Search Results for author: Anjali Narayan-Chen

Found 11 papers, 5 papers with code

Collaborative Dialogue in Minecraft

no code implementations ACL 2019 Anjali Narayan-Chen, Prashant Jayannavar, Julia Hockenmaier

We wish to develop interactive agents that can communicate with humans to collaboratively solve tasks in grounded scenarios.

Schema-Guided Natural Language Generation

1 code implementation INLG (ACL) 2020 Yuheng Du, Shereen Oraby, Vittorio Perera, Minmin Shen, Anjali Narayan-Chen, Tagyoung Chung, Anu Venkatesh, Dilek Hakkani-Tur

We train different state-of-the-art models for neural natural language generation on this dataset and show that in many cases, including rich schema information allows our models to produce higher quality outputs both in terms of semantics and diversity.

dialog state tracking Text Generation

Learning to execute instructions in a Minecraft dialogue

no code implementations ACL 2020 Prashant Jayannavar, Anjali Narayan-Chen, Julia Hockenmaier

The Minecraft Collaborative Building Task is a two-player game in which an Architect (A) instructs a Builder (B) to construct a target structure in a simulated Blocks World Environment.

Learning to Execute

Style Control for Schema-Guided Natural Language Generation

no code implementations EMNLP (NLP4ConvAI) 2021 Alicia Y. Tsai, Shereen Oraby, Vittorio Perera, Jiun-Yu Kao, Yuheng Du, Anjali Narayan-Chen, Tagyoung Chung, Dilek Hakkani-Tur

Our results show that while high style accuracy and semantic correctness are easier to achieve for more lexically-defined styles with conditional training, stylistic control is also achievable for more semantically complex styles using discriminator-based guided decoding methods.

Task-Oriented Dialogue Systems Text Generation

TEACh: Task-driven Embodied Agents that Chat

3 code implementations1 Oct 2021 Aishwarya Padmakumar, Jesse Thomason, Ayush Shrivastava, Patrick Lange, Anjali Narayan-Chen, Spandana Gella, Robinson Piramuthu, Gokhan Tur, Dilek Hakkani-Tur

Robots operating in human spaces must be able to engage in natural language interaction with people, both understanding and executing instructions, and using conversation to resolve ambiguity and recover from mistakes.

Dialogue Understanding

Context-Situated Pun Generation

1 code implementation24 Oct 2022 Jiao Sun, Anjali Narayan-Chen, Shereen Oraby, Shuyang Gao, Tagyoung Chung, Jing Huang, Yang Liu, Nanyun Peng

In this work, we propose a new task, context-situated pun generation, where a specific context represented by a set of keywords is provided, and the task is to first identify suitable pun words that are appropriate for the context, then generate puns based on the context keywords and the identified pun words.

Retrieval

ExPUNations: Augmenting Puns with Keywords and Explanations

1 code implementation24 Oct 2022 Jiao Sun, Anjali Narayan-Chen, Shereen Oraby, Alessandra Cervone, Tagyoung Chung, Jing Huang, Yang Liu, Nanyun Peng

The tasks of humor understanding and generation are challenging and subjective even for humans, requiring commonsense and real-world knowledge to master.

Explanation Generation Natural Language Understanding +1

Unsupervised Melody-Guided Lyrics Generation

no code implementations12 May 2023 Yufei Tian, Anjali Narayan-Chen, Shereen Oraby, Alessandra Cervone, Gunnar Sigurdsson, Chenyang Tao, Wenbo Zhao, Tagyoung Chung, Jing Huang, Nanyun Peng

At inference time, we leverage the crucial alignments between melody and lyrics and compile the given melody into constraints to guide the generation process.

Text Generation

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