Dominican Republic

EMNLP 2021 is planned to be a hybrid event in Punta Cana, Dominican Republic, with both on-site and fully virtual participation possible. The experience for on-site participants would closely approximate a normal pre-COVID *ACL conference, with 5-6 thematically organized parallel sessions and live Q/A and interactive discussion immediately after the talks. Presentations by virtual participants will be equitably interleaved with those of on-site participants, projected on the auditorium screens as if on-site, and also followed immediately by live Q/A and interactive discussion at a time during reasonable waking hours for the virtual presenter. For all participants, on-site and virtual, who are unable to attend a session due to either time-zone issues or because they are participating in another session live, talk recordings and slides will be available online at a minimum after the live presentation (and in many cases before as well), and questions may be submitted in advance on session-specific discussion boards and answered live in session with the usual visual aids if desired.

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Please Note: The EMNLP registration system is not currently connected to the underline site as we are still in the process of building out EMNLP 2021. You will receive access instructions from underline the week of November 1st. 

Access is given only to EMNLP upon registration, if you have not registered please do so [here](https://2021.emnlp.org/registration).

Registered attendees will receive access the week of November 1st.

EMNLP 2021

EMNLP 2021 is planned to be a hybrid event in Punta Cana, Dominican Republic, with both on-site and fully virtual participation possible.

Next generation task-oriented dialog systems need to understand conversational contexts with their perceived surroundings, to effectively help users in the real-world multimodal environment. Existing task-oriented dialog datasets aimed towards virtual assistance fall short and do not situate the dialog in the user's multimodal context. To overcome, we present a new dataset for Situated and Interactive Multimodal Conversations, SIMMC 2.0, which includes 11K task-oriented user<>assistant dialogs (117K utterances) in the shopping domain, grounded in immersive and photo-realistic scenes. The dialogs are collected using a two-phase pipeline: (1) A novel multimodal dialog simulator generates simulated dialog flows, with an emphasis on diversity and richness of interactions, (2) Manual paraphrasing of the generated utterances to collect diverse referring expressions. We provide an in-depth analysis of the collected dataset, and describe in detail the four main benchmark tasks we propose. Our baseline model, powered by the state-of-the-art language model, shows promising results, and highlights new challenges and directions for the community to study. Code & data are made publicly available: https://github.com/facebookresearch/simmc2.

SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal Conversations

poster

Multi-Modal Open-Domain Dialogue

A Label-Aware BERT Attention Network for Zero-Shot Multi-Intent Detection in Spoken Language Understanding

GOLD: Improving Out-of-Scope Detection in Dialogues using Data Augmentation

Zero-Shot Dialogue Disentanglement by Self-Supervised Entangled Response Selection

Automatically Exposing Problems with Neural Dialog Models

Towards Automatic Evaluation of Dialog Systems: A Model-Free Off-Policy Evaluation Approach

Maastricht University’s Large-Scale Multilingual Machine Translation System for WMT 2021

GTCOM Neural Machine Translation Systems for WMT21

Findings of the WMT Shared Task on Machine Translation Using Terminologies

Findings of the WMT 2021 Shared Task on Quality Estimation

workshop paper

https://d3smihljt9218e.cloudfront.net/transcript/24857/subtitle/5694598fb84092d1d58f2cd332607155.vtt

English (automatic)

SIMMC 2.0: A Task-oriented Dialog Dataset for Immersive Multimodal Conversations

Downloads

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