Search Results for author: Handong Zhao

Found 37 papers, 12 papers with code

Few-Shot Class-Incremental Learning for Named Entity Recognition

no code implementations ACL 2022 Rui Wang, Tong Yu, Handong Zhao, Sungchul Kim, Subrata Mitra, Ruiyi Zhang, Ricardo Henao

In this work, we study a more challenging but practical problem, i. e., few-shot class-incremental learning for NER, where an NER model is trained with only few labeled samples of the new classes, without forgetting knowledge of the old ones.

class-incremental learning Few-Shot Class-Incremental Learning +4

InfoPrompt: Information-Theoretic Soft Prompt Tuning for Natural Language Understanding

no code implementations8 Jun 2023 Junda Wu, Tong Yu, Rui Wang, Zhao Song, Ruiyi Zhang, Handong Zhao, Chaochao Lu, Shuai Li, Ricardo Henao

With this framework, we develop two novel mutual information based loss functions, to (i) discover proper prompt initialization for the downstream tasks and learn sufficient task-relevant information from prompt tokens and (ii) encourage the output representation from the pretrained language model to be more aware of the task-relevant information captured in the learnt prompt.

Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer

no code implementations20 May 2023 Kaige Xie, Tong Yu, Haoliang Wang, Junda Wu, Handong Zhao, Ruiyi Zhang, Kanak Mahadik, Ani Nenkova, Mark Riedl

In this paper, we focus on improving the prompt transfer from dialogue state tracking to dialogue summarization and propose Skeleton-Assisted Prompt Transfer (SAPT), which leverages skeleton generation as extra supervision that functions as a medium connecting the distinct source and target task and resulting in the model's better consumption of dialogue state information.

Dialogue State Tracking Transfer Learning

Harnessing the Spatial-Temporal Attention of Diffusion Models for High-Fidelity Text-to-Image Synthesis

1 code implementation7 Apr 2023 Qiucheng Wu, Yujian Liu, Handong Zhao, Trung Bui, Zhe Lin, Yang Zhang, Shiyu Chang

We then impose spatial attention control by combining the attention over the entire text description and that over the local description of the particular object in the corresponding pixel region of that object.

Denoising Image Generation

Structured Dynamic Pricing: Optimal Regret in a Global Shrinkage Model

no code implementations28 Mar 2023 Rashmi Ranjan Bhuyan, Adel Javanmard, Sungchul Kim, Gourab Mukherjee, Ryan A. Rossi, Tong Yu, Handong Zhao

We consider dynamic pricing strategies in a streamed longitudinal data set-up where the objective is to maximize, over time, the cumulative profit across a large number of customer segments.

Better Generative Replay for Continual Federated Learning

no code implementations25 Feb 2023 Daiqing Qi, Handong Zhao, Sheng Li

Federated learning is a technique that enables a centralized server to learn from distributed clients via communications without accessing the client local data.

Continual Learning Federated Learning

Uncovering the Disentanglement Capability in Text-to-Image Diffusion Models

1 code implementation CVPR 2023 Qiucheng Wu, Yujian Liu, Handong Zhao, Ajinkya Kale, Trung Bui, Tong Yu, Zhe Lin, Yang Zhang, Shiyu Chang

Based on this finding, we further propose a simple, light-weight image editing algorithm where the mixing weights of the two text embeddings are optimized for style matching and content preservation.

Denoising Disentanglement

Hierarchical Conversational Preference Elicitation with Bandit Feedback

no code implementations6 Sep 2022 Jinhang Zuo, Songwen Hu, Tong Yu, Shuai Li, Handong Zhao, Carlee Joe-Wong

To achieve this, the recommender system conducts conversations with users, asking their preferences for different items or item categories.

Recommendation Systems

Bundle MCR: Towards Conversational Bundle Recommendation

1 code implementation26 Jul 2022 Zhankui He, Handong Zhao, Tong Yu, Sungchul Kim, Fan Du, Julian McAuley

MCR, which uses a conversational paradigm to elicit user interests by asking user preferences on tags (e. g., categories or attributes) and handling user feedback across multiple rounds, is an emerging recommendation setting to acquire user feedback and narrow down the output space, but has not been explored in the context of bundle recommendation.

