activity
20202022
most citedOn Data Augmentation for Extreme Multi-label Classification

17 citations · 36 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL20221 cited

Short Text Pre-training with Extended Token Classification for E-commerce Query Understanding

Haoming Jiang, Tianyu Cao, Zheng Li +6

E-commerce query understanding is the process of inferring the shopping intent of customers by extracting semantic meaning from their search queries. The recent progress of pre-tra…

cs.CL2022

SeqZero: Few-shot Compositional Semantic Parsing with Sequential Prompts and Zero-shot Models

Jingfeng Yang, Haoming Jiang, Qingyu Yin +3

Recent research showed promising results on combining pretrained language models (LMs) with canonical utterance for few-shot semantic parsing. The canonical utterance is often leng…

cs.IR2022

RETE: Retrieval-Enhanced Temporal Event Forecasting on Unified Query Product Evolutionary Graph

Ruijie Wang, Zheng Li, Danqing Zhang +4

With the increasing demands on e-commerce platforms, numerous user action history is emerging. Those enriched action records are vital to understand users' interests and intents. R…

cs.CL202113 cited

QUEACO: Borrowing Treasures from Weakly-labeled Behavior Data for Query Attribute Value Extraction

Danqing Zhang, Zheng Li, Tianyu Cao +7

We study the problem of query attribute value extraction, which aims to identify named entities from user queries as diverse surface form attribute values and afterward transform t…

cs.CL20213 cited

Named Entity Recognition with Small Strongly Labeled and Large Weakly Labeled Data

Haoming Jiang, Danqing Zhang, Tianyu Cao +2

Weak supervision has shown promising results in many natural language processing tasks, such as Named Entity Recognition (NER). Existing work mainly focuses on learning deep NER mo…

cs.CL20212 cited

Improving Pretrained Models for Zero-shot Multi-label Text Classification through Reinforced Label Hierarchy Reasoning

Hui Liu, Danqing Zhang, Bing Yin +1

Exploiting label hierarchies has become a promising approach to tackling the zero-shot multi-label text classification (ZS-MTC) problem. Conventional methods aim to learn a matchin…