Text generation from semantic parses is to generate textual descriptions for the formal representation inputs such as logic forms and SQL queries. This is challenging for two reasons: (1) the complex and intensive inner logic with data scarcity constraint, (2) the lack of automatic logic consistency evaluation metrics. To address these two challenges, this paper first proposes SNOWBALL, a framework for text generation from semantic parses that employs an iterative training procedure by recursively augmenting the training set with quality control. Second, we propose a novel automatic metric, BLEC, for evaluating the logical consistency between the semantic parses and generated texts. The experimental results on two benchmark datasets, Logic2Text and Spider, demonstrate the SNOWBALL framework enhances the logic consistency on both BLEC and human evaluation. Furthermore, our statistical analysis reveals that BLEC is more logically consistent with human evaluation than general-purpose automatic metrics including BLEU, ROUGE and BLEURT.

Logic-Consistency Text Generation from Semantic Parses

Many database users do not precisely know the structure or the content of databases, and thus their queries do not exactly reflect their information needs. To help users formulate their questions when they query databases, we propose AUTO SQL, a question auto-completion framework in Text-to-SQL for natural language interfaces to databases. We construct a benchmark dataset and experiment with models on our constructed dataset. Experiment results demonstrate that our dataset is challenging for current models.

AutoSQL: Question Auto-Completion for Text-to-SQL

Findings Papers - Language Generation

technical paper

**Welcome to ACL-IJCNLP 2021!**

The great event is jointly organized by the Association for Computational Linguistics (ACL) and Asian Federation of Natural Language Processing (AFNLP). 

As in previous years, the program of the conference includes a poster session, tutorials, workshops and demonstrations in addition to the main conference.


We were able to keep the registration fees similar to those charged for the virtual ACL 2020. The one fee allows attendance at the main conference and any/all tutorials and workshops. These fees would be $125 Regular Early and $175 Regular Late; $50 Student Early and $75 Student Late. Early registration closes at midnight July 11, 2021 (Eastern Daylight Time).

**Reminder:** It is ACL’s policy that at least one author of each accepted paper (including ACL Finding papers) must register for the conference.

**Reminder2:** Underline site will open closer to the event. If you already registered you will receive access detail

Registration is now open

IJCNLP-AACL 2021

The great event is jointly organized by the Association for Computational Linguistics (ACL) and Asian Federation of Natural Language Processing (AFNLP).

Peng .

3

Presentations

Logic-Consistency Text Generation from Semantic Parses

AutoSQL: Question Auto-Completion for Text-to-SQL

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

COMPANY

RESOURCES