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We stand with Ukraine

Mengyue Yang

Orcid: 0000-0003-4175-8398

According to our database¹, Mengyue Yang authored at least 60 papers between 2018 and 2026.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

Legend:

Book In proceedings Article PhD thesis Dataset Other

Links

On csauthors.net:

Bibliography

2026

Distill-Belief: Closed-Loop Inverse Source Localization and Characterization in Physical Fields.

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CoRR, April, 2026

CreativeGame:Toward Mechanic-Aware Creative Game Generation.

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CoRR, April, 2026

CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges.

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CoRR, March, 2026

Invariant Causal Routing for Governing Social Norms in Online Market Economies.

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CoRR, March, 2026

Seeking Necessary and Sufficient Information from Multimodal Medical Data.

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CoRR, March, 2026

Learning Generation Orders for Masked Discrete Diffusion Models via Variational Inference.

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Laurence Aitchison

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Raul Santos-Rodriguez

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CoRR, February, 2026

A Very Big Video Reasoning Suite.

[DOI]

Maijunxian Wang

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Thaddäus Wiedemer

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Raphaël Millière

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Nuno Vasconcelos

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Daniel Khashabi

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CoRR, February, 2026

ProcMEM: Learning Reusable Procedural Memory from Experience via Non-Parametric PPO for LLM Agents.

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CoRR, February, 2026

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey.

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Francisco Piedrahita Velez

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Trans. Mach. Learn. Res., 2026

A Comprehensive Survey of Process Reward Models: Data Generation, Model Construction, and Usage.

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Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2026

Toward Causal Foundation World Models: From Representation to Decision-Making.

[DOI]

Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

Fine-Grained Interpretation of Political Opinions in Large Language Models.

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Proceedings of the Fortieth AAAI Conference on Artificial Intelligence, 2026

2025

Dynamic Correction of Erroneous State Estimates via Diffusion Bayesian Exploration.

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CoRR, December, 2025

Probing the "Psyche" of Large Reasoning Models: Understanding Through a Human Lens.

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CoRR, December, 2025

TriShGAN: Enhancing Sparsity and Robustness in Multivariate Time Series Counterfactuals Explanation.

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CoRR, November, 2025

A Survey of Process Reward Models: From Outcome Signals to Process Supervisions for Large Language Models.

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CoRR, October, 2025

Memory-Driven Self-Improvement for Decision Making with Large Language Models.

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CoRR, September, 2025

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey.

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Michael Littman

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CoRR, September, 2025

CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models.

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CoRR, July, 2025

Curious Causality-Seeking Agents Learn Meta Causal World.

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Francesco Faccio

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Jürgen Schmidhuber

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CoRR, June, 2025

Estimating the Effects of Sample Training Orders for Large Language Models without Retraining.

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CoRR, May, 2025

MF-LLM: Simulating Collective Decision Dynamics via a Mean-Field Large Language Model Framework.

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CoRR, April, 2025

Single machine scheduling problem with unexpected failures under flexible maintenance.

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J. Oper. Res. Soc., January, 2025

Beyond Prior Limits: Addressing Distribution Misalignment in Particle Filtering.

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CoRR, January, 2025

Attention-Driven Hierarchical Reinforcement Learning with Particle Filtering for Source Localization in Dynamic Fields.

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CoRR, January, 2025

Curious Causality-Seeking Agents in Open-ended Worlds.

[DOI]

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Francesco Faccio

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Jürgen Schmidhuber

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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning.

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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Decentralized Dynamic Cooperation of Personalized Models for Federated Continual Learning.

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Abudukelimu Wuerkaixi

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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

MF-LLM: Simulating Population Decision Dynamics via a Mean-Field Large Language Model Framework.

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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

A Principle of Targeted Intervention for Multi-Agent Reinforcement Learning.

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Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2025, 2025

Mean Field Correlated Imitation Learning.

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Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

When Can Proxies Improve the Sample Complexity of Preference Learning?

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Daniel Augusto de Souza

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Pasquale Minervini

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Alexander Nicholas D'Amour

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Large Language Models are Demonstration Pre-Selectors for Themselves.

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Proceedings of the Forty-second International Conference on Machine Learning, 2025

Efficient Reinforcement Learning with Large Language Model Priors.

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Haitham Bou-Ammar

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Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Causal Representation Learning from Multimodal Biomedical Observations.

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Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Learning Macroeconomic Policies Through Dynamic Stackelberg Mean-Field Games.

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Proceedings of the ECAI 2025 - 28th European Conference on Artificial Intelligence, 25-30 October 2025, Bologna, Italy, 2025

2024

Implementing a bivariate ordering and replacement policy for deteriorating systems with two failure types.

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Int. Trans. Oper. Res., July, 2024

Natural Language Reinforcement Learning.

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Girish A. Koushik

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CoRR, 2024

Causal Representation Learning from Multimodal Biological Observations.

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CoRR, 2024

Efficient Reinforcement Learning with Large Language Model Priors.

[DOI]

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Haitham Bou-Ammar

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CoRR, 2024

Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games.

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CoRR, 2024

Natural Language Reinforcement Learning.

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Girish A. Koushik

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CoRR, 2024

InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization.

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Julian J. McAuley

Proceedings of the ACM on Web Conference 2024, 2024

2023

Debiased Recommendation with User Feature Balancing.

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ACM Trans. Inf. Syst., October, 2023

Invariant Learning via Probability of Sufficient and Necessary Causes.

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Jean-Francois Ton

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CoRR, 2023

Rectifying Unfairness in Recommendation Feedback Loop.

[DOI]

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Jean-Francois Ton

Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2023

Invariant Learning via Probability of Sufficient and Necessary Causes.

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Jean-Francois Ton

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Lending Interaction Wings to Recommender Systems with Conversational Agents.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

ChessGPT: Bridging Policy Learning and Language Modeling.

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Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Specify Robust Causal Representation from Mixed Observations.

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Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Replace Scoring with Arrangement: A Contextual Set-to-Arrangement Framework for Learning-to-Rank.

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Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

Generalizable Information Theoretic Causal Representation.

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CoRR, 2022

Debiased Recommendation with User Feature Balancing.

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CoRR, 2022

2021

Deconfounding Representation Learning Based on User Interactions in Recommendation Systems.

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Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models.

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Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Top-N Recommendation with Counterfactual User Preference Simulation.

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Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

2020

Causal World Models by Unsupervised Deconfounding of Physical Dynamics.

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CoRR, 2020

CausalVAE: Structured Causal Disentanglement in Variational Autoencoder.

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CoRR, 2020

Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation.

[DOI]

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Zhiwei (Tony) Qin

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Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

2018

A Study for Moving Object Extraction Method of Intelligent Vehicle Omnidirectional Lidar.

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J. Inf. Hiding Multim. Signal Process., 2018

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