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Lihong Li

53 papers · 2008–2026 · 10 conferences · across top CS/AI conferences

Achievements

🌍 Conference Polyglot (9) 🐣 Hot Topic Early Bird 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (17) πŸ—ΊοΈ Taxonomy Completionist (23) 🧭 Keyword Pioneer 🌟 Keyword Trendsetter Combo (3) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ”¬ Deep Specialist (12) 🧬 Topic Evolution πŸ† Keyword Champion (5) πŸš€ Conference Pioneer ⚑ Prolific Year (6) πŸ’Ž Century Club (52) πŸ—ƒοΈ Keyword Collector (63) πŸ“ˆ Trend Setter πŸ”₯ Unstoppable (9)

Conferences

NIPS (13) ICML (12) ICLR (8) AISTATS (6) EMNLP (4) ACL (3) JMLR (3) COLT (2) EACL (1) IJCNLP (1)

Top co-authors

Bo Dai (8) Jianfeng Gao (7) Dale Schuurmans (6) Csaba SzepesvΓ‘ri (5) Jianshu Chen (5) John Langford (5) Qiang Liu (4) Dengyong Zhou (4) Li Deng (4) Xiujun Li (4)

Research topics

Reinforcement Learning (1)

Keywords

reinforcement learning (12) regret bound (10) contextual bandit (8) online learning (7) off-policy evaluation (7) stationary distribution (5) markov decision process (5) sample complexity (4) value function (4) dialogue system (4) neural network (3) policy learning (3) importance sampling (3) upper confidence bound (3) end-to-end learning (3) truncated gradient (2) value function approximation (2) convex loss (2) bellman equation (2) l1 regularization (2)

Papers

Turn-PPO: Turn-Level Advantage Estimation with PPO for Improved Multi-Turn RL in Agentic LLMs EACL 2026
WebAgent-R1: Training Web Agents via End-to-End Multi-Turn Reinforcement Learning EMNLP 2025
Understanding Domain Randomization for Sim-to-real Transfer ICLR 2022
Near-Optimal Representation Learning for Linear Bandits and Linear RL ICML 2021
Off-policy Evaluation in Infinite-Horizon Reinforcement Learning with Latent Confounders AISTATS 2021
Efficient Reinforcement Learning in Factored MDPs with Application to Constrained RL ICLR 2021
Neural Thompson Sampling ICLR 2021
On the Optimality of Batch Policy Optimization Algorithms ICML 2021
Randomized Exploration in Generalized Linear Bandits AISTATS 2020
Off-Policy Evaluation via the Regularized Lagrangian NIPS 2020
CoinDICE: Off-Policy Confidence Interval Estimation NIPS 2020
Escaping the Gravitational Pull of Softmax NIPS 2020
Black-box Off-policy Estimation for Infinite-Horizon Reinforcement Learning ICLR 2020
Doubly Robust Bias Reduction in Infinite Horizon Off-Policy Estimation ICLR 2020
GenDICE: Generalized Offline Estimation of Stationary Values ICLR 2020
Batch Stationary Distribution Estimation ICML 2020
Neural Contextual Bandits with UCB-based Exploration ICML 2020
A Kernel Loss for Solving the Bellman Equation NIPS 2019
Neural Logic Machines ICLR 2019
Policy Certificates: Towards Accountable Reinforcement Learning ICML 2019
DualDICE: Behavior-Agnostic Estimation of Discounted Stationary Distribution Corrections NIPS 2019
SBEED: Convergent Reinforcement Learning with Nonlinear Function Approximation ICML 2018
Neural Approaches to Conversational AI ACL 2018
Subgoal Discovery for Hierarchical Dialogue Policy Learning EMNLP 2018
Breaking the Curse of Horizon: Infinite-Horizon Off-Policy Estimation NIPS 2018
Boosting the Actor with Dual Critic ICLR 2018
Adversarial Attacks on Stochastic Bandits NIPS 2018
Scalable Bilinear Pi Learning Using State and Action Features ICML 2018
Provably Optimal Algorithms for Generalized Linear Contextual Bandits ICML 2017
End-to-End Task-Completion Neural Dialogue Systems IJCNLP 2017
Towards End-to-End Reinforcement Learning of Dialogue Agents for Information Access ACL 2017
Q-LDA: Uncovering Latent Patterns in Text-based Sequential Decision Processes NIPS 2017
Composite Task-Completion Dialogue Policy Learning via Hierarchical Deep Reinforcement Learning EMNLP 2017
Stochastic Variance Reduction Methods for Policy Evaluation ICML 2017
An efficient algorithm for contextual bandits with knapsacks, and an extension to concave objectives COLT 2016
Active Learning with Oracle Epiphany NIPS 2016
Doubly Robust Off-policy Value Evaluation for Reinforcement Learning ICML 2016
Deep Reinforcement Learning with a Natural Language Action Space ACL 2016
Deep Reinforcement Learning with a Combinatorial Action Space for Predicting Popular Reddit Threads EMNLP 2016
Toward Minimax Off-policy Value Estimation AISTATS 2015
Taming the Monster: A Fast and Simple Algorithm for Contextual Bandits ICML 2014
PAC-inspired Option Discovery in Lifelong Reinforcement Learning ICML 2014
Open Problem: Regret Bounds for Thompson Sampling COLT 2012
Contextual Bandit Algorithms with Supervised Learning Guarantees AISTATS 2011
Contextual Bandits with Linear Payoff Functions AISTATS 2011
An Empirical Evaluation of Thompson Sampling NIPS 2011
Linear-Time Estimators for Propensity Scores AISTATS 2011
Learning from Logged Implicit Exploration Data NIPS 2010
Parallelized Stochastic Gradient Descent NIPS 2010
Provably Efficient Learning with Typed Parametric Models JMLR 2009
Sparse Online Learning via Truncated Gradient JMLR 2009
Reinforcement Learning in Finite MDPs: PAC Analysis JMLR 2009
Sparse Online Learning via Truncated Gradient NIPS 2008