data-pruning

pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation

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

Data-efficient Fine-tuning for LLM-based Recommendation (SIGIR'24)

Learning Large-scale Neural Fields via Context Pruned Meta-Learning (NeurIPS 2023)

Jaehyung Kim et al's ACL 2023 paper on "infoVerse: A Universal Framework for Dataset Characterization with Multidimensional Meta-information"

Official repository of the paper "DiffProb: Data Pruning for Face Recognition" (accepted at FG 2025)

DataCull is a modular, light-weight data pruning library containing many dataset pruning (coreset selection) algorithm including the official Implementation of the paper, titled, RCAP: Robust, Class-Aware, Probab ilistic Dynamic Dataset Pruning

🌿 dPrune: A Framework for Data Pruning

code for the paper Beyond Neural scaling laws for fast proven robust certification of nearest prototype classifiers

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