36 citations · 67 across the 2 of their papers we have counts for
5 papers
Pyserini: An Easy-to-Use Python Toolkit to Support Replicable IR Research with Sparse and Dense Representations
Jimmy Lin, Xueguang Ma, Sheng-Chieh Lin +3
Pyserini is an easy-to-use Python toolkit that supports replicable IR research by providing effective first-stage retrieval in a multi-stage ranking architecture. Our toolkit is se…
Distilling Dense Representations for Ranking using Tightly-Coupled Teachers
Sheng-Chieh Lin, Jheng-Hong Yang, Jimmy Lin
We present an approach to ranking with dense representations that applies knowledge distillation to improve the recently proposed late-interaction ColBERT model. Specifically, we d…
Multi-Stage Conversational Passage Retrieval: An Approach to Fusing Term Importance Estimation and Neural Query Rewriting
Sheng-Chieh Lin, Jheng-Hong Yang, Rodrigo Nogueira +3
Conversational search plays a vital role in conversational information seeking. As queries in information seeking dialogues are ambiguous for traditional ad-hoc information retriev…
Conversational Question Reformulation via Sequence-to-Sequence Architectures and Pretrained Language Models
Sheng-Chieh Lin, Jheng-Hong Yang, Rodrigo Nogueira +3
This paper presents an empirical study of conversational question reformulation (CQR) with sequence-to-sequence architectures and pretrained language models (PLMs). We leverage PLM…
TTTTTackling WinoGrande Schemas
Sheng-Chieh Lin, Jheng-Hong Yang, Rodrigo Nogueira +3
We applied the T5 sequence-to-sequence model to tackle the AI2 WinoGrande Challenge by decomposing each example into two input text strings, each containing a hypothesis, and using…