data selection
The process of choosing specific data samples for training or evaluation, often based on criteria such as representativeness, diversity, or relevance to ensure effective learning.
- A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings
- AI Progress Should Be Measured by Capability-Per-Resource, Not Scale Alone: A Framework for Gradient-Guided Resource Allocation in LLMs
- Beyond the Surface: Enhancing LLM-as-a-Judge Alignment with Human via Internal Representations
- Computational Budget Should Be Considered in Data Selection
- Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data
- Group-Level Data Selection for Efficient Pretraining
- Less is More: Improving LLM Alignment via Preference Data Selection
- Task-Specific Data Selection for Instruction Tuning via Monosemantic Neuronal Activations
- Understanding Data Influence in Reinforcement Finetuning
- Vision Function Layer in Multimodal LLMs