Jiantao Jiao
31 papers · 2018–2025 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (64) π Conference Polyglot Β· Silver π Academic Marathon Β· Sprint π Interdisciplinary Bridge Β· Silver π£ Hot Topic Early Bird
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Research topics
Machine Learning
(28)
Optimization & Theory
(18)
Artificial Intelligence
(15)
Core AI
(11)
Reinforcement Learning
(10)
Learning Types
(9)
Methods
(9)
Mathematics & Optimization
(6)
Core Methods
(5)
Learning Paradigms
(5)
Application Areas
(4)
Mathematics
(4)
Deep Learning
(3)
Optimization
(3)
Natural Language Processing
(2)
Keywords
imitation learning
(5)
sample complexity
(4)
large language model
(4)
offline reinforcement learning
(3)
policy learning
(3)
reward model
(3)
online learning
(3)
moment matching
(2)
minimax rate
(2)
instruction following
(2)
wasserstein distance
(2)
regret bound
(2)
reinforcement learning from human feedback
(2)
reinforcement learning
(2)
federated learning
(2)
language modeling
(2)
behavior cloning
(2)
policy optimization
(2)
reward modeling
(1)
representation learning
(1)
Papers
EmbedLLM: Learning Compact Representations of Large Language Models
ICLR 2025
How to Evaluate Reward Models for RLHF
ICLR 2025
Meta-Rewarding Language Models: Self-Improving Alignment with LLM-as-a-Meta-Judge
EMNLP 2025
Thinking LLMs: General Instruction Following with Thought Generation
ICML 2025
Token Assorted: Mixing Latent and Text Tokens for Improved Language Model Reasoning
ICML 2025
An Analysis of Tokenization: Transformers under Markov Data
NeurIPS 2024
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF
ICML 2024
Towards a Theoretical Understanding of the 'Reversal Curse' via Training Dynamics
NeurIPS 2024
Toxicity Detection for Free
NeurIPS 2024
Byzantine-Robust Federated Learning with Optimal Statistical Rates
AISTATS 2023
Doubly-Robust Self-Training
NeurIPS 2023
Importance Weighted Actor-Critic for Optimal Conservative Offline Reinforcement Learning
NeurIPS 2023
Jump-Start Reinforcement Learning
ICML 2023
Online Learning in Stackelberg Games with an Omniscient Follower
ICML 2023
Optimal Conservative Offline RL with General Function Approximation via Augmented Lagrangian
ICLR 2023
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons
ICML 2023
Securing Secure Aggregation: Mitigating Multi-Round Privacy Leakage in Federated Learning
AAAI 2023
Towards Optimal Caching and Model Selection for Large Model Inference
NeurIPS 2023
Beyond the Best: Distribution Functional Estimation in Infinite-Armed Bandits
NeurIPS 2022
Minimax Optimal Online Imitation Learning via Replay Estimation
NeurIPS 2022
Nearly Optimal Policy Optimization with Stable at Any Time Guarantee
ICML 2022
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism
NeurIPS 2021
MADE: Exploration via Maximizing Deviation from Explored Regions
NeurIPS 2021
On the Value of Interaction and Function Approximation in Imitation Learning
NeurIPS 2021
SLIP: Learning to predict in unknown dynamical systems with long-term memory
NeurIPS 2020
Toward the Fundamental Limits of Imitation Learning
NeurIPS 2020
Approximate Profile Maximum Likelihood
JMLR 2019
Theoretically Principled Trade-off between Robustness and Accuracy
ICML 2019
Entropy Rate Estimation for Markov Chains with Large State Space
NeurIPS 2018
Local moment matching: A unified methodology for symmetric functional estimation and distribution estimation under Wasserstein distance
COLT 2018
The Nearest Neighbor Information Estimator is Adaptively Near Minimax Rate-Optimal
NeurIPS 2018