context Learning
by: Wang, Shaobo, et al.
Published: (2025)

Learning New Tasks from a Few Examples with Soft-Label Prototypes
by: Singh, Avyav Kumar, et al.
Published: (2022)

Automatically Generating Numerous Context-Driven SFT Data for LLMs across Diverse Granularity
by: Quan, Shanghaoran
Published: (2024)

Label Words as Local Task Vectors in In-Context Learning
by: Zheng, Bowen, et al.
Published: (2024)