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Found 8 papers, 6 papers with code
Hypertext Entity Extraction in Webpage
Webpage entity extraction is a fundamental natural language processing task in both research and applications.
Self-Supervised Audio-and-Text Pre-training with Extremely Low-Resource Parallel Data
Our pre-training framework consists of the following components: (1) Intra-modal Denoising Auto-Encoding (IDAE), which is able to reconstruct input text (audio) representations from a noisy version of itself.
ESCM$^2$: Entire Space Counterfactual Multi-Task Model for Post-Click Conversion Rate Estimation
In this paper, we theoretically demonstrate that ESMM suffers from the following two problems: (1) Inherent Estimation Bias (IEB), where the estimated CVR of ESMM is inherently higher than the ground truth; (2) Potential Independence Priority (PIP) for CTCVR estimation, where there is a risk that the ESMM overlooks the causality from click to conversion.
CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations
Existing audio-language task-specific predictive approaches focus on building complicated late-fusion mechanisms.
Solving ESL Sentence Completion Questions via Pre-trained Neural Language Models
Sentence completion (SC) questions present a sentence with one or more blanks that need to be filled in, three to five possible words or phrases as options.
Mathematical Word Problem Generation from Commonsense Knowledge Graph and Equations
There is an increasing interest in the use of mathematical word problem (MWP) generation in educational assessment.
Dolphin: A Spoken Language Proficiency Assessment System for Elementary Education
In our offline experiments, we show that Dolphin improves both phonological fluency and semantic relevance evaluation performance when compared to state-of-the-art baselines on real-world educational data sets.
Recommender Systems with Heterogeneous Side Information
In modern recommender systems, both users and items are associated with rich side information, which can help understand users and items.
