Mingjie Zhan

According to our database1, Mingjie Zhan authored at least 27 papers between 2020 and 2025.

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

Timeline

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Links

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Bibliography

2025
RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation.
ACM Trans. Inf. Syst., September, 2025

Evaluating MLLMs with Multimodal Multi-image Reasoning Benchmark.
CoRR, June, 2025

WebGen-Bench: Evaluating LLMs on Generating Interactive and Functional Websites from Scratch.
CoRR, May, 2025

Navi-plus: Managing Ambiguous GUI Navigation Tasks with Follow-up.
CoRR, March, 2025

MathCoder2: Better Math Reasoning from Continued Pretraining on Model-translated Mathematical Code.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

SpiritSight Agent: Advanced GUI Agent with One Look.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Probability-Consistent Preference Optimization for Enhanced LLM Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

ReflectionCoder: Learning from Reflection Sequence for Enhanced One-off Code Generation.
Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

MathCoder-VL: Bridging Vision and Code for Enhanced Multimodal Mathematical Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics, 2025

UFO: Enhancing Diffusion-Based Video Generation with a Uniform Frame Organizer.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
Step-Controlled DPO: Leveraging Stepwise Error for Enhanced Mathematical Reasoning.
CoRR, 2024

Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset.
CoRR, 2024

Integrating Large Language Models into Recommendation via Mutual Augmentation and Adaptive Aggregation.
CoRR, 2024

Measuring Multimodal Mathematical Reasoning with MATH-Vision Dataset.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Empowering Character-level Text Infilling by Eliminating Sub-Tokens.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023
RecRanker: Instruction Tuning Large Language Model as Ranker for Top-k Recommendation.
CoRR, 2023

TeacherLM: Teaching to Fish Rather Than Giving the Fish, Language Modeling Likewise.
CoRR, 2023

Self-Supervised Sentence Compression for Meeting Summarization.
CoRR, 2023

Towards Versatile and Efficient Visual Knowledge Injection into Pre-trained Language Models with Cross-Modal Adapters.
CoRR, 2023

Learning Locality and Isotropy in Dialogue Modeling.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Reconstruct Before Summarize: An Efficient Two-Step Framework for Condensing and Summarizing Meeting Transcripts.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

VCSUM: A Versatile Chinese Meeting Summarization Dataset.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2021
GroupLink: An End-to-end Multitask Method for Word Grouping and Relation Extraction in Form Understanding.
CoRR, 2021

2020
DocStruct: A Multimodal Method to Extract Hierarchy Structure in Document for General Form Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020


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