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Found 12 papers, 7 papers with code
Coarse-to-Fine Query Focused Multi-Document Summarization
We consider the problem of better modeling query-cluster interactions to facilitate query focused multi-document summarization.
Fine-Grained Natural Language Inference Based Faithfulness Evaluation for Diverse Summarisation Tasks
We study existing approaches to leverage off-the-shelf Natural Language Inference (NLI) models for the evaluation of summary faithfulness and argue that these are sub-optimal due to the granularity level considered for premises and hypotheses.
QTSumm: Query-Focused Summarization over Tabular Data
Motivated by this, we define a new query-focused table summarization task, where text generation models have to perform human-like reasoning and analysis over the given table to generate a tailored summary.
Text Summarization with Oracle Expectation
Extractive summarization produces summaries by identifying and concatenating the most important sentences in a document.
Tackling Query-Focused Summarization as A Knowledge-Intensive Task: A Pilot Study
In this dataset, answering the query requires document retrieval from a knowledge corpus.
Text Summarization with Latent Queries
The availability of large-scale datasets has driven the development of neural models that create summaries from single documents, for generic purposes.
Generating Query Focused Summaries from Query-Free Resources
The availability of large-scale datasets has driven the development of neural models that create generic summaries from single or multiple documents.
Meta Dialogue Policy Learning
Dialog policy determines the next-step actions for agents and hence is central to a dialogue system.
Bootstrapping a Crosslingual Semantic Parser
Considering when MT is inadequate, we also find that using our approach achieves parsing accuracy within 2% of complete translation using only 50% of training data.
Query Focused Multi-Document Summarization with Distant Supervision
We consider the problem of better modeling query-cluster interactions to facilitate query focused multi-document summarization (QFS).
Weakly Supervised Domain Detection
In this paper we introduce domain detection as a new natural language processing task.
Stock Movement Prediction from Tweets and Historical Prices
Stock movement prediction is a challenging problem: the market is highly stochastic, and we make temporally-dependent predictions from chaotic data.
Ranked #2 on
Stock Market Prediction
on stocknet
(using extra training data)
