Data-centric LLM training with dynamic sample selection, domain mixture optimization, and example reweighting inside the LLaMA-Factory training loop.

Official Repository of "LLM × DATA" Survey Paper

[ICML 2024] LESS: Selecting Influential Data for Targeted Instruction Tuning

DSIR large-scale data selection framework for language model training

A Survey on Data Selection for Language Models

🔥[VLDB'26] Official repository for the paper "LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning".

⛔ [DEPRECATED] Adapt Transformer-based language models to new text domains

Code for ACL 2025 Main paper "Data Whisperer: Efficient Data Selection for Task-Specific LLM Fine-Tuning via Few-Shot In-Context Learning".

InstructionGPT-4

[ACL 2025 main] SCAR: Data Selection via Style Consistency-Aware Response Ranking for Efficient Instruction-Tuning of Large Language Models

[ACL2025 Findings] Official code for MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space

arXiv 2024 | ZIP: entropy-law data selection for efficient LLM alignment.

[ICLR 2026] Skill-Targeted Adaptive Training

[ACL 2023] The code for our ACL'23 paper Cold-Start Data Selection for Few-shot Language Model Fine-tuning: A Prompt-Based Uncertainty Propagation Approach

[ACL'26 Main Conference] Instruction Data Selection via Answer Divergence

Implementation of TSDS: Data Selection for Task-Specific Model Finetuning. An optimal-transport framework for selecting domain-specific and task-specific training data to improve LLM finetuning and instruction tuning.

This is an official repository for "Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources" (NeurIPS 2023).

[COLM 2026] Official implementation for "GradAlign: Gradient-Aligned Data Selection for LLM Reinforcement Learning"

Enhancing Efficiency in Multidevice Federated Learning through Data Selection

Dynamic Transfer Learning for Low-Resource Neural Machine Translation