no code implementations • EMNLP 2020 • Manling Li, Qi Zeng, Ying Lin, Kyunghyun Cho, Heng Ji, Jonathan May, Nathanael Chambers, Clare Voss
Event schemas can guide our understanding and ability to make predictions with respect to what might happen next.
no code implementations • 22 Jun 2024 • Yash Kumar Lal, Vanya Cohen, Nathanael Chambers, Niranjan Balasubramanian, Raymond Mooney
A fundamental aspect of plans is the temporal order in which their steps needs to be executed, which reflects the underlying causal dependencies between them.
1 code implementation • 14 Feb 2023 • Mahnaz Koupaee, Greg Durrett, Nathanael Chambers, Niranjan Balasubramanian
Event scenarios are often complex and involve multiple event sequences connected through different entity participants.
no code implementations • 31 Jul 2022 • Sayontan Ghosh, Mahnaz Koupaee, Isabella Chen, Francis Ferraro, Nathanael Chambers, Niranjan Balasubramanian
This dataset contains inferable participant states; a counterfactual perturbation to each state; and the changes to the story that would be necessary if the counterfactual were true.
no code implementations • ACL 2021 • Mahnaz Koupaee, Greg Durrett, Nathanael Chambers, Niranjan Balasubramanian
Event language models represent plausible sequences of events.
no code implementations • Joint Conference on Lexical and Computational Semantics 2021 • Heeyoung Kwon, Nathanael Chambers, Niranjan Balasubramanian
We propose DiP, a Diverse Precondition generation system that can generate unique and diverse preconditions.
1 code implementation • Findings (ACL) 2021 • Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, Niranjan Balasubramanian
They are especially worse on questions whose answers are external to the narrative, thus providing a challenge for future QA and narrative understanding research.
no code implementations • ACL 2021 • Shih-ting Lin, Nathanael Chambers, Greg Durrett
We propose a single model that addresses both temporal ordering, sorting given events into the order they occurred, and event infilling, predicting new events which fit into an existing temporally-ordered sequence.
1 code implementation • Findings of the Association for Computational Linguistics 2020 • Heeyoung Kwon, Mahnaz Koupaee, Pratyush Singh, Gargi Sawhney, Anmol Shukla, Keerthi Kumar Kallur, Nathanael Chambers, Niranjan Balasubramanian
This paper introduces PeKo, a crowd-sourced annotation of preconditions between event pairs in newswire, an order of magnitude larger than prior text annotations.
1 code implementation • ACL 2020 • Radhika Gaonkar, Heeyoung Kwon, Mohaddeseh Bastan, Niranjan Balasubramanian, Nathanael Chambers
Predicting how events induce emotions in the characters of a story is typically seen as a standard multi-label classification task, which usually treats labels as anonymous classes to predict.
Ranked #1 on Emotion Classification on ROCStories
1 code implementation • CONLL 2020 • Noah Weber, Leena Shekhar, Heeyoung Kwon, Niranjan Balasubramanian, Nathanael Chambers
A SLDS is a dynamical system in which the latent dynamics of the system (i. e. how the state vector transforms over time) is controlled by top-level discrete switching variables.
no code implementations • WS 2019 • Nathanael Chambers, Timothy Forman, Catherine Griswold, Kevin Lu, Yogaish Khastgir, Stephen Steckler
Illicit activity on the Web often uses noisy text to obscure information between client and seller, such as the seller{'}s phone number.
1 code implementation • EMNLP 2018 • Noah Weber, Leena Shekhar, Niranjan Balasubramanian, Nathanael Chambers
This permits the decoder to softly decide what portions of the latent hierarchy to condition on by attending over the value embeddings for a given setting.
no code implementations • NAACL 2018 • Nathanael Chambers, Ben Fry, James McMasters
This paper describes a novel application of NLP models to detect denial of service attacks using only social media as evidence.
1 code implementation • TACL 2018 • Mohammad Javad Hosseini, Nathanael Chambers, Siva Reddy, Xavier R. Holt, Shay B. Cohen, Mark Johnson, Mark Steedman
We instead propose a scalable method that learns globally consistent similarity scores based on new soft constraints that consider both the structures across typed entailment graphs and inside each graph.
1 code implementation • 21 Nov 2017 • Noah Weber, Niranjan Balasubramanian, Nathanael Chambers
Robust and flexible event representations are important to many core areas in language understanding.
no code implementations • IJCNLP 2017 • Bill McDowell, Nathanael Chambers, Alex Ororbia II, er, David Reitter
Within this prediction reranking framework, we propose an alternative scoring function, showing an 8. 8{\%} relative gain over the original CAEVO.
no code implementations • WS 2017 • Nasrin Mostafazadeh, Michael Roth, Annie Louis, Nathanael Chambers, James Allen
The LSDSem{'}17 shared task is the Story Cloze Test, a new evaluation for story understanding and script learning.
no code implementations • WS 2017 • Nathanael Chambers
This paper analyzes the narrative event cloze test and its recent evolution.
no code implementations • WS 2017 • Kevin McKelvey, Peter Goutzounis, Stephen da Cruz, Nathanael Chambers
Recent work on entity linking attempts to resolve mentions to knowledge base entries, like a wikipedia page, but linking is unfortunately limited to well-known entities with pre-built pages.
no code implementations • 6 Apr 2016 • Nasrin Mostafazadeh, Nathanael Chambers, Xiaodong He, Devi Parikh, Dhruv Batra, Lucy Vanderwende, Pushmeet Kohli, James Allen
We created a new corpus of ~50k five-sentence commonsense stories, ROCStories, to enable this evaluation.
no code implementations • TACL 2014 • Nathanael Chambers, Taylor Cassidy, Bill McDowell, Steven Bethard
We experiment on the densest event graphs to date and show a 14{\%} gain over state-of-the-art.
Ranked #2 on Temporal Information Extraction on TimeBank