Mouxiang Chen

Orcid: 0000-0002-8341-1467

According to our database1, Mouxiang Chen authored at least 24 papers between 2021 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
ZeroCoder: Can LLMs Improve Code Generation Without Ground-Truth Supervision?
CoRR, April, 2026

Qwen3-Coder-Next Technical Report.
CoRR, March, 2026

SWE-Universe: Scale Real-World Verifiable Environments to Millions.
CoRR, February, 2026

MegaFlow: Large-Scale Distributed Orchestration System for the Agentic Era.
CoRR, January, 2026

AmanNet: Adaptive multi-window and adversarial noise network for volatile time series prediction.
Inf. Process. Manag., 2026

2025
Posterior-GRPO: Rewarding Reasoning Processes in Code Generation.
CoRR, August, 2025

VisionTS++: Cross-Modal Time Series Foundation Model with Continual Pre-trained Visual Backbones.
CoRR, August, 2025

The Power of Architecture: Deep Dive into Transformer Architectures for Long-Term Time Series Forecasting.
CoRR, July, 2025

SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner.
CoRR, June, 2025

Build a Good Human-Free Prompt Tuning: Jointly Pre-Trained Template and Verbalizer for Few-Shot Classification.
IEEE Trans. Knowl. Data Eng., May, 2025

Parallel Scaling Law for Language Models.
CoRR, May, 2025

VisionTS: Visual Masked Autoencoders Are Free-Lunch Zero-Shot Time Series Forecasters.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

Synthesizing Software Engineering Data in a Test-Driven Manner.
Proceedings of the Forty-second International Conference on Machine Learning, 2025

SEK: Self-Explained Keywords Empower Large Language Models for Code Generation.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

2024
Self-Explained Keywords Empower Large Language Models for Code Generation.
CoRR, 2024

Calibration of Time-Series Forecasting: Detecting and Adapting Context-Driven Distribution Shift.
Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

B4: Towards Optimal Assessment of Plausible Code Solutions with Plausible Tests.
Proceedings of the 39th IEEE/ACM International Conference on Automated Software Engineering, 2024

Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

JumpCoder: Go Beyond Autoregressive Coder via Online Modification.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
ULTRA-DP: Unifying Graph Pre-training with Multi-task Graph Dual Prompt.
CoRR, 2023

Calibration of Time-Series Forecasting Transformers: Detecting and Adapting Context-Driven Distribution Shift.
CoRR, 2023

2022
LBD: Decouple Relevance and Observation for Individual-Level Unbiased Learning to Rank.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Scalar is Not Enough: Vectorization-based Unbiased Learning to Rank.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

2021
Adapting Interactional Observation Embedding for Counterfactual Learning to Rank.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021


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