WS 2018

Findings of the E2E NLG Challenge

WS 2018 UFAL-DSG/tgen

This paper summarises the experimental setup and results of the first shared task on end-to-end (E2E) natural language generation (NLG) in spoken dialogue systems.

DATA-TO-TEXT GENERATION SPOKEN DIALOGUE SYSTEMS

Deep Graph Convolutional Encoders for Structured Data to Text Generation

WS 2018 diegma/graph-2-text

Most previous work on neural text generation from graph-structured data relies on standard sequence-to-sequence methods.

DATA-TO-TEXT GENERATION GRAPH-TO-SEQUENCE

Improving Context Modelling in Multimodal Dialogue Generation

WS 2018 shubhamagarwal92/mmd

In this work, we investigate the task of textual response generation in a multimodal task-oriented dialogue system.

DIALOGUE GENERATION

E2E NLG Challenge: Neural Models vs. Templates

WS 2018 UKPLab/e2e-nlg-challenge-2017

E2E NLG Challenge is a shared task on generating restaurant descriptions from sets of key-value pairs.

DATA-TO-TEXT GENERATION

Enriching the WebNLG corpus

WS 2018 ThiagoCF05/webnlg

This paper describes the enrichment of WebNLG corpus, with the aim to further extend its usefulness as a resource for evaluating common NLG tasks, including Discourse Ordering, Lexicalization and Referring Expression Generation.

MACHINE TRANSLATION TEXT GENERATION

Syntactic Manipulation for Generating more Diverse and Interesting Texts

WS 2018 jderiu/e2e_nlg

Natural Language Generation plays an important role in the domain of dialogue systems as it determines how users perceive the system.

TEXT GENERATION

Talking about other people: an endless range of possibilities

WS 2018 evanmiltenburg/LabelingPeople

This taxonomy serves as a reference point to think about how other people should be described, and can be used to classify and compute statistics about labels applied to people.

TEXT GENERATION

Automatic Opinion Question Generation

WS 2018 Tina-19/Question-Generation

We study the problem of opinion question generation from sentences with the help of community-based question answering systems.

COMMUNITY QUESTION ANSWERING QUESTION GENERATION READING COMPREHENSION TEXT GENERATION