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08/24/2023
Dense Text-to-Image Generation with Attention Modulation
Existing text-to-image diffusion models struggle to synthesize realistic...
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05/28/2023
KoSBi: A Dataset for Mitigating Social Bias Risks Towards Safer Large Language Model Application
Large language models (LLMs) learn not only natural text generation abil...
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05/27/2023
Query-Efficient Black-Box Red Teaming via Bayesian Optimization
The deployment of large-scale generative models is often restricted by t...
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04/04/2023
Text-Conditioned Sampling Framework for Text-to-Image Generation with Masked Generative Models
Token-based masked generative models are gaining popularity for their fa...
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12/07/2022
Pivotal Role of Language Modeling in Recommender Systems: Enriching Task-specific and Task-agnostic Representation Learning
Recent studies have proposed unified user modeling frameworks that lever...
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10/12/2022
On Divergence Measures for Bayesian Pseudocoresets
A Bayesian pseudocoreset is a small synthetic dataset for which the post...
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10/08/2022
AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models
There are growing interests in adapting large-scale language models usin...
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09/05/2022
Continuous Decomposition of Granularity for Neural Paraphrase Generation
While Transformers have had significant success in paragraph generation,...
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07/27/2022
Generator Knows What Discriminator Should Learn in Unconditional GANs
Recent methods for conditional image generation benefit from dense super...
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07/19/2022
Time Is MattEr: Temporal Self-supervision for Video Transformers
Understanding temporal dynamics of video is an essential aspect of learn...
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06/29/2022
Deformable Graph Transformer
Transformer-based models have been widely used and achieved state-of-the...
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06/17/2022
Rarity Score : A New Metric to Evaluate the Uncommonness of Synthesized Images
Evaluation metrics in image synthesis play a key role to measure perform...
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05/30/2022
Dataset Condensation via Efficient Synthetic-Data Parameterization
The great success of machine learning with massive amounts of data comes...
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05/19/2022
Two-Step Question Retrieval for Open-Domain QA
The retriever-reader pipeline has shown promising performance in open-do...
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04/28/2022
On the Effect of Pretraining Corpora on In-context Learning by a Large-scale Language Model
Many recent studies on large-scale language models have reported success...
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03/29/2022
Online Continual Learning on a Contaminated Data Stream with Blurry Task Boundaries
Learning under a continuously changing data distribution with incorrect ...
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03/26/2022
Metropolis-Hastings Data Augmentation for Graph Neural Networks
Graph Neural Networks (GNNs) often suffer from weak-generalization due t...
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02/21/2022
Generating Videos with Dynamics-aware Implicit Generative Adversarial Networks
In the deep learning era, long video generation of high-quality still re...
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12/30/2021
Contrastive Fine-grained Class Clustering via Generative Adversarial Networks
Unsupervised fine-grained class clustering is practical yet challenging ...
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10/19/2021
Online Continual Learning on Class Incremental Blurry Task Configuration with Anytime Inference
Despite rapid advances in continual learning, a large body of research i...
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09/10/2021
What Changes Can Large-scale Language Models Bring? Intensive Study on HyperCLOVA: Billions-scale Korean Generative Pretrained Transformers
GPT-3 shows remarkable in-context learning ability of large-scale langua...
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06/18/2021
Weakly Supervised Pre-Training for Multi-Hop Retriever
In multi-hop QA, answering complex questions entails iterative document ...
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05/20/2021
KLUE: Korean Language Understanding Evaluation
We introduce Korean Language Understanding Evaluation (KLUE) benchmark. ...
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04/15/2021
Reward Optimization for Neural Machine Translation with Learned Metrics
Neural machine translation (NMT) models are conventionally trained with ...
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03/31/2021
Rainbow Memory: Continual Learning with a Memory of Diverse Samples
Continual learning is a realistic learning scenario for AI models. Preva...
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03/01/2021
Self-supervised Auxiliary Learning for Graph Neural Networks via Meta-Learning
In recent years, graph neural networks (GNNs) have been widely adopted i...
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01/31/2021
M2FN: Multi-step Modality Fusion for Advertisement Image Assessment
Assessing advertisements, specifically on the basis of user preferences ...
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12/03/2020
DialogBERT: Discourse-Aware Response Generation via Learning to Recover and Rank Utterances
Recent advances in pre-trained language models have significantly improv...
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11/05/2020
Context-Aware Answer Extraction in Question Answering
Extractive QA models have shown very promising performance in predicting...
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10/23/2020
ST-BERT: Cross-modal Language Model Pre-training For End-to-end Spoken Language Understanding
Language model pre-training has shown promising results in various downs...
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08/14/2020
Which Strategies Matter for Noisy Label Classification? Insight into Loss and Uncertainty
Label noise is a critical factor that degrades the generalization perfor...
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07/16/2020
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs
Graph neural networks have shown superior performance in a wide range of...
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07/06/2020
CareCall: a Call-Based Active Monitoring Dialog Agent for Managing COVID-19 Pandemic
Tracking suspected cases of COVID-19 is crucial to suppressing the sprea...
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06/19/2020
Efficient Active Learning for Automatic Speech Recognition via Augmented Consistency Regularization
The cost of labeling transcriptions for large speech corpora becomes a b...
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06/15/2020
Slowing Down the Weight Norm Increase in Momentum-based Optimizers
Normalization techniques, such as batch normalization (BN), have led to ...
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05/18/2020
Graphs, Entities, and Step Mixture
Existing approaches for graph neural networks commonly suffer from the o...
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04/20/2020
ClovaCall: Korean Goal-Oriented Dialog Speech Corpus for Automatic Speech Recognition of Contact Centers
Automatic speech recognition (ASR) via call is essential for various app...
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02/10/2020
Modeling Musical Onset Probabilities via Neural Distribution Learning
Musical onset detection can be formulated as a time-to-event (TTE) or ti...
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12/04/2019
StarGAN v2: Diverse Image Synthesis for Multiple Domains
A good image-to-image translation model should learn a mapping between d...
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10/15/2019
Neural Approximation of an Auto-Regressive Process through Confidence Guided Sampling
We propose a generic confidence-based approximation that can be plugged ...
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10/06/2019
Which Ads to Show? Advertisement Image Assessment with Auxiliary Information via Multi-step Modality Fusion
Assessing aesthetic preference is a fundamental task related to human co...
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07/24/2019
Tripartite Heterogeneous Graph Propagation for Large-scale Social Recommendation
Graph Neural Networks (GNNs) have been emerging as a promising method fo...
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03/23/2019
Photorealistic Style Transfer via Wavelet Transforms
Recent style transfer models have provided promising artistic results. H...
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03/07/2019
Phase-aware Speech Enhancement with Deep Complex U-Net
Most deep learning-based models for speech enhancement have mainly focus...
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02/22/2019
Large-Scale Answerer in Questioner's Mind for Visual Dialog Question Generation
Answerer in Questioner's Mind (AQM) is an information-theoretic framewor...
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12/21/2018
Multi-Domain Processing via Hybrid Denoising Networks for Speech Enhancement
We present a hybrid framework that leverages the trade-off between tempo...
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10/08/2018
CHOPT : Automated Hyperparameter Optimization Framework for Cloud-Based Machine Learning Platforms
Many hyperparameter optimization (HyperOpt) methods assume restricted co...
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10/08/2018
NSML: Meet the MLaaS platform with a real-world case study
The boom of deep learning induced many industries and academies to intro...
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01/17/2018
Reinforcement Learning based Recommender System using Biclustering Technique
A recommender system aims to recommend items that a user is interested i...
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12/16/2017