Search Results for author: Tim Weninger

Found 17 papers, 9 papers with code

H-EMD: A Hierarchical Earth Mover's Distance Method for Instance Segmentation

no code implementations2 Jun 2022 Peixian Liang, Yizhe Zhang, Yifan Ding, Jianxu Chen, Chinedu S. Madukoma, Tim Weninger, Joshua D. Shrout, Danny Z. Chen

We observe that probability maps by DL semantic segmentation models can be used to generate many possible instance candidates, and accurate instance segmentation can be achieved by selecting from them a set of "optimized" candidates as output instances.

Image Segmentation Instance Segmentation +1

Posthoc Verification and the Fallibility of the Ground Truth

1 code implementation NAACL (DADC) 2022 Yifan Ding, Nicholas Botzer, Tim Weninger

Metrics used in these evaluations are tied to the availability of well-defined ground truth labels, and these metrics typically do not allow for inexact matches.

Entity Linking

Survey Equivalence: A Procedure for Measuring Classifier Accuracy Against Human Labels

1 code implementation2 Jun 2021 Paul Resnick, Yuqing Kong, Grant Schoenebeck, Tim Weninger

We refer to such tasks as survey settings because the ground truth is defined through a survey of one or more human raters.

Reddit Entity Linking Dataset

no code implementations4 Jan 2021 Nicholas Botzer, Yifan Ding, Tim Weninger

We introduce and make publicly available an entity linking dataset from Reddit that contains 17, 316 linked entities, each annotated by three human annotators and then grouped into Gold, Silver, and Bronze to indicate inter-annotator agreement.

Entity Linking

Tri-Train: Automatic Pre-Fine Tuning between Pre-Training and Fine-Tuning for SciNER

no code implementations Findings of the Association for Computational Linguistics 2020 Qingkai Zeng, Wenhao Yu, Mengxia Yu, Tianwen Jiang, Tim Weninger, Meng Jiang

The training process of scientific NER models is commonly performed in two steps: i) Pre-training a language model by self-supervised tasks on huge data and ii) fine-tune training with small labelled data.

Language Modelling NER

HetSeq: Distributed GPU Training on Heterogeneous Infrastructure

1 code implementation25 Sep 2020 Yifan Ding, Nicholas Botzer, Tim Weninger

The present work describes HetSeq, a software package adapted from the popular PyTorch package that provides the capability to train large neural network models on heterogeneous infrastructure.

Image Classification Language Modelling +1

Automatic Discovery of Political Meme Genres with Diverse Appearances

no code implementations17 Jan 2020 William Theisen, Joel Brogan, Pamela Bilo Thomas, Daniel Moreira, Pascal Phoa, Tim Weninger, Walter Scheirer

This pipeline can ingest meme images from a social network, apply computer vision-based techniques to extract local features and index new images into a database, and then organize the memes into related genres.

Improved Forecasting of Cryptocurrency Price using Social Signals

no code implementations1 Jul 2019 Maria Glenski, Tim Weninger, Svitlana Volkova

Social media signals have been successfully used to develop large-scale predictive and anticipatory analytics.

Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources

no code implementations ACL 2018 Maria Glenski, Tim Weninger, Svitlana Volkova

In the age of social news, it is important to understand the types of reactions that are evoked from news sources with various levels of credibility.

Visualizing the Flow of Discourse with a Concept Ontology

1 code implementation23 Feb 2018 Baoxu Shi, Tim Weninger

Understanding and visualizing human discourse has long being a challenging task.

Argument Mining

Open-World Knowledge Graph Completion

1 code implementation9 Nov 2017 Baoxu Shi, Tim Weninger

Knowledge Graphs (KGs) have been applied to many tasks including Web search, link prediction, recommendation, natural language processing, and entity linking.

Entity Linking Link Prediction

ProjE: Embedding Projection for Knowledge Graph Completion

2 code implementations16 Nov 2016 Baoxu Shi, Tim Weninger

In this work, we present a shared variable neural network model called ProjE that fills-in missing information in a knowledge graph by learning joint embeddings of the knowledge graph's entities and edges, and through subtle, but important, changes to the standard loss function.

Fact Checking Feature Engineering +1

Growing Graphs with Hyperedge Replacement Graph Grammars

1 code implementation10 Aug 2016 Salvador Aguiñaga, Rodrigo Palacios, David Chiang, Tim Weninger

In experiments on large real world networks, we show that random graphs, generated from extracted graph grammars, exhibit a wide range of properties that are very similar to the original graphs.

Scalable Models for Computing Hierarchies in Information Networks

1 code implementation4 Jan 2016 Baoxu Shi, Tim Weninger

Information hierarchies are organizational structures that often used to organize and present large and complex information as well as provide a mechanism for effective human navigation.

Discriminative Predicate Path Mining for Fact Checking in Knowledge Graphs

1 code implementation20 Oct 2015 Baoxu Shi, Tim Weninger

Traditional fact checking by experts and analysts cannot keep pace with the volume of newly created information.

Fact Checking Knowledge Graphs +1

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