Yufei Ma

Orcid: 0009-0002-5075-0099

Affiliations:
  • Northwestern Polytechnical University, Xi'an, China


According to our database1, Yufei Ma authored at least 14 papers between 2024 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Plan Before Search: Search Agents Need Plan.
CoRR, May, 2026

Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning.
CoRR, May, 2026

SD-Search: On-Policy Hindsight Self-Distillation for Search-Augmented Reasoning.
CoRR, May, 2026

Bian Que: An Agentic Framework with Flexible Skill Arrangement for Online System Operations.
CoRR, April, 2026

IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning.
CoRR, April, 2026

OneSearch-V2: The Latent Reasoning Enhanced Self-distillation Generative Search Framework.
CoRR, March, 2026

CSMCIR: CoT-Enhanced Symmetric Alignment with Memory Bank for Composed Image Retrieval.
CoRR, January, 2026

2025
InfoGain-RAG: Boosting Retrieval-Augmented Generation via Document Information Gain-based Reranking and Filtering.
CoRR, September, 2025

OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search.
CoRR, September, 2025

InfoGain-RAG: Boosting Retrieval-Augmented Generation through Document Information Gain-based Reranking and Filtering.
Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

UniECS: Unified Multimodal E-Commerce Search Framework with Gated Cross-modal Fusion.
Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024
FashionGPT: LLM instruction fine-tuning with multiple LoRA-adapter fusion.
Knowl. Based Syst., 2024

Self-Renewal Prompt Optimizing with Implicit Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

MoDULA: Mixture of Domain-Specific and Universal LoRA for Multi-Task Learning.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024


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