Meng Fang

About Meng Fang

Meng Fang, With an exceptional h-index of 28 and a recent h-index of 26 (since 2020), a distinguished researcher at Technische Universiteit Eindhoven, specializes in the field of Natural Language Processing, Reinforcement Learning, Machine Learning.

His recent articles reflect a diverse array of research interests and contributions to the field:

Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation

Representation-Based Robustness in Goal-Conditioned Reinforcement Learning

Unsupervised multiple choices question answering via universal corpus

RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question Answering

COOM: A Game Benchmark for Continual Reinforcement Learning

Dynamic sparsity is channel-level sparsity learner

Large language models are neurosymbolic reasoners

Human-Guided Moral Decision Making in Text-based Games

Meng Fang Information

University

Position

(TU/e)

Citations(all)

2976

Citations(since 2020)

2537

Cited By

1117

hIndex(all)

28

hIndex(since 2020)

26

i10Index(all)

57

i10Index(since 2020)

51

Email

University Profile Page

Google Scholar

Meng Fang Skills & Research Interests

Natural Language Processing

Reinforcement Learning

Machine Learning

Top articles of Meng Fang

Adaptive Regularization of Representation Rank as an Implicit Constraint of Bellman Equation

arXiv preprint arXiv:2404.12754

2024/4/19

Representation-Based Robustness in Goal-Conditioned Reinforcement Learning

2024/3/24

Unsupervised multiple choices question answering via universal corpus

arXiv preprint arXiv:2402.17333

2024/2/27

RetrievalQA: Assessing Adaptive Retrieval-Augmented Generation for Short-form Open-Domain Question Answering

arXiv preprint arXiv:2402.16457

2024/2/26

COOM: A Game Benchmark for Continual Reinforcement Learning

NeurIPS 2023: Advances in Neural Information Processing Systems

2024/2/13

Large language models are neurosymbolic reasoners

arXiv preprint arXiv:2401.09334

2024/1/17

Human-Guided Moral Decision Making in Text-based Games

2024

Turn-Level Active Learning for Dialogue State Tracking

arXiv preprint arXiv:2310.14513

2023/10/23

Enhancing conversational search: Large language model-aided informative query rewriting

arXiv preprint arXiv:2310.09716

2023/10/15

() Visual Prompt Locates Good Structure Sparisty through a Recurent HyperNetwork

2023/10/13

Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning

2023/10/13

How do large language models capture the ever-changing world knowledge? a review of recent advances

2023/10/11

Towards data-centric graph machine learning: Review and outlook

2023/9/20

Eigensubspace of Temporal-Difference Dynamics and How It Improves Value Approximation in Reinforcement Learning

Machine Learning and Knowledge Discovery in Databases: Research Track

2023/9/18

REST: Enhancing Group Robustness in DNNs Through Reweighted Sparse Training

2023/9/17

Enhancing adversarial training via reweighting optimization trajectory

2023/6/25

Where would i go next? large language models as human mobility predictors

arXiv preprint arXiv:2308.15197

2023/8/29

Dynamic Truck–UAV Collaboration and Integrated Route Planning for Resilient Urban Emergency Response

IEEE Transactions on Engineering Management

2023/8/24

Gangyan Xu
Gangyan Xu

H-Index: 15

Meng Fang
Meng Fang

H-Index: 16

Are large kernels better teachers than transformers for convnets?

2023/4/24

See List of Professors in Meng Fang University(Technische Universiteit Eindhoven)

Co-Authors

academic-engine