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09/17/2023
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
The driving factors behind the development of large language models (LLM...
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09/16/2023
PDFTriage: Question Answering over Long, Structured Documents
Large Language Models (LLMs) have issues with document question answerin...
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09/02/2023
Bias and Fairness in Large Language Models: A Survey
Rapid advancements of large language models (LLMs) have enabled the proc...
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08/22/2023
Knowledge Graph Prompting for Multi-Document Question Answering
The 'pre-train, prompt, predict' paradigm of large language models (LLMs...
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07/29/2023
Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback
A key technology for the development of large language models (LLMs) inv...
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07/20/2023
FigCaps-HF: A Figure-to-Caption Generative Framework and Benchmark with Human Feedback
Captions are crucial for understanding scientific visualizations and doc...
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07/08/2023
Fairness-Aware Graph Neural Networks: A Survey
Graph Neural Networks (GNNs) have become increasingly important due to t...
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06/20/2023
A Model-free Closeness-of-influence Test for Features in Supervised Learning
Understanding the effect of a feature vector x ∈ℝ^d on the response valu...
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03/28/2023
Structured Dynamic Pricing: Optimal Regret in a Global Shrinkage Model
We consider dynamic pricing strategies in a streamed longitudinal data s...
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03/02/2023
DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data Preparation
Selecting relevant data subsets from large, unfamiliar datasets can be d...
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12/28/2022
A Hypergraph Neural Network Framework for Learning Hyperedge-Dependent Node Embeddings
In this work, we introduce a hypergraph representation learning framewor...
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12/28/2022
PersonaSAGE: A Multi-Persona Graph Neural Network
Graph Neural Networks (GNNs) have become increasingly important in recen...
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11/04/2022
Robustness of Fusion-based Multimodal Classifiers to Cross-Modal Content Dilutions
As multimodal learning finds applications in a wide variety of high-stak...
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09/30/2022
Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs
Temporal networks model a variety of important phenomena involving timed...
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08/18/2022
Implicit Session Contexts for Next-Item Recommendations
Session-based recommender systems capture the short-term interest of a u...
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06/08/2022
Network Report: A Structured Description for Network Datasets
The rapid development of network science and technologies depends on sha...
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05/28/2022
CyCLIP: Cyclic Contrastive Language-Image Pretraining
Recent advances in contrastive representation learning over paired image...
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11/04/2021
An Interpretable Graph Generative Model with Heterophily
Many models for graphs fall under the framework of edge-independent dot ...
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08/23/2021
Influence-guided Data Augmentation for Neural Tensor Completion
How can we predict missing values in multi-dimensional data (or tensors)...
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07/09/2021
Optimal Space and Time for Streaming Pattern Matching
In this work, we study longest common substring, pattern matching, and w...
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04/11/2021
Edge: Enriching Knowledge Graph Embeddings with External Text
Knowledge graphs suffer from sparsity which degrades the quality of repr...
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03/21/2021
Insight-centric Visualization Recommendation
Visualization recommendation systems simplify exploratory data analysis ...
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02/12/2021
Personalized Visualization Recommendation
Visualization recommendation work has focused solely on scoring visualiz...
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01/15/2021
Fundamental Tradeoffs in Distributionally Adversarial Training
Adversarial training is among the most effective techniques to improve t...
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10/23/2020
Heterogeneous Graphlets
In this paper, we introduce a generalization of graphlets to heterogeneo...
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10/14/2020
Graph Deep Factors for Forecasting
Deep probabilistic forecasting techniques have recently been proposed fo...
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09/28/2020
Graph Neural Networks with Heterophily
Graph Neural Networks (GNNs) have proven to be useful for many different...
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09/25/2020
A Context Integrated Relational Spatio-Temporal Model for Demand and Supply Forecasting
Traditional methods for demand forecasting only focus on modeling the te...
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09/25/2020
ML-based Visualization Recommendation: Learning to Recommend Visualizations from Data
Visualization recommendation seeks to generate, score, and recommend to ...
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09/21/2020
From Static to Dynamic Node Embeddings
We introduce a general framework for leveraging graph stream data for te...
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07/13/2020
Structured Policy Iteration for Linear Quadratic Regulator
Linear quadratic regulator (LQR) is one of the most popular frameworks t...
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12/22/2019
Approximate Maximum Matching in Random Streams
In this paper, we study the problem of finding a maximum matching in the...
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10/18/2019
Temporal Network Sampling
Temporal networks representing a stream of timestamped edges are seeming...
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08/22/2019
From Community to Role-based Graph Embeddings
Roles are sets of structurally similar nodes that are more similar to no...
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06/14/2019
Linear-time Hierarchical Community Detection
Community detection in graphs has many important and fundamental applica...
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06/12/2019
Higher-Order Ranking and Link Prediction: From Closing Triangles to Closing Higher-Order Motifs
In this paper, we introduce the notion of motif closure and describe hig...
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04/12/2019
Temporal Network Representation Learning
Networks evolve continuously over time with the addition, deletion, and ...
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01/28/2019
Heterogeneous Network Motifs
Many real-world applications give rise to large heterogeneous networks w...
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10/06/2018
Higher-order Spectral Clustering for Heterogeneous Graphs
Higher-order connectivity patterns such as small induced sub-graphs call...
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09/12/2018
Higher-order Graph Convolutional Networks
Following the success of deep convolutional networks in various vision a...
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07/20/2018
Attention Models in Graphs: A Survey
Graph-structured data arise naturally in many different application doma...
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05/07/2018
Predicting Graph Categories from Structural Properties
Complex networks are often categorized according to the underlying pheno...
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01/28/2018
HONE: Higher-Order Network Embeddings
This paper describes a general framework for learning Higher-Order Netwo...
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10/27/2017
Similarity-based Multi-label Learning
Multi-label classification is an important learning problem with many ap...
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10/25/2017
Inductive Representation Learning in Large Attributed Graphs
Graphs (networks) are ubiquitous and allow us to model entities (nodes) ...
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09/14/2017
A Framework for Generalizing Graph-based Representation Learning Methods
Random walks are at the heart of many existing deep learning algorithms ...
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09/13/2017
Network Classification and Categorization
To the best of our knowledge, this paper presents the first large-scale ...
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04/28/2017
Deep Feature Learning for Graphs
This paper presents a general graph representation learning framework ca...
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01/06/2017
Estimation of Graphlet Statistics
Graphlets are induced subgraphs of a large network and are important for...
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10/04/2016