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Found 32 papers, 8 papers with code
Event Representations with Tensor-based Compositions
Robust and flexible event representations are important to many core areas in language understanding.
Modeling Label Semantics for Predicting Emotional Reactions
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
Hierarchical Quantized Representations for Script Generation
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.
TellMeWhy: A Dataset for Answering Why-Questions in Narratives
They are especially worse on questions whose answers are external to the narrative, thus providing a challenge for future QA and narrative understanding research.
Learning Typed Entailment Graphs with Global Soft Constraints
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.
Modeling Complex Event Scenarios via Simple Entity-focused Questions
Event scenarios are often complex and involve multiple event sequences connected through different entity participants.
Generating Narrative Text in a Switching Dynamical System
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.
Modeling Preconditions in Text with a Crowd-sourced Dataset
This paper introduces PeKo, a crowd-sourced annotation of preconditions between event pairs in newswire, an order of magnitude larger than prior text annotations.
A Corpus and Evaluation Framework for Deeper Understanding of Commonsense Stories
We created a new corpus of ~50k five-sentence commonsense stories, ROCStories, to enable this evaluation.
Detecting Denial-of-Service Attacks from Social Media Text: Applying NLP to Computer Security
This paper describes a novel application of NLP models to detect denial of service attacks using only social media as evidence.
Behind the Scenes of an Evolving Event Cloze Test
This paper analyzes the narrative event cloze test and its recent evolution.
LSDSem 2017 Shared Task: The Story Cloze Test
The LSDSem{'}17 shared task is the Story Cloze Test, a new evaluation for story understanding and script learning.
Aligning Entity Names with Online Aliases on Twitter
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.
Event Ordering with a Generalized Model for Sieve Prediction Ranking
Within this prediction reranking framework, we propose an alternative scoring function, showing an 8. 8{\%} relative gain over the original CAEVO.
Dense Event Ordering with a Multi-Pass Architecture
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
Character-Based Models for Adversarial Phone Extraction: Preventing Human Sex Trafficking
Illicit activity on the Web often uses noisy text to obscure information between client and seller, such as the seller{'}s phone number.
Connecting the Dots: Event Graph Schema Induction with Path Language Modeling
Event schemas can guide our understanding and ability to make predictions with respect to what might happen next.
Conditional Generation of Temporally-ordered Event Sequences
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.
Toward Diverse Precondition Generation
We propose DiP, a Diverse Precondition generation system that can generate unique and diverse preconditions.
Don't Let Discourse Confine Your Model: Sequence Perturbations for Improved Event Language Models
Event language models represent plausible sequences of events.
PASTA: A Dataset for Modeling Participant States in Narratives
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.
