United States

NAACL 2022

Building a Personalized Dialogue System with Prompt-Tuning

## Welcome to NAACL 2022!
The Annual Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL) is taking place July 10-15, 2022 as a hybrid event, in Seattle, WA and online. We are happy to welcome all of you to conference! 
 
The main conference program features oral presentations, in-person and virtual posters and demo sessions, a plenary session for our best paper presentations and awards, keynote presentations, a plenary panel on the place of linguistics and symbolic structures in NLP, and an Industrial Track panel on Careers in NLP.
 
Posters (including Findings of NAACL 2022) and demos are grouped by areas for both the in-person and the virtual sessions. For the virtual component, the talks will be on Zoom and the posters and the demos will be in GatherTown. The Student Research Workshop and will have an oral session and a poster session.
 
The program also features 6 Tutorials and 26 Workshops.
 
 We wish you a wonderful conference!
 
[The NAACL 2022 Organizing Committee](https://2022.naacl.org/committees/organization/)

2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics

poster

MM-GATBT: Enriching Multimodal Representation Using Graph Attention Network

ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation

Compositional Generalization in Grounded Language Learning via Induced Model Sparsity

How do people talk about images? A study on open-domain conversations with images.

A Simple Approach to Jointly Rank Passages and Select Relevant Sentences in the OBQA Context

Neural Networks in a Product of Hyperbolic Spaces

Strong Heuristics for Named Entity Linking

Few-shot fine-tuning SOTA summarization models for medical dialogues

Unifying Parsing and Tree-Structured Models for Generating Sentence Semantic Representations

Defending Compositionality in Emergent Languages

https://d3smihljt9218e.cloudfront.net/transcript/36499/subtitle/f691a7be4819b32f05a96af403a9ea01.vtt

English (automatic)

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MM-GATBT: Enriching Multimodal Representation Using Graph Attention Network

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