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Found 10 papers, 3 papers with code
Towards Scalability and Extensibility of Query Reformulation Modeling in E-commerce Search
Notably, employing the proposed solution in search ranking resulted in 0. 14% and 0. 29% increase in overall revenue in Japanese and Hindi cases, respectively, and a 0. 08% incremental gain in the English case compared to the legacy implementation; while in search Ads matching led to a 0. 36% increase in Ads revenue in the Japanese case.
PERT: A New Solution to Pinyin to Character Conversion Task
Pinyin to Character conversion (P2C) task is the key task of Input Method Engine (IME) in commercial input software for Asian languages, such as Chinese, Japanese, Thai language and so on.
Program Transfer for Answering Complex Questions over Knowledge Bases
In this paper, we propose the approach of program transfer, which aims to leverage the valuable program annotations on the rich-resourced KBs as external supervision signals to aid program induction for the low-resourced KBs that lack program annotations.
Pre-training Language Model Incorporating Domain-specific Heterogeneous Knowledge into A Unified Representation
In this paper, we propose a heterogeneous knowledge language model (\textbf{HKLM}), a unified pre-trained language model (PLM) for all forms of text, including unstructured text, semi-structured text, and well-structured text.
An Approach to Improve Robustness of NLP Systems against ASR Errors
Speech-enabled systems typically first convert audio to text through an automatic speech recognition (ASR) model and then feed the text to downstream natural language processing (NLP) modules.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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PPKE: Knowledge Representation Learning by Path-based Pre-training
Entities may have complex interactions in a knowledge graph (KG), such as multi-step relationships, which can be viewed as graph contextual information of the entities.
KgPLM: Knowledge-guided Language Model Pre-training via Generative and Discriminative Learning
Recent studies on pre-trained language models have demonstrated their ability to capture factual knowledge and applications in knowledge-aware downstream tasks.
BERT-MK: Integrating Graph Contextualized Knowledge into Pre-trained Language Models
Complex node interactions are common in knowledge graphs (KGs), and these interactions can be considered as contextualized knowledge exists in the topological structure of KGs.
HyperText: Endowing FastText with Hyperbolic Geometry
Natural language data exhibit tree-like hierarchical structures such as the hypernym-hyponym relations in WordNet.
Integrating Graph Contextualized Knowledge into Pre-trained Language Models
Complex node interactions are common in knowledge graphs, and these interactions also contain rich knowledge information.
