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Found 14 papers, 8 papers with code
ADS-Cap: A Framework for Accurate and Diverse Stylized Captioning with Unpaired Stylistic Corpora
Generating visually grounded image captions with specific linguistic styles using unpaired stylistic corpora is a challenging task, especially since we expect stylized captions with a wide variety of stylistic patterns.
$SmartProbe$: A Virtual Moderator for Market Research Surveys
Market research surveys are a powerful methodology for understanding consumer perspectives at scale, but are limited by depth of understanding and insights.
Which Model Shall I Choose? Cost/Quality Trade-offs for Text Classification Tasks
Industry practitioners always face the problem of choosing the appropriate model for deployment under different considerations, such as to maximize a metric that is crucial for production, or to reduce the total cost given financial concerns.
Probing Cross-modal Semantics Alignment Capability from the Textual Perspective
In recent years, vision and language pre-training (VLP) models have advanced the state-of-the-art results in a variety of cross-modal downstream tasks.
Music-to-Text Synaesthesia: Generating Descriptive Text from Music Recordings
In this paper, we consider a novel research problem: music-to-text synaesthesia.
Analyzing the Intensity of Complaints on Social Media
Furthermore, we conduct a comprehensive linguistic analysis around complaints, including the connections between complaints and sentiment, and a cross-lingual comparison for complaints expressions used by Chinese and English speakers.
Doctor Recommendation in Online Health Forums via Expertise Learning
Huge volumes of patient queries are daily generated on online health forums, rendering manual doctor allocation a labor-intensive task.
Faster Nearest Neighbor Machine Translation
The core idea of Faster $k$NN-MT is to use a hierarchical clustering strategy to approximate the distance between the query and a data point in the datastore, which is decomposed into two parts: the distance between the query and the center of the cluster that the data point belongs to, and the distance between the data point and the cluster center.
GNN-LM: Language Modeling based on Global Contexts via GNN
Inspired by the notion that ``{\it to copy is easier than to memorize}``, in this work, we introduce GNN-LM, which extends the vanilla neural language model (LM) by allowing to reference similar contexts in the entire training corpus.
Measuring Forecasting Skill from Text
We present a number of linguistic metrics which are computed over text associated with people's predictions about the future including: uncertainty, readability, and emotion.
Extracting a Knowledge Base of COVID-19 Events from Social Media
In this paper, we present a manually annotated corpus of 10, 000 tweets containing public reports of five COVID-19 events, including positive and negative tests, deaths, denied access to testing, claimed cures and preventions.
Analyzing the Perceived Severity of Cybersecurity Threats Reported on Social Media
In this paper, we investigate methods to analyze the severity of cybersecurity threats based on the language that is used to describe them online.
Does Weather Matter? Causal Analysis of TV Logs
To the best of our knowledge, this is the first large-scale causal study of the impact of weather on TV watching patterns.
Cascading Bandits for Large-Scale Recommendation Problems
In this work, we study cascading bandits, an online learning variant of the cascade model where the goal is to recommend $K$ most attractive items from a large set of $L$ candidate items.
