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08/21/2023
Instruction Tuning for Large Language Models: A Survey
This paper surveys research works in the quickly advancing field of inst...
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06/16/2023
Pushing the Limits of ChatGPT on NLP Tasks
Despite the success of ChatGPT, its performances on most NLP tasks are s...
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05/23/2023
TaDSE: Template-aware Dialogue Sentence Embeddings
Learning high quality sentence embeddings from dialogues has drawn incre...
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05/15/2023
Text Classification via Large Language Models
Despite the remarkable success of large-scale Language Models (LLMs) suc...
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05/09/2023
Towards Building the Federated GPT: Federated Instruction Tuning
While “instruction-tuned" generative large language models (LLMs) have d...
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04/21/2023
Granular-ball computing: an efficient, robust, and interpretable adaptive multi-granularity representation and computation method
Human cognition has a “large-scale first” cognitive mechanism, therefore...
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04/20/2023
GPT-NER: Named Entity Recognition via Large Language Models
Despite the fact that large-scale Language Models (LLM) have achieved SO...
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03/18/2023
Granular-ball Optimization Algorithm
The existing intelligent optimization algorithms are designed based on t...
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03/09/2023
Open World Classification with Adaptive Negative Samples
Open world classification is a task in natural language processing with ...
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03/07/2023
Research on Efficient Fuzzy Clustering Method Based on Local Fuzzy Granular balls
In recent years, the problem of fuzzy clustering has been widely concern...
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03/02/2023
GBMST: An Efficient Minimum Spanning Tree Clustering Based on Granular-Ball Computing
Most of the existing clustering methods are based on a single granularit...
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02/13/2023
PK-ICR: Persona-Knowledge Interactive Context Retrieval for Grounded Dialogue
Identifying relevant Persona or Knowledge for conversational systems is ...
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12/30/2022
A novel cluster internal evaluation index based on hyper-balls
It is crucial to evaluate the quality and determine the optimal number o...
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12/05/2022
GNN-SL: Sequence Labeling Based on Nearest Examples via GNN
To better handle long-tail cases in the sequence labeling (SL) task, in ...
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10/06/2022
GBSVM: Granular-ball Support Vector Machine
GBSVM (Granular-ball Support Vector Machine) is an important attempt to ...
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08/17/2022
Semi-supervised Learning with Deterministic Labeling and Large Margin Projection
The centrality and diversity of the labeled data are very influential to...
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07/28/2022
Learning Personalized Representations using Graph Convolutional Network
Generating representations that precisely reflect customers' behavior is...
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07/26/2022
Advanced Conditional Variational Autoencoders (A-CVAE): Towards interpreting open-domain conversation generation via disentangling latent feature representation
Currently end-to-end deep learning based open-domain dialogue systems re...
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05/07/2022
Number Entity Recognition
Numbers are essential components of text, like any other word tokens, fr...
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03/31/2022
kNN-NER: Named Entity Recognition with Nearest Neighbor Search
Inspired by recent advances in retrieval augmented methods in NLP <cit.>...
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03/17/2022
One-Stage Deep Edge Detection Based on Dense-Scale Feature Fusion and Pixel-Level Imbalance Learning
Edge detection, a basic task in the field of computer vision, is an impo...
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01/13/2022
Multi-granularity Association Learning Framework for on-the-fly Fine-Grained Sketch-based Image Retrieval
Fine-grained sketch-based image retrieval (FG-SBIR) addresses the proble...
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01/12/2022
An Efficient and Adaptive Granular-ball Generation Method in Classification Problem
Granular-ball computing is an efficient, robust, and scalable learning m...
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12/29/2021
An Efficient and Accurate Rough Set for Feature Selection, Classification and Knowledge Representation
This paper present a strong data mining method based on rough set, which...
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12/15/2021
Faster Nearest Neighbor Machine Translation
kNN based neural machine translation (kNN-MT) has achieved state-of-the-...
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11/03/2021
Rethinking the Image Feature Biases Exhibited by Deep CNN Models
In recent years, convolutional neural networks (CNNs) have been applied ...
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09/25/2021
Deciding Whether to Ask Clarifying Questions in Large-Scale Spoken Language Understanding
A large-scale conversational agent can suffer from understanding user ut...
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06/10/2021
AUGNLG: Few-shot Natural Language Generation using Self-trained Data Augmentation
Natural Language Generation (NLG) is a key component in a task-oriented ...
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12/03/2020
D-Unet: A Dual-encoder U-Net for Image Splicing Forgery Detection and Localization
Recently, many detection methods based on convolutional neural networks ...
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10/31/2020
LRA: an accelerated rough set framework based on local redundancy of attribute for feature selection
In this paper, we propose and prove the theorem regarding the stability ...
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10/12/2020
Improving Text Generation with Student-Forcing Optimal Transport
Neural language models are often trained with maximum likelihood estimat...
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08/14/2020
Weakly supervised cross-domain alignment with optimal transport
Cross-domain alignment between image objects and text sequences is key t...
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05/04/2020
Improving Adversarial Text Generation by Modeling the Distant Future
Auto-regressive text generation models usually focus on local fluency, a...
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05/02/2020
Ball k-means
This paper presents a novel accelerated exact k-means algorithm called t...
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05/01/2020
POINTER: Constrained Text Generation via Insertion-based Generative Pre-training
Large-scale pre-trained language models, such as BERT and GPT-2, have ac...
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11/20/2019
Graph-Driven Generative Models for Heterogeneous Multi-Task Learning
We propose a novel graph-driven generative model, that unifies multiple ...
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11/10/2019
Syntax-Infused Transformer and BERT models for Machine Translation and Natural Language Understanding
Attention-based models have shown significant improvement over tradition...
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10/20/2019
An Optimal Transport Framework for Zero-Shot Learning
We present an optimal transport (OT) framework for generalized zero-shot...
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10/09/2019
Kernel-Based Approaches for Sequence Modeling: Connections to Neural Methods
We investigate time-dependent data analysis from the perspective of recu...
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09/30/2019
Improving Textual Network Learning with Variational Homophilic Embeddings
The performance of many network learning applications crucially hinges o...
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06/07/2019
Learning Word Embeddings with Domain Awareness
Word embeddings are traditionally trained on a large corpus in an unsupe...
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06/05/2019
Improving Textual Network Embedding with Global Attention via Optimal Transport
Constituting highly informative network embeddings is an important tool ...
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05/30/2019
Discriminative Clustering for Robust Unsupervised Domain Adaptation
Unsupervised domain adaptation seeks to learn an invariant and discrimin...
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03/17/2019
Topic-Guided Variational Autoencoders for Text Generation
We propose a topic-guided variational autoencoder (TGVAE) model for text...
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01/03/2019
Adversarial Learning of a Sampler Based on an Unnormalized Distribution
We investigate adversarial learning in the case when only an unnormalize...
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12/30/2018
Mining Maximal Dynamic Spatial Co-Location Patterns
A spatial co-location pattern represents a subset of spatial features wh...
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11/27/2018
Generative Adversarial Network Training is a Continual Learning Problem
Generative Adversarial Networks (GANs) have proven to be a powerful fram...
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11/02/2018
Sequence Generation with Guider Network
Sequence generation with reinforcement learning (RL) has received signif...
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06/08/2018
JointGAN: Multi-Domain Joint Distribution Learning with Generative Adversarial Nets
A new generative adversarial network is developed for joint distribution...
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05/24/2018