Qiu, Linlu

Quasi-Dense Similarity Learning for Multiple Object Tracking

Pang, J., Qiu, L., Li, X., Chen, H., Li, Q., Darrell, T., & Yu, F. (2021) · 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Video Surveillance and Tracking MethodsAutonomous Vehicle Technology and Safety

Cited by 480

Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks

Wu, Z., Qiu, L., Ross, A., Akyürek, E., Chen, B., Wang, B., Kim, N., Andreas, J., & Kim, Y. (2024) · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 58

Reasoning or Reciting? Exploring the Capabilities and Limitations of Language Models Through Counterfactual Tasks

Wu, Z., Qiu, L., Ross, A., Akyürek, E., Chen, B., Wang, B., Kim, N., Andreas, J., & Kim, Y. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 19

Generate-and-Retrieve: use your predictions to improve retrieval for semantic parsing

Zemlyanskiy, Y., de Jong, M., Ainslie, J., Pasupat, P., Shaw, P., Qiu, L., Sanghai, S., & Sha, F. (2022) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 8

The Surprising Effectiveness of Test-Time Training for Few-Shot Learning

Akyürek, E., Damani, M., Zweiger, A., Qiu, L., Guo, H., Pari, J., Kim, Y., & Andreas, J. (2024) · arXiv

Domain Adaptation and Few-Shot LearningTopic Modeling

Cited by 4