Yingqi Qu

According to our database1, Yingqi Qu authored at least 13 papers between 2021 and 2025.

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

Timeline

2021
2022
2023
2024
2025
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1
2
3
4
5
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2
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3

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
A New Insight into the Epipole from Four Point Correspondences in Two Calibrated Views.
J. Math. Imaging Vis., January, 2025

Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation.
Proceedings of the 31st International Conference on Computational Linguistics, 2025

2024
Self-Evaluation of Large Language Model based on Glass-box Features.
CoRR, 2024

An Empirical Study of LLM-as-a-Judge for LLM Evaluation: Fine-tuned Judge Models are Task-specific Classifiers.
CoRR, 2024

BASES: Large-scale Web Search User Simulation with Large Language Model based Agents.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

Self-Evaluation of Large Language Model based on Glass-box Features.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
Investigating the Factual Knowledge Boundary of Large Language Models with Retrieval Augmentation.
CoRR, 2023

A Thorough Examination on Zero-shot Dense Retrieval.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
DuReader_retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine.
CoRR, 2022

DuReader-Retrieval: A Large-scale Chinese Benchmark for Passage Retrieval from Web Search Engine.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021
RocketQA: An Optimized Training Approach to Dense Passage Retrieval for Open-Domain Question Answering.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

RocketQAv2: A Joint Training Method for Dense Passage Retrieval and Passage Re-ranking.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

PAIR: Leveraging Passage-Centric Similarity Relation for Improving Dense Passage Retrieval.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021


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