mlsanityData to 7 Oct 2026

THUIR2 at NTCIR-16 Session Search (SS) Task

arXiv 2307.00250 ↗First posted 1 Jul 2023cs.IR cs.AIcited by 12

Not on the map. Why?

Abstract (arXiv)

Our team(THUIR2) participated in both FOSS and POSS subtasks of the NTCIR-161 Session Search (SS) Task. This paper describes our approaches and results. In the FOSS subtask, we submit five runs using learning-to-rank and fine-tuned pre-trained language models. We fine-tuned the pre-trained language model with ad-hoc data and session information and assembled them by a learning-to-rank method. The assembled model achieves the best performance among all participants in the preliminary evaluation. In the POSS subtask, we used an assembled model which also achieves the best performance in the preliminary evaluation.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Builds on 3 of its 9 references that are in the map. First posted on arXiv 1 Jul 2023.

Builds on

3 of 9 references.

References · 3

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Overview of the TREC 2019 deep learning trackcited by 282
  3. 2021Rethink Training of BERT Rerankers in Multi-Stage Retrieval Pipelinecited by 65

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 5; 2025: 6.

12 papers.