activity
20182021
most citedPAM: Understanding Product Images in Cross Product Category Attribute Extraction

28 citations · 32 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CL2021

End-to-End Conversational Search for Online Shopping with Utterance Transfer

Liqiang Xiao, Jun Ma2, Xin Luna Dong +6

Successful conversational search systems can present natural, adaptive and interactive shopping experience for online shopping customers. However, building such systems from scratc…

cs.CV202128 cited

PAM: Understanding Product Images in Cross Product Category Attribute Extraction

Rongmei Lin, Xiang He, Jie Feng +4

Understanding product attributes plays an important role in improving online shopping experience for customers and serves as an integral part for constructing a product knowledge g…

cs.CL20213 cited

AdaTag: Multi-Attribute Value Extraction from Product Profiles with Adaptive Decoding

Jun Yan, Nasser Zalmout, Yan Liang +3

Automatic extraction of product attribute values is an important enabling technology in e-Commerce platforms. This task is usually modeled using sequence labeling architectures, wi…

cs.CL20191 cited

Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling

Nasser Zalmout, Nizar Habash

Morphological tagging is challenging for morphologically rich languages due to the large target space and the need for more training data to minimize model sparsity. Dialectal vari…

cs.CL2019

Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging

Nasser Zalmout, Nizar Habash

Semitic languages can be highly ambiguous, having several interpretations of the same surface forms, and morphologically rich, having many morphemes that realize several morphologi…

cs.CL2018

Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models

Daniel Watson, Nasser Zalmout, Nizar Habash

Text normalization is an important enabling technology for several NLP tasks. Recently, neural-network-based approaches have outperformed well-established models in this task. Howe…