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09/09/2023
RR-CP: Reliable-Region-Based Conformal Prediction for Trustworthy Medical Image Classification
Conformal prediction (CP) generates a set of predictions for a given tes...
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08/26/2023
SamDSK: Combining Segment Anything Model with Domain-Specific Knowledge for Semi-Supervised Learning in Medical Image Segmentation
The Segment Anything Model (SAM) exhibits a capability to segment a wide...
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06/08/2023
BOOT: Data-free Distillation of Denoising Diffusion Models with Bootstrapping
Diffusion models have demonstrated excellent potential for generating di...
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06/05/2023
PLANNER: Generating Diversified Paragraph via Latent Language Diffusion Model
Autoregressive models for text sometimes generate repetitive and low-qua...
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04/22/2023
Input Augmentation with SAM: Boosting Medical Image Segmentation with Segmentation Foundation Model
The Segment Anything Model (SAM) is a recently developed large model for...
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03/11/2023
Stabilizing Transformer Training by Preventing Attention Entropy Collapse
Training stability is of great importance to Transformers. In this work,...
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03/02/2023
Interactive Text Generation
Users interact with text, image, code, or other editors on a daily basis...
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02/17/2023
GPT4MIA: Utilizing Generative Pre-trained Transformer (GPT-3) as A Plug-and-Play Transductive Model for Medical Image Analysis
In this paper, we propose a novel approach (called GPT4MIA) that utilize...
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12/23/2022
EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset)
The advance of computer-aided detection systems using deep learning open...
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10/25/2022
Bridging the Training-Inference Gap for Dense Phrase Retrieval
Building dense retrievers requires a series of standard procedures, incl...
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10/10/2022
f-DM: A Multi-stage Diffusion Model via Progressive Signal Transformation
Diffusion models (DMs) have recently emerged as SoTA tools for generativ...
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09/04/2022
Data-Driven Deep Supervision for Skin Lesion Classification
Automatic classification of pigmented, non-pigmented, and depigmented no...
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07/01/2022
Usable Region Estimate for Assessing Practical Usability of Medical Image Segmentation Models
We aim to quantitatively measure the practical usability of medical imag...
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06/02/2022
H-EMD: A Hierarchical Earth Mover's Distance Method for Instance Segmentation
Deep learning (DL) based semantic segmentation methods have achieved exc...
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03/23/2022
Linearizing Transformer with Key-Value Memory Bank
Transformer has brought great success to a wide range of natural languag...
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03/18/2022
Report from the NSF Future Directions Workshop on Automatic Evaluation of Dialog: Research Directions and Challenges
This is a report on the NSF Future Directions Workshop on Automatic Eval...
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12/12/2021
Towards More Efficient Insertion Transformer with Fractional Positional Encoding
Auto-regressive neural sequence models have been shown to be effective a...
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11/03/2021
HS3: Learning with Proper Task Complexity in Hierarchically Supervised Semantic Segmentation
While deeply supervised networks are common in recent literature, they t...
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10/24/2021
X-Distill: Improving Self-Supervised Monocular Depth via Cross-Task Distillation
In this paper, we propose a novel method, X-Distill, to improve the self...
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10/24/2021
Perceptual Consistency in Video Segmentation
In this paper, we present a novel perceptual consistency perspective on ...
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10/24/2021
AuxAdapt: Stable and Efficient Test-Time Adaptation for Temporally Consistent Video Semantic Segmentation
In video segmentation, generating temporally consistent results across f...
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06/14/2021
Automatic Document Sketching: Generating Drafts from Analogous Texts
The advent of large pre-trained language models has made it possible to ...
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05/14/2021
Joint Retrieval and Generation Training for Grounded Text Generation
Recent advances in large-scale pre-training such as GPT-3 allow seemingl...
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04/18/2021
A Token-level Reference-free Hallucination Detection Benchmark for Free-form Text Generation
Large pretrained generative models like GPT-3 often suffer from hallucin...
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04/16/2021
An Adversarially-Learned Turing Test for Dialog Generation Models
The design of better automated dialogue evaluation metrics offers the po...
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04/06/2021
InverseForm: A Loss Function for Structured Boundary-Aware Segmentation
We present a novel boundary-aware loss term for semantic segmentation us...
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03/24/2021
Finetuning Pretrained Transformers into RNNs
Transformers have outperformed recurrent neural networks (RNNs) in natur...
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03/02/2021
Data Augmentation for Abstractive Query-Focused Multi-Document Summarization
The progress in Query-focused Multi-Document Summarization (QMDS) has be...
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01/17/2021
What Makes Good In-Context Examples for GPT-3?
GPT-3 has attracted lots of attention due to its superior performance ac...
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01/02/2021
SDA: Improving Text Generation with Self Data Augmentation
Data augmentation has been widely used to improve deep neural networks i...
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12/21/2020
Narrative Incoherence Detection
Motivated by the increasing popularity of intelligent editing assistant,...
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12/17/2020
Unlabeled Data Guided Semi-supervised Histopathology Image Segmentation
Automatic histopathology image segmentation is crucial to disease analys...
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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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09/16/2020
Contextualized Perturbation for Textual Adversarial Attack
Adversarial examples expose the vulnerabilities of natural language proc...
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09/15/2020
Dialogue Response Ranking Training with Large-Scale Human Feedback Data
Existing open-domain dialog models are generally trained to minimize the...
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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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08/06/2020
Structured Convolutions for Efficient Neural Network Design
In this work, we tackle model efficiency by exploiting redundancy in the...
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06/01/2020
Improving Disentangled Text Representation Learning with Information-Theoretic Guidance
Learning disentangled representations of natural language is essential f...
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05/01/2020
A Controllable Model of Grounded Response Generation
Current end-to-end neural conversation models inherently lack the flexib...
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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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04/30/2020
Contextual Text Style Transfer
We introduce a new task, Contextual Text Style Transfer - translating a ...
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04/05/2020
Optimus: Organizing Sentences via Pre-trained Modeling of a Latent Space
When trained effectively, the Variational Autoencoder (VAE) can be both ...
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12/31/2019
Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation
Sequence generation models are commonly refined with reinforcement learn...
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11/10/2019
INSET: Sentence Infilling with Inter-sentential Generative Pre-training
Missing sentence generation (or sentence infilling) fosters a wide range...
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11/08/2019
Unsupervised Common Question Generation from Multiple Documents using Reinforced Contrastive Coordinator
Web search engines today return a ranked list of document links in respo...
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11/01/2019
DialoGPT: Large-Scale Generative Pre-training for Conversational Response Generation
We present a large, tunable neural conversational response generation mo...
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10/25/2019
Generating a Common Question from Multiple Documents using Multi-source Encoder-Decoder Models
Ambiguous user queries in search engines result in the retrieval of docu...
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09/11/2019
Contrastively Smoothed Class Alignment for Unsupervised Domain Adaptation
Recent unsupervised approaches to domain adaptation primarily focus on m...
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09/03/2019
Structuring Latent Spaces for Stylized Response Generation
Generating responses in a targeted style is a useful yet challenging tas...
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08/31/2019
