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09/11/2023
Incorporating Pre-trained Model Prompting in Multimodal Stock Volume Movement Prediction
Multimodal stock trading volume movement prediction with stock-related n...
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08/25/2023
MultiCapCLIP: Auto-Encoding Prompts for Zero-Shot Multilingual Visual Captioning
Supervised visual captioning models typically require a large scale of i...
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07/29/2023
Towards Codable Text Watermarking for Large Language Models
As large language models (LLMs) generate texts with increasing fluency a...
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06/07/2023
M^3IT: A Large-Scale Dataset towards Multi-Modal Multilingual Instruction Tuning
Instruction tuning has significantly advanced large language models (LLM...
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05/23/2023
Label Words are Anchors: An Information Flow Perspective for Understanding In-Context Learning
In-context learning (ICL) emerges as a promising capability of large lan...
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05/23/2023
Can Language Models Understand Physical Concepts?
Language models (LMs) gradually become general-purpose interfaces in the...
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05/21/2023
Communication Efficient Federated Learning for Multilingual Neural Machine Translation with Adapter
Federated Multilingual Neural Machine Translation (Fed-MNMT) has emerged...
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05/13/2023
PALM: Open Fundus Photograph Dataset with Pathologic Myopia Recognition and Anatomical Structure Annotation
Pathologic myopia (PM) is a common blinding retinal degeneration suffere...
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05/08/2023
Diffusion Theory as a Scalpel: Detecting and Purifying Poisonous Dimensions in Pre-trained Language Models Caused by Backdoor or Bias
Pre-trained Language Models (PLMs) may be poisonous with backdoors or bi...
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04/10/2023
Prompt Pre-Training with Twenty-Thousand Classes for Open-Vocabulary Visual Recognition
This work proposes POMP, a prompt pre-training method for vision-languag...
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01/30/2023
Fine-Tuning Deteriorates General Textual Out-of-Distribution Detection by Distorting Task-Agnostic Features
Detecting out-of-distribution (OOD) inputs is crucial for the safe deplo...
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01/25/2023
When to Trust Aggregated Gradients: Addressing Negative Client Sampling in Federated Learning
Federated Learning has become a widely-used framework which allows learn...
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01/25/2023
Integrating Local Real Data with Global Gradient Prototypes for Classifier Re-Balancing in Federated Long-Tailed Learning
Federated Learning (FL) has become a popular distributed learning paradi...
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12/31/2022
A Survey for In-context Learning
With the increasing ability of large language models (LLMs), in-context ...
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11/22/2022
Aligning Source Visual and Target Language Domains for Unpaired Video Captioning
Training supervised video captioning model requires coupled video-captio...
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11/02/2022
Gradient Knowledge Distillation for Pre-trained Language Models
Knowledge distillation (KD) is an effective framework to transfer knowle...
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10/28/2022
DiMBERT: Learning Vision-Language Grounded Representations with Disentangled Multimodal-Attention
Vision-and-language (V-L) tasks require the system to understand both vi...
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10/23/2022
Retrieve, Reason, and Refine: Generating Accurate and Faithful Patient Instructions
The "Patient Instruction" (PI), which contains critical instructional in...
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10/19/2022
Prophet Attention: Predicting Attention with Future Attention for Improved Image Captioning
Recently, attention based models have been used extensively in many sequ...
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10/18/2022
Fine-mixing: Mitigating Backdoors in Fine-tuned Language Models
Deep Neural Networks (DNNs) are known to be vulnerable to backdoor attac...
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10/14/2022
Expose Backdoors on the Way: A Feature-Based Efficient Defense against Textual Backdoor Attacks
Natural language processing (NLP) models are known to be vulnerable to b...
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10/14/2022
Holistic Sentence Embeddings for Better Out-of-Distribution Detection
Detecting out-of-distribution (OOD) instances is significant for the saf...
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10/13/2022
GA-SAM: Gradient-Strength based Adaptive Sharpness-Aware Minimization for Improved Generalization
Recently, Sharpness-Aware Minimization (SAM) algorithm has shown state-o...
