Search Results for author:
Found 24 papers, 4 papers with code
Conversational Search with Mixed-Initiative - Asking Good Clarification Questions backed-up by Passage Retrieval
We deal with the scenario of conversational search, where user queries are under-specified or ambiguous.
TWEETSUMM - A Dialog Summarization Dataset for Customer Service
In most cases, at the end of the conversation, agents are asked to write a short summary emphasizing the problem and the proposed solution, usually for the benefit of other agents that may have to deal with the same customer or issue.
Extractive Summarization
Unsupervised Extractive Summarization
Best Practices for Machine Learning Systems: An Industrial Framework for Analysis and Optimization
In the last few years, the Machine Learning (ML) and Artificial Intelligence community has developed an increasing interest in Software Engineering (SE) for ML Systems leading to a proliferation of best practices, rules, and guidelines aiming at improving the quality of the software of ML Systems.
Conversational Search with Mixed-Initiative -- Asking Good Clarification Questions backed-up by Passage Retrieval
We deal with the scenario of conversational search, where user queries are under-specified or ambiguous.
TWEETSUMM -- A Dialog Summarization Dataset for Customer Service
In most cases, at the end of the conversation, agents are asked to write a short summary emphasizing the problem and the proposed solution, usually for the benefit of other agents that may have to deal with the same customer or issue.
Extractive Summarization
Unsupervised Extractive Summarization
HowSumm: A Multi-Document Summarization Dataset Derived from WikiHow Articles
We present HowSumm, a novel large-scale dataset for the task of query-focused multi-document summarization (qMDS), which targets the use-case of generating actionable instructions from a set of sources.
Ranked #1 on
Document Summarization
on HowSumm-Step
Summary Grounded Conversation Generation
Many conversation datasets have been constructed in the recent years using crowdsourcing.
Conversational Document Prediction to Assist Customer Care Agents
A frequent pattern in customer care conversations is the agents responding with appropriate webpage URLs that address users' needs.
Agent Assist through Conversation Analysis
Customer support agents play a crucial role as an interface between an organization and its end-users.
orgFAQ: A New Dataset and Analysis on Organizational FAQs and User Questions
Thus, we release orgFAQ, a new dataset composed of $6988$ user questions and $1579$ corresponding FAQs that were extracted from organizations' FAQ webpages in the Jobs domain.
Unsupervised FAQ Retrieval with Question Generation and BERT
The two models match user queries to FAQ answers and questions, respectively.
A Study of Human Summaries of Scientific Articles
Researchers and students face an explosion of newly published papers which may be relevant to their work.
A Summarization System for Scientific Documents
We present a novel system providing summaries for Computer Science publications.
Controversy in Context
With the growing interest in social applications of Natural Language Processing and Computational Argumentation, a natural question is how controversial a given concept is.
A Study of BERT for Non-Factoid Question-Answering under Passage Length Constraints
We study the use of BERT for non-factoid question-answering, focusing on the passage re-ranking task under varying passage lengths.
TalkSumm: A Dataset and Scalable Annotation Method for Scientific Paper Summarization Based on Conference Talks
We collected 1716 papers and their corresponding videos, and created a dataset of paper summaries.
Bot2Vec: Learning Representations of Chatbots
Chatbots (i. e., bots) are becoming widely used in multiple domains, along with supporting bot programming platforms.
An Editorial Network for Enhanced Document Summarization
We suggest a new idea of Editorial Network - a mixed extractive-abstractive summarization approach, which is applied as a post-processing step over a given sequence of extracted sentences.
Ranked #34 on
Abstractive Text Summarization
on CNN / Daily Mail
Unsupervised Dual-Cascade Learning with Pseudo-Feedback Distillation for Query-based Extractive Summarization
We propose Dual-CES -- a novel unsupervised, query-focused, multi-document extractive summarizer.
Extractive Summarization
Query-Based Extractive Summarization
Learning Concept Abstractness Using Weak Supervision
We introduce a weakly supervised approach for inferring the property of abstractness of words and expressions in the complete absence of labeled data.
Detecting Egregious Conversations between Customers and Virtual Agents
In this paper, we outline an approach to detecting such egregious conversations, using behavioral cues from the user, patterns in agent responses, and user-agent interaction.
Neural Response Generation for Customer Service based on Personality Traits
We present a neural response generation model that generates responses conditioned on a target personality.
