output
20102026
most citedLearning Intents behind Interactions with Knowledge Graph for Recommendation

579 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions
Showing cs.CLShow all

5 papers · 1 filter

cs.CL2025★ 3 cited

Understanding Gender Bias in AI-Generated Product Descriptions

Markelle Kelly, Mohammad Tahaei, Padhraic Smyth +1

While gender bias in large language models (LLMs) has been extensively studied in many domains, uses of LLMs in e-commerce remain largely unexamined and may reveal novel forms of a…

cs.CL2021

SAUCE: Truncated Sparse Document Signature Bit-Vectors for Fast Web-Scale Corpus Expansion

Muntasir Wahed, Daniel Gruhl, Alfredo Alba +5

Recent advances in text representation have shown that training on large amounts of text is crucial for natural language understanding. However, models trained without predefined n…

cs.CL2019★ 68 cited

Relation Embedding with Dihedral Group in Knowledge Graph

Canran Xu, Ruijiang Li

Link prediction is critical for the application of incomplete knowledge graph (KG) in the downstream tasks. As a family of effective approaches for link predictions, embedding meth…

cs.CL2018★ 8 cited

Learning Better Internal Structure of Words for Sequence Labeling

Yingwei Xin, Ethan Hart, Vibhuti Mahajan +1

Character-based neural models have recently proven very useful for many NLP tasks. However, there is a gap of sophistication between methods for learning representations of sentenc…

cs.CL2018★ 35 cited

Abstractive and Extractive Text Summarization using Document Context Vector and Recurrent Neural Networks

Chandra Khatri, Gyanit Singh, Nish Parikh

Sequence to sequence (Seq2Seq) learning has recently been used for abstractive and extractive summarization. In current study, Seq2Seq models have been used for eBay product descri…