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10/13/2022
Dim-Krum: Backdoor-Resistant Federated Learning for NLP with Dimension-wise Krum-Based Aggregation
Despite the potential of federated learning, it is known to be vulnerabl...
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10/11/2022
From Mimicking to Integrating: Knowledge Integration for Pre-Trained Language Models
Investigating better ways to reuse the released pre-trained language mod...
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06/04/2022
Rethinking the Openness of CLIP
Contrastive Language-Image Pre-training (CLIP) has demonstrated great po...
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03/20/2022
Hierarchical Inductive Transfer for Continual Dialogue Learning
Pre-trained models have achieved excellent performance on the dialogue t...
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03/12/2022
DFTR: Depth-supervised Hierarchical Feature Fusion Transformer for Salient Object Detection
Automated salient object detection (SOD) plays an increasingly crucial r...
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02/18/2022
REFUGE2 Challenge: Treasure for Multi-Domain Learning in Glaucoma Assessment
Glaucoma is the second leading cause of blindness and is the leading cau...
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02/16/2022
ADAM Challenge: Detecting Age-related Macular Degeneration from Fundus Images
Age-related macular degeneration (AMD) is the leading cause of visual im...
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12/14/2021
Model Uncertainty-Aware Knowledge Amalgamation for Pre-Trained Language Models
As many fine-tuned pre-trained language models (PLMs) with promising per...
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11/26/2021
KNAS: Green Neural Architecture Search
Many existing neural architecture search (NAS) solutions rely on downstr...
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11/08/2021
Auto-Encoding Knowledge Graph for Unsupervised Medical Report Generation
Medical report generation, which aims to automatically generate a long a...
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10/15/2021
RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models
Backdoor attacks, which maliciously control a well-trained model's outpu...
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10/13/2021
Well-classified Examples are Underestimated in Classification with Deep Neural Networks
The conventional wisdom behind learning deep classification models is to...
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10/08/2021
Topology-Imbalance Learning for Semi-Supervised Node Classification
The class imbalance problem, as an important issue in learning node repr...
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09/23/2021
Dynamic Knowledge Distillation for Pre-trained Language Models
Knowledge distillation (KD) has been proved effective for compressing la...
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09/07/2021
Adversarial Parameter Defense by Multi-Step Risk Minimization
Previous studies demonstrate DNNs' vulnerability to adversarial examples...
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09/03/2021
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data
Since training a large-scale backdoored model from scratch requires a la...
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09/01/2021
Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification
Data augmentation aims to enrich training samples for alleviating the ov...
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08/23/2021
Long-term, Short-term and Sudden Event: Trading Volume Movement Prediction with Graph-based Multi-view Modeling
Trading volume movement prediction is the key in a variety of financial ...
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08/20/2021
ASAT: Adaptively Scaled Adversarial Training in Time Series
Adversarial training is a method for enhancing neural networks to improv...
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08/05/2021
O2NA: An Object-Oriented Non-Autoregressive Approach for Controllable Video Captioning
Video captioning combines video understanding and language generation. D...
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06/13/2021
Contrastive Attention for Automatic Chest X-ray Report Generation
Recently, chest X-ray report generation, which aims to automatically gen...
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05/28/2021
Learning Relation Alignment for Calibrated Cross-modal Retrieval
Despite the achievements of large-scale multimodal pre-training approach...
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05/28/2021
Alleviating the Knowledge-Language Inconsistency: A Study for Deep Commonsense Knowledge
Knowledge facts are typically represented by relational triples, while w...
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05/15/2021
Rethinking Skip Connection with Layer Normalization in Transformers and ResNets
Skip connection, is a widely-used technique to improve the performance a...
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03/29/2021
Be Careful about Poisoned Word Embeddings: Exploring the Vulnerability of the Embedding Layers in NLP Models
Recent studies have revealed a security threat to natural language proce...
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02/22/2021
Multi-View Feature Representation for Dialogue Generation with Bidirectional Distillation
Neural dialogue models suffer from low-quality responses when interacted...
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12/29/2020
