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09/21/2023
How Robust is Google's Bard to Adversarial Image Attacks?
Multimodal Large Language Models (MLLMs) that integrate text and other m...
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09/04/2023
Benchmarking Large Language Models in Retrieval-Augmented Generation
Retrieval-Augmented Generation (RAG) is a promising approach for mitigat...
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08/13/2023
CDR: Conservative Doubly Robust Learning for Debiased Recommendation
In recommendation systems (RS), user behavior data is observational rath...
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08/10/2023
Homophily-enhanced Structure Learning for Graph Clustering
Graph clustering is a fundamental task in graph analysis, and recent adv...
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08/04/2023
AdvFAS: A robust face anti-spoofing framework against adversarial examples
Ensuring the reliability of face recognition systems against presentatio...
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07/25/2023
Text-oriented Modality Reinforcement Network for Multimodal Sentiment Analysis from Unaligned Multimodal Sequences
Multimodal Sentiment Analysis (MSA) aims to mine sentiment information f...
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07/19/2023
Information Retrieval Meets Large Language Models: A Strategic Report from Chinese IR Community
The research field of Information Retrieval (IR) has evolved significant...
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06/17/2023
OpenGSL: A Comprehensive Benchmark for Graph Structure Learning
Graph Neural Networks (GNNs) have emerged as the de facto standard for r...
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05/24/2023
How Graph Convolutions Amplify Popularity Bias for Recommendation?
Graph convolutional networks (GCNs) have become prevalent in recommender...
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05/18/2023
Learning In-context Learning for Named Entity Recognition
Named entity recognition in real-world applications suffers from the div...
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05/16/2023
Retentive or Forgetful? Diving into the Knowledge Memorizing Mechanism of Language Models
Memory is one of the most essential cognitive functions serving as a rep...
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05/08/2023
Retriever and Ranker Framework with Probabilistic Hard Negative Sampling for Code Search
Pretrained Language Models (PLMs) have emerged as the state-of-the-art p...
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04/11/2023
Life Regression based Patch Slimming for Vision Transformers
Vision transformers have achieved remarkable success in computer vision ...
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02/09/2023
Adap-τ: Adaptively Modulating Embedding Magnitude for Recommendation
Recent years have witnessed the great successes of embedding-based metho...
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02/07/2023
FFHR: Fully and Flexible Hyperbolic Representation for Knowledge Graph Completion
Learning hyperbolic embeddings for knowledge graph (KG) has gained incre...
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02/07/2023
On the Theories Behind Hard Negative Sampling for Recommendation
Negative sampling has been heavily used to train recommender models on l...
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12/28/2022
Robust Sequence Networked Submodular Maximization
In this paper, we study the Robust optimization for sequence Networked s...
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12/15/2022
Hierarchical Codebook Design for Near-Field MmWave MIMO Communications Systems
Communications system with analog or hybrid analog/digital architectures...
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11/27/2022
Unbiased Knowledge Distillation for Recommendation
As a promising solution for model compression, knowledge distillation (K...
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06/15/2022
A Comprehensive Survey on Deep Clustering: Taxonomy, Challenges, and Future Directions
Clustering is a fundamental machine learning task which has been widely ...
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06/08/2022
Dap-FL: Federated Learning flourishes by adaptive tuning and secure aggregation
Federated learning (FL), an attractive and promising distributed machine...
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05/30/2022
BinauralGrad: A Two-Stage Conditional Diffusion Probabilistic Model for Binaural Audio Synthesis
Binaural audio plays a significant role in constructing immersive augmen...
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05/09/2022
NaturalSpeech: End-to-End Text to Speech Synthesis with Human-Level Quality
Text to speech (TTS) has made rapid progress in both academia and indust...
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05/07/2022
Time-Series Domain Adaptation via Sparse Associative Structure Alignment: Learning Invariance and Variance
Domain adaptation on time-series data is often encountered in the indust...
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04/08/2022
Communication-Efficient Cluster Federated Learning in Large-scale Peer-to-Peer Networks
A traditional federated learning (FL) allows clients to collaboratively ...
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03/23/2022
Few-shot Named Entity Recognition with Self-describing Networks
Few-shot NER needs to effectively capture information from limited insta...
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02/22/2022
KuaiRec: A Fully-observed Dataset for Recommender Systems
Recommender systems are usually developed and evaluated on the historica...
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02/10/2022
IHGNN: Interactive Hypergraph Neural Network for Personalized Product Search
A good personalized product search (PPS) system should not only focus on...
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01/07/2022
On the Effectiveness of Sampled Softmax Loss for Item Recommendation
Learning objectives of recommender models remain largely unexplored. Mos...
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09/16/2021
Popularity Bias Is Not Always Evil: Disentangling Benign and Harmful Bias for Recommendation
Recommender system usually suffers from severe popularity bias – the col...
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09/16/2021
PDAugment: Data Augmentation by Pitch and Duration Adjustments for Automatic Lyrics Transcription
Automatic lyrics transcription (ALT), which can be regarded as automatic...
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09/13/2021
Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention
Event detection has long been troubled by the trigger curse: overfitting...
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08/22/2021
DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network
Knowledge graph completion (KGC) has become a focus of attention across ...
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08/20/2021
MM-ViT: Multi-Modal Video Transformer for Compressed Video Action Recognition
This paper presents a pure transformer-based approach, dubbed the Multi-...
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08/12/2021
Distilling Holistic Knowledge with Graph Neural Networks
Knowledge Distillation (KD) aims at transferring knowledge from a larger...
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08/05/2021
Time-aware Path Reasoning on Knowledge Graph for Recommendation
Reasoning on knowledge graph (KG) has been studied for explainable recom...
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06/30/2021
Mutual-GAN: Towards Unsupervised Cross-Weather Adaptation with Mutual Information Constraint
Convolutional neural network (CNN) have proven its success for semantic ...
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05/28/2021
CausCF: Causal Collaborative Filtering for RecommendationEffect Estimation
To improve user experience and profits of corporations, modern industria...
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05/10/2021
AutoDebias: Learning to Debias for Recommendation
Recommender systems rely on user behavior data like ratings and clicks t...
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03/23/2021
A General Framework for Learning Prosodic-Enhanced Representation of Rap Lyrics
Learning and analyzing rap lyrics is a significant basis for many web ap...
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02/02/2021
GCF-Net: Gated Clip Fusion Network for Video Action Recognition
In recent years, most of the accuracy gains for video action recognition...
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12/22/2020
Time Series Domain Adaptation via Sparse Associative Structure Alignment
Domain adaptation on time series data is an important but challenging ta...
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11/16/2020
CoSam: An Efficient Collaborative Adaptive Sampler for Recommendation
Sampling strategies have been widely applied in many recommendation syst...
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11/16/2020
SamWalker++: recommendation with informative sampling strategy
Recommendation from implicit feedback is a highly challenging task due t...
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10/29/2020
Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System
The general aim of the recommender system is to provide personalized sug...
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10/23/2020
On the Equivalence of Decoupled Graph Convolution Network and Label Propagation
The original design of Graph Convolution Network (GCN) couples feature t...
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10/07/2020
Bias and Debias in Recommender System: A Survey and Future Directions
While recent years have witnessed a rapid growth of research papers on r...
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09/03/2020
HiFiSinger: Towards High-Fidelity Neural Singing Voice Synthesis
High-fidelity singing voices usually require higher sampling rate (e.g.,...
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08/03/2020
Residual Frames with Efficient Pseudo-3D CNN for Human Action Recognition
Human action recognition is regarded as a key cornerstone in domains suc...
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07/22/2020