37 citations · 127 across the 12 of their papers we have counts for
5 papers · 1 filter
CAPSTONE: Curriculum Sampling for Dense Retrieval with Document Expansion
Xingwei He, Yeyun Gong, A-Long Jin +5
The dual-encoder has become the de facto architecture for dense retrieval. Typically, it computes the latent representations of the query and document independently, thus failing t…
APOLLO: An Optimized Training Approach for Long-form Numerical Reasoning
Jiashuo Sun, Hang Zhang, Chen Lin +3
Long-form numerical reasoning in financial analysis aims to generate a reasoning program to calculate the correct answer for a given question. Previous work followed a retriever-ge…
Metric-guided Distillation: Distilling Knowledge from the Metric to Ranker and Retriever for Generative Commonsense Reasoning
Xingwei He, Yeyun Gong, A-Long Jin +7
Commonsense generation aims to generate a realistic sentence describing a daily scene under the given concepts, which is very challenging, since it requires models to have relation…
Sentiment-Aware Word and Sentence Level Pre-training for Sentiment Analysis
Shuai Fan, Chen Lin, Haonan Li +6
Most existing pre-trained language representation models (PLMs) are sub-optimal in sentiment analysis tasks, as they capture the sentiment information from word-level while under-c…
PROD: Progressive Distillation for Dense Retrieval
Zhenghao Lin, Yeyun Gong, Xiao Liu +8
Knowledge distillation is an effective way to transfer knowledge from a strong teacher to an efficient student model. Ideally, we expect the better the teacher is, the better the s…