Justin Fu
14 papers · 2017–2024 · 5 conferences · across top CS/AI conferences
Achievements
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π Conference Polyglot (5) π Academic Marathon (7) π Interdisciplinary Bridge π§ Keyword Pioneer π Cross-Pollinator (11)
πΊοΈ
Taxonomy Completionist
(18)
π
Interdisciplinary Bridge
π
Triple Crown
π₯
Mega-Team
(22)
π€
Dynamic Duo
(12)
π
Conference Pioneer
π
Century Club
(14)
Conferences
ICLR (5)
NIPS (5)
NAACL (2)
ECCV (1)
ICML (1)
Top co-authors
Keywords
continuous control
(3)
dialogue system
(2)
language model
(2)
policy optimization
(2)
deep reinforcement learning
(2)
function approximation
(1)
conversational ai
(1)
autonomous driving
(1)
task-oriented dialogue
(1)
inverse reinforcement learning
(1)
model-based reinforcement learning
(1)
novelty detection
(1)
reward function
(1)
off-policy learning
(1)
exemplar models
(1)
model generalization
(1)
behavioral cloning
(1)
sampling error
(1)
multi-agent simulation
(1)
goal-oriented dialogue
(1)
Papers
Improving Agent Behaviors with RL Fine-tuning for Autonomous Driving
ECCV 2024
Waymax: An Accelerated, Data-Driven Simulator for Large-Scale Autonomous Driving Research
NIPS 2023
Context-Aware Language Modeling for Goal-Oriented Dialogue Systems
NAACL 2022
CHAI: A CHatbot AI for Task-Oriented Dialogue with Offline Reinforcement Learning
NAACL 2022
Offline Model-Based Optimization via Normalized Maximum Likelihood Estimation
ICLR 2021
Benchmarks for Deep Off-Policy Evaluation
ICLR 2021
Learning to Reach Goals via Iterated Supervised Learning
ICLR 2021
From Language to Goals: Inverse Reinforcement Learning for Vision-Based Instruction Following
ICLR 2019
When to Trust Your Model: Model-Based Policy Optimization
NIPS 2019
Stabilizing Off-Policy Q-Learning via Bootstrapping Error Reduction
NIPS 2019
Diagnosing Bottlenecks in Deep Q-learning Algorithms
ICML 2019
Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition
NIPS 2018
Learning Robust Rewards with Adverserial Inverse Reinforcement Learning
ICLR 2018
EX2: Exploration with Exemplar Models for Deep Reinforcement Learning
NIPS 2017