Bei Peng
14 papers · 2017–2026 · 8 venues · across top CS/AI venues
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Achievements
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πΊοΈ Taxonomy Completionist (22) π Academic Marathon Β· Sprint π Conference Polyglot Β· Silver π Interdisciplinary Bridge Β· Bronze π£ Hot Topic Early Bird
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Topic Evolution
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Triple Crown
ποΈ
Keyword Collector
(59)
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Trend Setter
π
Century Club Β· Bronze
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Prolific Year Β· Productive
Top co-authors
Research topics
Artificial Intelligence
(8)
Machine Learning
(7)
Reinforcement Learning
(7)
Core AI
(7)
Methods
(6)
Learning Types Β· Machine Learning
(5)
Deep Learning
(3)
Applications
(3)
Natural Language Processing
(2)
Generation
(2)
Learning Types Β· Deep Learning
(2)
Core Methods
(1)
Learning Paradigms
(1)
Models
(1)
Optimization & Theory
(1)
Keywords
multi-agent reinforcement learning
(5)
reinforcement learning
(3)
commonsense generation
(2)
value function
(2)
interactive learning
(1)
transfer learning
(1)
image classification
(1)
human feedback
(1)
natural language generation
(1)
text generation
(1)
multimodal learning
(1)
policy learning
(1)
deepfake detection
(1)
evaluation methodology
(1)
optimistic exploration
(1)
in-context learning
(1)
synthetic data generation
(1)
intrinsic motivation
(1)
curriculum learning
(1)
multi-task learning
(1)
Papers
Synthetic Data Generation for Training Diversified Commonsense Reasoning Models
ACL 2026
Evaluating the Evaluation of Diversity in Commonsense Generation
ACL 2025
SIDA: Social Media Image Deepfake Detection, Localization and Explanation with Large Multimodal Model
CVPR 2025
Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning
EMNLP 2024
Learning to Predict Concept Ordering for Common Sense Generation
IJCNLP 2023
FACMAC: Factored Multi-Agent Centralised Policy Gradients
NeurIPS 2021
Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
ICML 2021
Regularized Softmax Deep Multi-Agent Q-Learning
NeurIPS 2021
RODE: Learning Roles to Decompose Multi-Agent Tasks
ICLR 2021
UneVEn: Universal Value Exploration for Multi-Agent Reinforcement Learning
ICML 2021
Curriculum Learning for Reinforcement Learning Domains: A Framework and Survey
JMLR 2020
Optimistic Exploration even with a Pessimistic Initialisation
ICLR 2020
Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
NeurIPS 2020
Interactive Learning from Policy-Dependent Human Feedback
ICML 2017