Mengyue Yang

Orcid: 0000-0003-4175-8398

According to our database1, Mengyue Yang authored at least 38 papers between 2018 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
CoLD: Counterfactually-Guided Length Debiasing for Process Reward Models.
CoRR, July, 2025

Curious Causality-Seeking Agents Learn Meta Causal World.
CoRR, June, 2025

Causal Sufficiency and Necessity Improves Chain-of-Thought Reasoning.
CoRR, June, 2025

Large Language Models are Demonstration Pre-Selectors for Themselves.
CoRR, June, 2025

Fine-Grained Interpretation of Political Opinions in Large Language Models.
CoRR, June, 2025

Estimating the Effects of Sample Training Orders for Large Language Models without Retraining.
CoRR, May, 2025

MF-LLM: Simulating Collective Decision Dynamics via a Mean-Field Large Language Model Framework.
CoRR, April, 2025

Single machine scheduling problem with unexpected failures under flexible maintenance.
J. Oper. Res. Soc., January, 2025

Beyond Prior Limits: Addressing Distribution Misalignment in Particle Filtering.
CoRR, January, 2025

Attention-Driven Hierarchical Reinforcement Learning with Particle Filtering for Source Localization in Dynamic Fields.
CoRR, January, 2025

Mean Field Correlated Imitation Learning.
Proceedings of the 24th International Conference on Autonomous Agents and Multiagent Systems, 2025

Efficient Reinforcement Learning with Large Language Model Priors.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Causal Representation Learning from Multimodal Biomedical Observations.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024
Implementing a bivariate ordering and replacement policy for deteriorating systems with two failure types.
Int. Trans. Oper. Res., July, 2024

When Can Proxies Improve the Sample Complexity of Preference Learning?
CoRR, 2024

Natural Language Reinforcement Learning.
CoRR, 2024

Causal Representation Learning from Multimodal Biological Observations.
CoRR, 2024

Efficient Reinforcement Learning with Large Language Model Priors.
CoRR, 2024

Attaining Human's Desirable Outcomes in Human-AI Interaction via Structural Causal Games.
CoRR, 2024

Natural Language Reinforcement Learning.
CoRR, 2024

InfoRank: Unbiased Learning-to-Rank via Conditional Mutual Information Minimization.
Proceedings of the ACM on Web Conference 2024, 2024

2023
Debiased Recommendation with User Feature Balancing.
ACM Trans. Inf. Syst., October, 2023

Invariant Learning via Probability of Sufficient and Necessary Causes.
CoRR, 2023

Rectifying Unfairness in Recommendation Feedback Loop.
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.
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.
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.
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.
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.
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022
Generalizable Information Theoretic Causal Representation.
CoRR, 2022

Debiased Recommendation with User Feature Balancing.
CoRR, 2022

2021
Deconfounding Representation Learning Based on User Interactions in Recommendation Systems.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2021

CausalVAE: Disentangled Representation Learning via Neural Structural Causal Models.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Top-N Recommendation with Counterfactual User Preference Simulation.
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.
CoRR, 2020

CausalVAE: Structured Causal Disentanglement in Variational Autoencoder.
CoRR, 2020

Hierarchical Adaptive Contextual Bandits for Resource Constraint based Recommendation.
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.
J. Inf. Hiding Multim. Signal Process., 2018


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