b'Xing Xie'

research

∙ 08/31/2023

Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations

Recommender models excel at providing domain-specific item recommendatio...

0 Xu Huang, et al. ∙

research

∙ 08/28/2023

Can Transformer and GNN Help Each Other?

Although Transformer has achieved great success in natural language proc...

0 Peiyan Zhang, et al. ∙

research

∙ 08/23/2023

From Instructions to Intrinsic Human Values – A Survey of Alignment Goals for Big Models

Big models, exemplified by Large Language Models (LLMs), are models typi...

0 Jing Yao, et al. ∙

research

∙ 08/21/2023

Foundation Model-oriented Robustness: Robust Image Model Evaluation with Pretrained Models

Machine learning has demonstrated remarkable performance over finite dat...

0 Peiyan Zhang, et al. ∙

research

∙ 08/05/2023

ConvFormer: Revisiting Transformer for Sequential User Modeling

Sequential user modeling, a critical task in personalized recommender sy...

0 Hao Wang, et al. ∙

research

∙ 08/04/2023

Frustratingly Easy Model Generalization by Dummy Risk Minimization

Empirical risk minimization (ERM) is a fundamental machine learning para...

0 Juncheng Wang, et al. ∙

research

∙ 08/04/2023

DIVERSIFY: A General Framework for Time Series Out-of-distribution Detection and Generalization

Time series remains one of the most challenging modalities in machine le...

0 Wang Lu, et al. ∙

research

∙ 07/14/2023

EmotionPrompt: Leveraging Psychology for Large Language Models Enhancement via Emotional Stimulus

Large language models (LLMs) have achieved significant performance in ma...

0 Cheng Li, et al. ∙

research

∙ 07/06/2023

A Survey on Evaluation of Large Language Models

Large language models (LLMs) are gaining increasing popularity in both a...

0 Yupeng Chang, et al. ∙

research

∙ 06/25/2023

FedSampling: A Better Sampling Strategy for Federated Learning

Federated learning (FL) is an important technique for learning models fr...

0 Tao Qi, et al. ∙

research

∙ 06/17/2023

KEST: Kernel Distance Based Efficient Self-Training for Improving Controllable Text Generation

Self-training (ST) has come to fruition in language understanding tasks ...

0 Yuxi Feng, et al. ∙

research

∙ 06/08/2023

PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization

Instruction tuning large language models (LLMs) remains a challenging ta...

0 Yidong Wang, et al. ∙

research

∙ 06/07/2023

PromptBench: Towards Evaluating the Robustness of Large Language Models on Adversarial Prompts

The increasing reliance on Large Language Models (LLMs) across academia ...

0 Kaijie Zhu, et al. ∙

research

∙ 05/23/2023

To Copy Rather Than Memorize: A Vertical Learning Paradigm for Knowledge Graph Completion

Embedding models have shown great power in knowledge graph completion (K...

0 Rui Li, et al. ∙

research

∙ 05/23/2023

Continual Learning on Dynamic Graphs via Parameter Isolation

Many real-world graph learning tasks require handling dynamic graphs whe...

0 Peiyan Zhang, et al. ∙

research

∙ 05/17/2023

Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor Watermark

Large language models (LLMs) have demonstrated powerful capabilities in ...

0 Wenjun Peng, et al. ∙

research

∙ 04/27/2023

Towards Explainable Collaborative Filtering with Taste Clusters Learning

Collaborative Filtering (CF) is a widely used and effective technique fo...

0 Yuntao Du, et al. ∙

research

∙ 04/04/2023

Exploring Vision-Language Models for Imbalanced Learning

Vision-Language models (VLMs) that use contrastive language-image pre-tr...

0 Yidong Wang, et al. ∙

research

∙ 03/17/2023

IRGen: Generative Modeling for Image Retrieval

While generative modeling has been ubiquitous in natural language proces...

0 Yidan Zhang, et al. ∙

research

∙ 03/15/2023

DualFair: Fair Representation Learning at Both Group and Individual Levels via Contrastive Self-supervision

Algorithmic fairness has become an important machine learning problem, e...

0 Sungwon Han, et al. ∙

research

∙ 03/02/2023

Distillation from Heterogeneous Models for Top-K Recommendation

Recent recommender systems have shown remarkable performance by using an...

0 SeongKu Kang, et al. ∙

research

∙ 02/27/2023

FedCLIP: Fast Generalization and Personalization for CLIP in Federated Learning

Federated learning (FL) has emerged as a new paradigm for privacy-preser...

0 Wang Lu, et al. ∙

research

∙ 02/22/2023

On the Robustness of ChatGPT: An Adversarial and Out-of-distribution Perspective

ChatGPT is a recent chatbot service released by OpenAI and is receiving ...

0 Jindong Wang, et al. ∙

research

∙ 01/26/2023

SoftMatch: Addressing the Quantity-Quality Trade-off in Semi-supervised Learning

The critical challenge of Semi-Supervised Learning (SSL) is how to effec...

0 Hao Chen, et al. ∙

research

∙ 12/21/2022

Generating Multiple-Length Summaries via Reinforcement Learning for Unsupervised Sentence Summarization

Sentence summarization shortens given texts while maintaining core conte...

