Lin, S.-C., Yang, J.-H., Nogueira, R., Tsai, M.-F., Wang, C.-J., & Lin, J. (2021). Multi-Stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting. ACM Transactions on Information Systems (TOIS), 39, 1-48. https://doi.org/10.1145/3446426
Reference author: Sheng-Chieh Lin
First name
Sheng-Chieh
Last name
Lin
Lin, S.-C., Yang, J.-H., & Lin, J. (2021). Contextualized Query Embeddings for Conversational Search. Presented at the Contextualized Query Embeddings for Conversational Search. Retrieved from https://aclanthology.org/2021.emnlp-main.77
Lin, S.-C., & Lin, J. (2021). Densifying Sparse Representations for Passage Retrieval by Representational Slicing. ArXiv, abs/2112.04666. Retrieved from https://arxiv.org/abs/2112.04666
Lin, S.-C., Yang, J.-H., Nogueira, R., Tsai, M.-F., Wang, C.-J., & Lin, J. (2021). Multi-Stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting. ACM Transactions on Information Systems (TOIS), 39, 1-48. https://doi.org/10.1145/3446426
Lin, S.-C., Yang, J.-H., & Lin, J. (2021). Contextualized Query Embeddings for Conversational Search. Presented at the Contextualized Query Embeddings for Conversational Search. Retrieved from https://aclanthology.org/2021.emnlp-main.77
Lin, S.-C., & Lin, J. (2021). Densifying Sparse Representations for Passage Retrieval by Representational Slicing. ArXiv, abs/2112.04666. Retrieved from https://arxiv.org/abs/2112.04666
Lin, S.-C., Yang, J.-H., & Lin, J. (2021). In-Batch Negatives for Knowledge Distillation With Tightly-Coupled Teachers for Dense Retrieval. Presented at the In-Batch Negatives for Knowledge Distillation With Tightly-Coupled Teachers for Dense Retrieval. Retrieved from https://aclanthology.org/2021.repl4nlp-1.17
Lin, S.-C., Yang, J.-H., & Lin, J. (2021). In-Batch Negatives for Knowledge Distillation With Tightly-Coupled Teachers for Dense Retrieval. Presented at the In-Batch Negatives for Knowledge Distillation With Tightly-Coupled Teachers for Dense Retrieval. Retrieved from https://aclanthology.org/2021.repl4nlp-1.17
Lin, S.-C., Li, M., & Lin, J. (2022). Aggretriever: A Simple Approach to Aggregate Textual Representation For Robust Dense Passage Retrieval. ArXiv, abs/2208.00511. https://doi.org/10.48550/arXiv.2208.00511
Lin, S.-C., Li, M., & Lin, J. (2022). Aggretriever: A Simple Approach to Aggregate Textual Representation For Robust Dense Passage Retrieval. ArXiv, abs/2208.00511. https://doi.org/10.48550/arXiv.2208.00511