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09/16/2023
Enhancing Large Language Model Induced Task-Oriented Dialogue Systems Through Look-Forward Motivated Goals
Recently, the development of large language models (LLMs) has been signi...
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06/22/2023
Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs
The task of empowering large language models (LLMs) to accurately expres...
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06/16/2023
Unlocking the Potential of User Feedback: Leveraging Large Language Model as User Simulator to Enhance Dialogue System
Dialogue systems and large language models (LLMs) have gained considerab...
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06/14/2023
PoetryDiffusion: Towards Joint Semantic and Metrical Manipulation in Poetry Generation
Poetry generation is a typical and popular task in natural language gene...
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06/14/2023
LargeST: A Benchmark Dataset for Large-Scale Traffic Forecasting
Traffic forecasting plays a critical role in smart city initiatives and ...
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06/07/2023
Proximity-Informed Calibration for Deep Neural Networks
Confidence calibration is central to providing accurate and interpretabl...
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05/31/2023
Explanations as Features: LLM-Based Features for Text-Attributed Graphs
Representation learning on text-attributed graphs (TAGs) has become a cr...
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05/30/2023
GraphCleaner: Detecting Mislabelled Samples in Popular Graph Learning Benchmarks
Label errors have been found to be prevalent in popular text, vision, an...
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05/23/2023
SPEECH: Structured Prediction with Energy-Based Event-Centric Hyperspheres
Event-centric structured prediction involves predicting structured outpu...
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05/22/2023
EntRED: Benchmarking Relation Extraction with Fewer Shortcuts
Entity names play an effective role in relation extraction (RE) and ofte...
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05/10/2023
Towards Better Graph Representation Learning with Parameterized Decomposition Filtering
Proposing an effective and flexible matrix to represent a graph is a fun...
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05/02/2023
Great Models Think Alike: Improving Model Reliability via Inter-Model Latent Agreement
Reliable application of machine learning is of primary importance to the...
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04/17/2023
TAP: A Comprehensive Data Repository for Traffic Accident Prediction in Road Networks
Road safety is a major global public health concern. Effective traffic c...
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02/25/2023
RETEXO: Scalable Neural Network Training over Distributed Graphs
Graph neural networks offer a promising approach to supervised learning ...
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02/06/2023
Trust, but Verify: Using Self-Supervised Probing to Improve Trustworthiness
Trustworthy machine learning is of primary importance to the practical d...
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01/30/2023
Do We Really Need Graph Neural Networks for Traffic Forecasting?
Spatio-temporal graph neural networks (STGNN) have become the most popul...
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12/27/2022
A Generalization of ViT/MLP-Mixer to Graphs
Graph Neural Networks (GNNs) have shown great potential in the field of ...
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11/29/2022
Birds of a Feather Trust Together: Knowing When to Trust a Classifier via Adaptive Neighborhood Aggregation
How do we know when the predictions made by a classifier can be trusted?...
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11/25/2022
Expanding Small-Scale Datasets with Guided Imagination
The power of Deep Neural Networks (DNNs) depends heavily on the training...
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10/24/2022
Reachability-Aware Laplacian Representation in Reinforcement Learning
In Reinforcement Learning (RL), Laplacian Representation (LapRep) is a t...
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10/15/2022
MGNNI: Multiscale Graph Neural Networks with Implicit Layers
Recently, implicit graph neural networks (GNNs) have been proposed to ca...
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09/25/2022
Joint Triplet Loss Learning for Next New POI Recommendation
Sparsity of the User-POI matrix is a well established problem for next P...
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09/19/2022
Probing Spurious Correlations in Popular Event-Based Rumor Detection Benchmarks
As social media becomes a hotbed for the spread of misinformation, the c...
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09/17/2022
Flashlight: Scalable Link Prediction with Effective Decoders
Link prediction (LP) has been recognized as an important task in graph l...
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08/23/2022
Neural PCA for Flow-Based Representation Learning
Of particular interest is to discover useful representations solely from...
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08/18/2022
A Scalable, Interpretable, Verifiable Differentiable Logic Gate Convolutional Neural Network Architecture From Truth Tables
We propose 𝒯ruth 𝒯able net (𝒯𝒯net), a novel Convolutional Neural Network...
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06/15/2022
ARES: Locally Adaptive Reconstruction-based Anomaly Scoring
How can we detect anomalies: that is, samples that significantly differ ...
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05/08/2022
GRAPHCACHE: Message Passing as Caching for Sentence-Level Relation Extraction
Entity types and textual context are essential properties for sentence-l...
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05/08/2022
Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis
Recent literature focuses on utilizing the entity information in the sen...
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05/06/2022
LPGNet: Link Private Graph Networks for Node Classification
Classification tasks on labeled graph-structured data have many importan...
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05/05/2022
Dangling-Aware Entity Alignment with Mixed High-Order Proximities
We study dangling-aware entity alignment in knowledge graphs (KGs), whic...
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02/22/2022
EIGNN: Efficient Infinite-Depth Graph Neural Networks
Graph neural networks (GNNs) are widely used for modelling graph-structu...
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01/30/2022
The Geometry of Robust Value Functions
The space of value functions is a fundamental concept in reinforcement l...
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12/18/2021
Time-Aware Neighbor Sampling for Temporal Graph Networks
We present a new neighbor sampling method on temporal graphs. In a tempo...
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12/10/2021
LUNAR: Unifying Local Outlier Detection Methods via Graph Neural Networks
Many well-established anomaly detection methods use the distance of a sa...
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12/02/2021
Probabilistic Contrastive Loss for Self-Supervised Learning
This paper proposes a probabilistic contrastive loss function for self-s...
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12/01/2021
Structure-Aware Label Smoothing for Graph Neural Networks
Representing a label distribution as a one-hot vector is a common practi...
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11/11/2021
Benefit-aware Early Prediction of Health Outcomes on Multivariate EEG Time Series
Given a cardiac-arrest patient being monitored in the ICU (intensive car...
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10/25/2021
SSMF: Shifting Seasonal Matrix Factorization
Given taxi-ride counts information between departure and destination loc...
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10/09/2021
Deep Long-Tailed Learning: A Survey
Deep long-tailed learning, one of the most challenging problems in visua...
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08/26/2021
Spatio-Temporal Graph Contrastive Learning
Deep learning models are modern tools for spatio-temporal graph (STG) fo...
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07/20/2021
Test-Agnostic Long-Tailed Recognition by Test-Time Aggregating Diverse Experts with Self-Supervision
Existing long-tailed recognition methods, aiming to train class-balance ...
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07/12/2021
Towards Better Laplacian Representation in Reinforcement Learning with Generalized Graph Drawing
The Laplacian representation recently gains increasing attention for rei...
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06/13/2021
Graph Neural Network-Based Anomaly Detection in Multivariate Time Series
Given high-dimensional time series data (e.g., sensor data), how can we ...
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06/08/2021
Sketch-Based Streaming Anomaly Detection in Dynamic Graphs
Given a stream of graph edges from a dynamic graph, how can we assign an...
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06/07/2021
MemStream: Memory-Based Anomaly Detection in Multi-Aspect Streams with Concept Drift
Given a stream of entries over time in a multi-aspect data setting where...
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04/04/2021
Isconna: Streaming Anomaly Detection with Frequency and Patterns
An edge stream is a common form of presentation of dynamic networks. It ...
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03/20/2021
PathEnum: Towards Real-Time Hop-Constrained s-t Path Enumeration
We study the hop-constrained s-t path enumeration (HcPE) problem, which ...
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02/12/2021
Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning
Contrastive self-supervised learning (CSL) leverages unlabeled data to t...
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12/30/2020