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09/21/2023
A Chinese Prompt Attack Dataset for LLMs with Evil Content
Large Language Models (LLMs) present significant priority in text unders...
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08/16/2023
Hierarchical Topological Ordering with Conditional Independence Test for Limited Time Series
Learning directed acyclic graphs (DAGs) to identify causal relations und...
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05/25/2023
Quantitatively Measuring and Contrastively Exploring Heterogeneity for Domain Generalization
Domain generalization (DG) is a prevalent problem in real-world applicat...
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04/28/2023
RexUIE: A Recursive Method with Explicit Schema Instructor for Universal Information Extraction
Universal Information Extraction (UIE) is an area of interest due to the...
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04/24/2023
Universal Domain Adaptation via Compressive Attention Matching
Universal domain adaptation (UniDA) aims to transfer knowledge from the ...
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02/14/2023
IDEAL: Toward High-efficiency Device-Cloud Collaborative and Dynamic Recommendation System
Recommendation systems have shown great potential to solve the informati...
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02/14/2023
Adaptive Value Decomposition with Greedy Marginal Contribution Computation for Cooperative Multi-Agent Reinforcement Learning
Real-world cooperation often requires intensive coordination among agent...
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12/12/2022
Instrumental Variables in Causal Inference and Machine Learning: A Survey
Causal inference is the process of using assumptions, study designs, and...
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12/04/2022
ConfounderGAN: Protecting Image Data Privacy with Causal Confounder
The success of deep learning is partly attributed to the availability of...
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11/28/2022
Learning From Good Trajectories in Offline Multi-Agent Reinforcement Learning
Offline multi-agent reinforcement learning (MARL) aims to learn effectiv...
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11/18/2022
Confounder Balancing for Instrumental Variable Regression with Latent Variable
This paper studies the confounding effects from the unmeasured confounde...
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11/15/2022
Exploiting Contrastive Learning and Numerical Evidence for Improving Confusing Legal Judgment Prediction
Given the fact description text of a legal case, legal judgment predicti...
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10/25/2022
Learning Individual Treatment Effects under Heterogeneous Interference in Networks
Estimates of individual treatment effects from networked observational d...
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10/16/2022
Investigating the Robustness of Natural Language Generation from Logical Forms via Counterfactual Samples
The aim of Logic2Text is to generate controllable and faithful texts con...
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10/06/2022
Domain Generalization via Contrastive Causal Learning
Domain Generalization (DG) aims to learn a model that can generalize wel...
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09/12/2022
DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization
Device Model Generalization (DMG) is a practical yet under-investigated ...
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08/23/2022
Treatment Effect Estimation with Unmeasured Confounders in Data Fusion
In the presence of unmeasured confounders, we address the problem of tre...
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08/19/2022
Personalizing Intervened Network for Long-tailed Sequential User Behavior Modeling
In an era of information explosion, recommendation systems play an impor...
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08/07/2022
Label-Efficient Domain Generalization via Collaborative Exploration and Generalization
Considerable progress has been made in domain generalization (DG) which ...
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06/20/2022
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?
Collaborative multi-agent reinforcement learning (MARL) has been widely ...
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06/07/2022
Collaborative Intelligence Orchestration: Inconsistency-Based Fusion of Semi-Supervised Learning and Active Learning
While annotating decent amounts of data to satisfy sophisticated learnin...
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01/19/2022
Debiased Graph Neural Networks with Agnostic Label Selection Bias
Most existing Graph Neural Networks (GNNs) are proposed without consider...
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12/20/2021
Multi-agent Communication with Graph Information Bottleneck under Limited Bandwidth
Recent studies have shown that introducing communication between agents ...
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11/11/2021
Edge-Cloud Polarization and Collaboration: A Comprehensive Survey
Influenced by the great success of deep learning via cloud computing and...
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11/09/2021
Unified Group Fairness on Federated Learning
Federated learning (FL) has emerged as an important machine learning par...
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11/05/2021
Dialogue Inspectional Summarization with Factual Inconsistency Awareness
Dialogue summarization has been extensively studied and applied, where t...
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10/13/2021
Do We Need to Directly Access the Source Datasets for Domain Generalization?
Domain generalization (DG) aims to learn a generalizable model from mult...
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10/08/2021
Stable Prediction on Graphs with Agnostic Distribution Shift
Graph is a flexible and effective tool to represent complex structures i...
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10/04/2021
Learning Domain-Invariant Relationship with Instrumental Variable for Domain Generalization
Domain generalization (DG) aims to learn from multiple source domains a ...
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10/02/2021
Domain-Specific Bias Filtering for Single Labeled Domain Generalization
Domain generalization (DG) utilizes multiple labeled source datasets to ...
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07/13/2021
Auto IV: Counterfactual Prediction via Automatic Instrumental Variable Decomposition
Instrumental variables (IVs), sources of treatment randomization that ar...
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06/30/2021
Distributionally Robust Learning with Stable Adversarial Training
Machine learning algorithms with empirical risk minimization are vulnera...
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06/01/2021
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning
Centralized Training with Decentralized Execution (CTDE) has been a popu...
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05/29/2021
Analysis and Applications of Class-wise Robustness in Adversarial Training
Adversarial training is one of the most effective approaches to improve ...
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05/17/2021
Dependency Parsing as MRC-based Span-Span Prediction
Higher-order methods for dependency parsing can partially but not fully ...
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05/12/2021
BertGCN: Transductive Text Classification by Combining GCN and BERT
In this work, we propose BertGCN, a model that combines large scale pret...
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11/07/2020
Interventional Domain Adaptation
Domain adaptation (DA) aims to transfer discriminative features learned ...
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10/18/2020
Federated Unsupervised Representation Learning
To leverage enormous unlabeled data on distributed edge devices, we form...
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08/16/2020
DeVLBert: Learning Deconfounded Visio-Linguistic Representations
In this paper, we propose to investigate the problem of out-of-domain vi...
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08/16/2020
Poet: Product-oriented Video Captioner for E-commerce
In e-commerce, a growing number of user-generated videos are used for pr...
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08/13/2020
MTBRN: Multiplex Target-Behavior Relation Enhanced Network for Click-Through Rate Prediction
Click-through rate (CTR) prediction is a critical task for many industri...
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06/29/2020
Decorrelated Clustering with Data Selection Bias
Most of existing clustering algorithms are proposed without considering ...
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06/24/2020
Comprehensive Information Integration Modeling Framework for Video Titling
In e-commerce, consumer-generated videos, which in general deliver consu...
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06/18/2020
Algorithmic Decision Making with Conditional Fairness
Nowadays fairness issues have raised great concerns in decision-making s...
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06/12/2020
Learning Decomposed Representation for Counterfactual Inference
One fundamental problem in the learning treatment effect from observatio...
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06/09/2020
Stable Prediction via Leveraging Seed Variable
In this paper, we focus on the problem of stable prediction across unkno...
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06/08/2020
Invariant Adversarial Learning for Distributional Robustness
Machine learning algorithms with empirical risk minimization are vulnera...
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06/08/2020
Balance-Subsampled Stable Prediction
In machine learning, it is commonly assumed that training and test data ...
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01/31/2020
Stable Prediction with Model Misspecification and Agnostic Distribution Shift
For many machine learning algorithms, two main assumptions are required ...
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06/16/2018