1 code implementation • 19 Nov 2024 • Claire Bonial, Stephanie M. Lukin, Mitchell Abrams, Anthony Baker, Lucia Donatelli, Ashley Foots, Cory J. Hayes, Cassidy Henry, Taylor Hudson, Matthew Marge, Kimberly A. Pollard, Ron artstein, David Traum, Clare R. Voss
In this paper, we describe the development of symbolic representations annotated on human-robot dialogue data to make dimensions of meaning accessible to autonomous systems participating in collaborative, natural language dialogue, and to enable common ground with human partners.
1 code implementation • 19 Nov 2024 • Stephanie M. Lukin, Claire Bonial, Matthew Marge, Taylor Hudson, Cory J. Hayes, Kimberly A. Pollard, Anthony Baker, Ashley N. Foots, Ron artstein, Felix Gervits, Mitchell Abrams, Cassidy Henry, Lucia Donatelli, Anton Leuski, Susan G. Hill, David Traum, Clare R. Voss
We introduce the Situated Corpus Of Understanding Transactions (SCOUT), a multi-modal collection of human-robot dialogue in the task domain of collaborative exploration.
no code implementations • 24 Oct 2024 • Sha Li, Revanth Gangi Reddy, Khanh Duy Nguyen, Qingyun Wang, May Fung, Chi Han, Jiawei Han, Kartik Natarajan, Clare R. Voss, Heng Ji
Complex news events, such as natural disasters and socio-political conflicts, require swift responses from the government and society.
no code implementations • 23 May 2023 • Navita Goyal, Eleftheria Briakou, Amanda Liu, Connor Baumler, Claire Bonial, Jeffrey Micher, Clare R. Voss, Marine Carpuat, Hal Daumé III
In this work, we study how users interact with QA systems in the absence of sufficient information to assess their predictions.
1 code implementation • 23 Oct 2022 • Liliang Ren, Zixuan Zhang, Han Wang, Clare R. Voss, ChengXiang Zhai, Heng Ji
Modern large-scale Pre-trained Language Models (PLMs) have achieved tremendous success on a wide range of downstream tasks.
Ranked #8 on
Few-shot NER
on Few-NERD (INTRA)
(using extra training data)
no code implementations • 31 May 2019 • Stephanie M. Lukin, Claire Bonial, Clare R. Voss
We describe the task of Visual Understanding and Narration, in which a robot (or agent) generates text for the images that it collects when navigating its environment, by answering open-ended questions, such as 'what happens, or might have happened, here?'
no code implementations • WS 2018 • Stephanie M. Lukin, Kimberly A. Pollard, Claire Bonial, Matthew Marge, Cassidy Henry, Ron Arstein, David Traum, Clare R. Voss
This paper identifies stylistic differences in instruction-giving observed in a corpus of human-robot dialogue.
no code implementations • ACL 2018 • Stephanie M. Lukin, Felix Gervits, Cory J. Hayes, Anton Leuski, Pooja Moolchandani, John G. Rogers III, Carlos Sanchez Amaro, Matthew Marge, Clare R. Voss, David Traum
ScoutBot is a dialogue interface to physical and simulated robots that supports collaborative exploration of environments.
no code implementations • WS 2018 • Stephanie M. Lukin, Reginald Hobbs, Clare R. Voss
We have piloted this design for a sequence of images in an annotation task.
1 code implementation • 17 Oct 2017 • Claire Bonial, Matthew Marge, Ron artstein, Ashley Foots, Felix Gervits, Cory J. Hayes, Cassidy Henry, Susan G. Hill, Anton Leuski, Stephanie M. Lukin, Pooja Moolchandani, Kimberly A. Pollard, David Traum, Clare R. Voss
We describe the adaptation and refinement of a graphical user interface designed to facilitate a Wizard-of-Oz (WoZ) approach to collecting human-robot dialogue data.
1 code implementation • ACL 2018 • Lifu Huang, Heng Ji, Kyunghyun Cho, Clare R. Voss
Most previous event extraction studies have relied heavily on features derived from annotated event mentions, thus cannot be applied to new event types without annotation effort.
4 code implementations • 15 Feb 2017 • Jingbo Shang, Jialu Liu, Meng Jiang, Xiang Ren, Clare R. Voss, Jiawei Han
As one of the fundamental tasks in text analysis, phrase mining aims at extracting quality phrases from a text corpus.
3 code implementations • 27 Oct 2016 • Xiang Ren, Zeqiu Wu, Wenqi He, Meng Qu, Clare R. Voss, Heng Ji, Tarek F. Abdelzaher, Jiawei Han
We propose a novel domain-independent framework, called CoType, that runs a data-driven text segmentation algorithm to extract entity mentions, and jointly embeds entity mentions, relation mentions, text features and type labels into two low-dimensional spaces (for entity and relation mentions respectively), where, in each space, objects whose types are close will also have similar representations.
Ranked #11 on
Relation Extraction
on NYT11-HRL
3 code implementations • 17 Feb 2016 • Xiang Ren, Wenqi He, Meng Qu, Clare R. Voss, Heng Ji, Jiawei Han
Current systems of fine-grained entity typing use distant supervision in conjunction with existing knowledge bases to assign categories (type labels) to entity mentions.