0 Dongmin Hyun, et al. ∙

research

∙ 12/16/2022

DuNST: Dual Noisy Self Training for Semi-Supervised Controllable Text Generation

Self-training (ST) has prospered again in language understanding by augm...

0 Yuxi Feng, et al. ∙

research

∙ 11/30/2022

CDSM: Cascaded Deep Semantic Matching on Textual Graphs Leveraging Ad-hoc Neighbor Selection

Deep semantic matching aims to discriminate the relationship between doc...

0 Jing Yao, et al. ∙

research

∙ 11/24/2022

Prototypical Fine-tuning: Towards Robust Performance Under Varying Data Sizes

In this paper, we move towards combining large parametric models with no...

0 Yiqiao Jin, et al. ∙

research

∙ 11/20/2022

An Embarrassingly Simple Baseline for Imbalanced Semi-Supervised Learning

Semi-supervised learning (SSL) has shown great promise in leveraging unl...

0 Hao Chen, et al. ∙

research

∙ 11/15/2022

GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective

Pre-trained language models (PLMs) are known to improve the generalizati...

0 Linyi Yang, et al. ∙

research

∙ 11/14/2022

Evade the Trap of Mediocrity: Promoting Diversity and Novelty in Text Generation via Concentrating Attention

Recently, powerful Transformer architectures have proven superior in gen...

0 Wenhao Li, et al. ∙

research

∙ 11/07/2022

FIXED: Frustratingly Easy Domain Generalization with Mixup

Domain generalization (DG) aims to learn a generalizable model from mult...

0 Wang Lu, et al. ∙

research

∙ 10/26/2022

Learning on Large-scale Text-attributed Graphs via Variational Inference

This paper studies learning on text-attributed graphs (TAGs), where each...

0 Jianan Zhao, et al. ∙

research

∙ 10/22/2022

Recurrence Boosts Diversity! Revisiting Recurrent Latent Variable in Transformer-Based Variational AutoEncoder for Diverse Text Generation

Variational Auto-Encoder (VAE) has been widely adopted in text generatio...

0 Jinyi Hu, et al. ∙

research

∙ 10/18/2022

RAPO: An Adaptive Ranking Paradigm for Bilingual Lexicon Induction

Bilingual lexicon induction induces the word translations by aligning in...

0 Zhoujin Tian, et al. ∙

research

∙ 10/17/2022

Test-Time Training for Graph Neural Networks

Graph Neural Networks (GNNs) have made tremendous progress in the graph ...

3 Yiqi Wang, et al. ∙

research

∙ 10/17/2022

Effective and Efficient Query-aware Snippet Extraction for Web Search

Query-aware webpage snippet extraction is widely used in search engines ...

0 Jingwei Yi, et al. ∙

research

∙ 10/13/2022

Self-explaining deep models with logic rule reasoning

We present SELOR, a framework for integrating self-explaining capabiliti...

0 Seungeon Lee, et al. ∙

research

∙ 09/15/2022

Generalized Representations Learning for Time Series Classification

Time series classification is an important problem in real world. Due to...

0 Wang Lu, et al. ∙

research

∙ 09/01/2022

Towards Optimization and Model Selection for Domain Generalization: A Mixup-guided Solution

The distribution shifts between training and test data typically undermi...

0 Wang Lu, et al. ∙

research

∙ 08/12/2022

USB: A Unified Semi-supervised Learning Benchmark

Semi-supervised learning (SSL) improves model generalization by leveragi...

0 Yidong Wang, et al. ∙

research

∙ 08/03/2022

Equivariant Disentangled Transformation for Domain Generalization under Combination Shift

Machine learning systems may encounter unexpected problems when the data...

0 Yivan Zhang, et al. ∙

research

∙ 08/02/2022

Geometric Interaction Augmented Graph Collaborative Filtering

Graph-based collaborative filtering is capable of capturing the essentia...

0 Yiding Zhang, et al. ∙

research

∙ 07/25/2022

Domain-invariant Feature Exploration for Domain Generalization

Deep learning has achieved great success in the past few years. However,...

0 Wang Lu, et al. ∙

research

∙ 07/19/2022

FedX: Unsupervised Federated Learning with Cross Knowledge Distillation

This paper presents FedX, an unsupervised federated learning framework. ...

0 Sungwon Han, et al. ∙

research

∙ 07/13/2022

Fuse It More Deeply! A Variational Transformer with Layer-Wise Latent Variable Inference for Text Generation

The past several years have witnessed Variational Auto-Encoder's superio...

15 Jinyi Hu, et al. ∙

research

∙ 06/28/2022

Cooperative Retriever and Ranker in Deep Recommenders

Deep recommender systems jointly leverage the retrieval and ranking oper...

4 Xu Huang, et al. ∙

research

∙ 06/26/2022

Two-Stage Neural Contextual Bandits for Personalised News Recommendation

We consider the problem of personalised news recommendation where each u...

1 Mengyan Zhang, et al. ∙

research

∙ 06/26/2022

Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network

Session-based recommendation (SBR) aims to predict the user next action ...

0 Peiyan Zhang, et al. ∙

research

∙ 06/26/2022

Evolutionary Preference Learning via Graph Nested GRU ODE for Session-based Recommendation

Session-based recommendation (SBR) aims to predict the user next action ...

0 Jiayan Guo, et al. ∙

Xing Xie

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