1 code implementation • 10 Jan 2023 • Yunchang Zhu, Liang Pang, Kangxi Wu, Yanyan Lan, HuaWei Shen, Xueqi Cheng
Comparative loss is essentially a ranking loss on top of the task-specific losses of the full and ablated models, with the expectation that the task-specific loss of the full model is minimal.
1 code implementation • 25 Apr 2022 • Yunchang Zhu, Liang Pang, Yanyan Lan, HuaWei Shen, Xueqi Cheng
Ideally, if a PRF model can distinguish between irrelevant and relevant information in the feedback, the more feedback documents there are, the better the revised query will be.
1 code implementation • EMNLP 2021 • Yunchang Zhu, Liang Pang, Yanyan Lan, HuaWei Shen, Xueqi Cheng
Information seeking is an essential step for open-domain question answering to efficiently gather evidence from a large corpus.
Ranked #3 on Question Answering on HotpotQA
1 code implementation • 22 May 2020 • Yunchang Zhu, Liang Pang, Yanyan Lan, Xue-Qi Cheng
To fill this gap, we switch to a ranking perspective that sorts the hypotheses in order of their plausibilities.