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Found 21 papers, 1 papers with code
Evaluating Machine Translation in Cross-lingual E-Commerce Search
Multilingual query localization is integral to modern e-commerce.
Controlled Text Generation with Hidden Representation Transformations
We propose CHRT (Control Hidden Representation Transformation) - a controlled language generation framework that steers large language models to generate text pertaining to certain attributes (such as toxicity).
Machine Translation Impact in E-commerce Multilingual Search
Using this information we develop techniques to compare query translations for multiple language pairs and identify the most promising language pairs to invest and improve.
Accountable Error Characterization
Customers of machine learning systems demand accountability from the companies employing these algorithms for various prediction tasks.
Teacher-Student Learning Paradigm for Tri-training: An Efficient Method for Unlabeled Data Exploitation
Given that labeled data is expensive to obtain in real-world scenarios, many semi-supervised algorithms have explored the task of exploitation of unlabeled data.
Using Structured Representation and Data: A Hybrid Model for Negation and Sentiment in Customer Service Conversations
We further investigate the results of negation scope detection for the sentiment prediction task on customer service conversation data using both a traditional SVM and a Neural Network.
Don't get Lost in Negation: An Effective Negation Handled Dialogue Acts Prediction Algorithm for Twitter Customer Service Conversations
Lately, there have been several works proposing a novel taxonomy for fine-grained dialogue acts as well as develop algorithms for automatic detection of these acts.
SlugNERDS: A Named Entity Recognition Tool for Open Domain Dialogue Systems
In dialogue systems, the tasks of named entity recognition (NER) and named entity linking (NEL) are vital preprocessing steps for understanding user intent, especially in open domain interaction where we cannot rely on domain-specific inference.
Slugbot: An Application of a Novel and Scalable Open Domain Socialbot Framework
In this paper we introduce a novel, open domain socialbot for the Amazon Alexa Prize competition, aimed at carrying on friendly conversations with users on a variety of topics.
Summarizing Dialogic Arguments from Social Media
We show that we can identify the most important arguments by using the dialog context with a best F-measure of 0. 74 for gun control, 0. 71 for gay marriage, and 0. 67 for abortion.
Combining Search with Structured Data to Create a More Engaging User Experience in Open Domain Dialogue
The greatest challenges in building sophisticated open-domain conversational agents arise directly from the potential for ongoing mixed-initiative multi-turn dialogues, which do not follow a particular plan or pursue a particular fixed information need.
Are you serious?: Rhetorical Questions and Sarcasm in Social Media Dialog
We present experiments to distinguish between these uses of RQs using SVM and LSTM models that represent linguistic features and post-level context, achieving results as high as 0. 76 F1 for "sarcastic" and 0. 77 F1 for "other" in forums, and 0. 83 F1 for both "sarcastic" and "other" in tweets.
Debbie, the Debate Bot of the Future
Chatbots are a rapidly expanding application of dialogue systems with companies switching to bot services for customer support, and new applications for users interested in casual conversation.
Data-Driven Dialogue Systems for Social Agents
In order to build dialogue systems to tackle the ambitious task of holding social conversations, we argue that we need a data driven approach that includes insight into human conversational chit chat, and which incorporates different natural language processing modules.
Measuring the Similarity of Sentential Arguments in Dialog
Debate websites produce curated summaries of arguments on such topics; these summaries typically consist of lists of sentences that represent frequently paraphrased propositions, or labels capturing the essence of one particular aspect of an argument, e. g.
Using Summarization to Discover Argument Facets in Online Ideological Dialog
What are the CENTRAL PROPOSITIONS associated with different stances on an issue, what are the abstract objects under discussion that are central to a speaker's argument?
Topic Independent Identification of Agreement and Disagreement in Social Media Dialogue
Research on the structure of dialogue has been hampered for years because large dialogue corpora have not been available.
A Semi-Supervised Approach to Detecting Stance in Tweets
Stance classification aims to identify, for a particular issue under discussion, whether the speaker or author of a conversational turn has Pro (Favor) or Con (Against) stance on the issue.
