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Found 16 papers, 3 papers with code
Ad-hoc Document Retrieval using Weak-Supervision with BERT and GPT2
We describe a weakly-supervised method for training deep learning models for the task of ad-hoc document retrieval.
Unsupervised Search Algorithm Configuration using Query Performance Prediction
Search engine configuration can be quite difficult for inexpert developers.
tBDFS: Temporal Graph Neural Network Leveraging DFS
A common approach employed by most previous works is to apply a layer that aggregates information from the historical neighbors of a node.
Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commerce
In e-commerce, the watchlist enables users to track items over time and has emerged as a primary feature, playing an important role in users' shopping journey.
PreSizE: Predicting Size in E-Commerce using Transformers
Predicting a proper size for an item to recommend is an important personalization challenge, and is being studied in this work.
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.
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.
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.
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
Query Scheduling in the Presence of Complex User Profiles
Advances in Web technology enable personalization proxies that assist users in satisfying their complex information monitoring and aggregation needs through the repeated querying of multiple volatile data sources.
Query Term Weighting based on Query Performance Prediction
This work presents a general query term weighting approach based on query performance prediction (QPP).
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
