YiDing Jiang
14 papers · 2019–2025 · 3 venues · across top CS/AI venues
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Achievements
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π Academic Marathon Β· Sprint π£ Hot Topic Early Bird π Interdisciplinary Bridge Β· Bronze π Conference Polyglot Β· Bronze πΊοΈ Taxonomy Completionist (38)
π§
Keyword Pioneer
π
Trend Setter
π
Century Club Β· Bronze
ποΈ
Keyword Collector
(80)
Venues
Top co-authors
Research topics
Machine Learning
(11)
Deep Learning
(7)
Core Methods
(6)
Optimization & Theory Β· Machine Learning
(6)
Artificial Intelligence
(5)
Learning Types Β· Deep Learning
(5)
Learning Types Β· Machine Learning
(5)
Reinforcement Learning
(4)
Core AI
(4)
Methods
(4)
Application Areas
(2)
Architectures
(2)
Optimization & Theory Β· Deep Learning
(2)
Learning Paradigms
(1)
Models
(1)
Keywords
representation learning
(3)
generalization error
(2)
implicit neural representation
(2)
reinforcement learning
(2)
neural network
(2)
multi-task learning
(2)
few-shot learning
(1)
epistemic uncertainty
(1)
feature learning
(1)
curriculum learning
(1)
deep learning
(1)
model calibration
(1)
attention mechanism
(1)
prompt engineering
(1)
ensemble learning
(1)
permutation equivariance
(1)
instruction following
(1)
online learning
(1)
model architecture
(1)
prompt-based learning
(1)
Papers
Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws
ICLR 2025
Training a Generally Curious Agent
ICML 2025
On the Joint Interaction of Models, Data, and Features
ICLR 2024
Understanding prompt engineering may not require rethinking generalization
ICLR 2024
Language Models are Weak Learners
NeurIPS 2023
Neural Functional Transformers
NeurIPS 2023
On the Importance of Exploration for Generalization in Reinforcement Learning
NeurIPS 2023
Permutation Equivariant Neural Functionals
NeurIPS 2023
Agreement-on-the-line: Predicting the Performance of Neural Networks under Distribution Shift
NeurIPS 2022
Assessing Generalization of SGD via Disagreement
ICLR 2022
Learning Options via Compression
NeurIPS 2022
Observational Overfitting in Reinforcement Learning
ICLR 2020
Language as an Abstraction for Hierarchical Deep Reinforcement Learning
NeurIPS 2019
Predicting the Generalization Gap in Deep Networks with Margin Distributions
ICLR 2019