← Authors

Chih-Kuan Yeh

16 papers · 2018–2025 · 8 conferences · across top CS/AI conferences

Achievements

🌈 Renaissance Researcher (5) πŸ—ΊοΈ Taxonomy Completionist (27) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (14) 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (7) πŸŒ‰ Interdisciplinary Bridge πŸ† Keyword Champion 🧬 Topic Evolution πŸ—ƒοΈ Keyword Collector (53) πŸš€ Conference Pioneer πŸ’Ž Century Club (16) πŸ”₯ Unstoppable (6) ⚑ Prolific Year (5)

Conferences

NIPS (6) ICLR (4) ACL (1) AISTATS (1) CVPR (1) ECCV (1) JMLR (1) NAACL (1)

Top co-authors

Pradeep K Ravikumar (5) Cheng-Yu Hsieh (3) Pradeep K. Ravikumar (3) Cho-jui Hsieh (3) Pradeep Ravikumar (3) Tomas Pfister (2) Ankur Taly (2) Pradeep Kumar Ravikumar (2) Frederick Liu (2) Che-Ping Tsai (2)

Keywords

feature attribution (2) neural network (2) shapley value (2) feature importance (2) influence function (2) multi-task learning (2) few-shot learning (1) adversarial robustness (1) continual learning (1) rationale extraction (1) explainable ai (1) visual reasoning (1) knowledge graph (1) neural machine translation (1) value function (1) knowledge distillation (1) model interpretability (1) perturbation analysis (1) computational efficiency (1) concept-based explanation (1)

Papers

An Efficient Rehearsal Scheme for Catastrophic Forgetting Mitigation during Multi-stage Fine-tuning NAACL 2025
Faith-Shap: The Faithful Shapley Interaction Index JMLR 2023
Concept Gradient: Concept-based Interpretation Without Linear Assumption ICLR 2023
Sample based Explanations via Generalized Representers NIPS 2023
Order Matters in the Presence of Dataset Imbalance for Multilingual Learning NIPS 2023
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes ACL 2023
Threading the Needle of On and Off-Manifold Value Functions for Shapley Explanations AISTATS 2022
First is Better Than Last for Language Data Influence NIPS 2022
Evaluations and Methods for Explanation through Robustness Analysis ICLR 2021
On Completeness-aware Concept-Based Explanations in Deep Neural Networks NIPS 2020
Minimizing FLOPs to Learn Efficient Sparse Representations ICLR 2020
Unsupervised Speech Recognition via Segmental Empirical Output Distribution Matching ICLR 2019
On the (In)fidelity and Sensitivity of Explanations NIPS 2019
Multi-Label Zero-Shot Learning With Structured Knowledge Graphs CVPR 2018
Representer Point Selection for Explaining Deep Neural Networks NIPS 2018
Deep Generative Models for Weakly-Supervised Multi-Label Classification ECCV 2018