Recommendation Systems

Unified Pretraining Framework for Document Understanding

no code implementations22 Apr 2022 Jiuxiang Gu, Jason Kuen, Vlad I. Morariu, Handong Zhao, Nikolaos Barmpalios, Rajiv Jain, Ani Nenkova, Tong Sun

Document intelligence automates the extraction of information from documents and supports many business applications.

Self-Supervised Learning

Neural Point Process for Learning Spatiotemporal Event Dynamics

1 code implementation12 Dec 2021 ZiHao Zhou, Xingyi Yang, Ryan Rossi, Handong Zhao, Rose Yu

The key construction of our approach is the nonparametric space-time intensity function, governed by a latent process.

Point Processes Variational Inference

Slow Learning and Fast Inference: Efficient Graph Similarity Computation via Knowledge Distillation

1 code implementation NeurIPS 2021 Can Qin, Handong Zhao, Lichen Wang, Huan Wang, Yulun Zhang, Yun Fu

For slow learning of graph similarity, this paper proposes a novel early-fusion approach by designing a co-attention-based feature fusion network on multilevel GNN features.

Anomaly Detection Graph Similarity +3

Automatic Forecasting via Meta-Learning

no code implementations29 Sep 2021 Mustafa Abdallah, Ryan Rossi, Kanak Mahadik, Sungchul Kim, Handong Zhao, Haoliang Wang, Saurabh Bagchi

In this work, we develop techniques for fast automatic selection of the best forecasting model for a new unseen time-series dataset, without having to first train (or evaluate) all the models on the new time-series data to select the best one.

Meta-Learning Time Series Forecasting

IPOF: An Extremely and Excitingly Simple Outlier Detection Booster via Infinite Propagation

no code implementations1 Aug 2021 Sibo Zhu, Handong Zhao, Hongfu Liu

By employing score-based outlier detectors for initialization, iPOF updates each data point's outlier score by averaging the outlier factors of its nearest common neighbors.

Outlier Detection

SelfDoc: Self-Supervised Document Representation Learning

no code implementations CVPR 2021 Peizhao Li, Jiuxiang Gu, Jason Kuen, Vlad I. Morariu, Handong Zhao, Rajiv Jain, Varun Manjunatha, Hongfu Liu

For downstream usage, we propose a novel modality-adaptive attention mechanism for multimodal feature fusion by adaptively emphasizing language and vision signals.

Representation Learning

ECACL: A Holistic Framework for Semi-Supervised Domain Adaptation

1 code implementation ICCV 2021 Kai Li, Chang Liu, Handong Zhao, Yulun Zhang, Yun Fu

This paper studies Semi-Supervised Domain Adaptation (SSDA), a practical yet under-investigated research topic that aims to learn a model of good performance using unlabeled samples and a few labeled samples in the target domain, with the help of labeled samples from a source domain.

Data Augmentation Domain Adaptation

RPCL: A Framework for Improving Cross-Domain Detection with Auxiliary Tasks

no code implementations18 Apr 2021 Kai Li, Curtis Wigington, Chris Tensmeyer, Vlad I. Morariu, Handong Zhao, Varun Manjunatha, Nikolaos Barmpalios, Yun Fu

Contrasted with prior work, this paper provides a complementary solution to align domains by learning the same auxiliary tasks in both domains simultaneously.

Insight-centric Visualization Recommendation

no code implementations21 Mar 2021 Camille Harris, Ryan A. Rossi, Sana Malik, Jane Hoffswell, Fan Du, Tak Yeon Lee, Eunyee Koh, Handong Zhao

This global ranking makes it difficult and time-consuming for users to find the most interesting or relevant insights.

Recommendation Systems

Adaptive Adversarial Network for Source-Free Domain Adaptation

no code implementations ICCV 2021 Haifeng Xia, Handong Zhao, Zhengming Ding

Unsupervised Domain Adaptation solves knowledge transfer along with the coexistence of well-annotated source domain and unlabeled target instances.

Source-Free Domain Adaptation Transfer Learning +1

Neural Point Process for Forecasting Spatiotemporal Events

no code implementations1 Jan 2021 ZiHao Zhou, Xingyi Yang, Xinyi He, Ryan Rossi, Handong Zhao, Rose Yu

To the best of our knowledge, this is the first neural point process model that can jointly predict both the space and time of events.

Density Estimation Point Processes

Learning Contextualized Knowledge Graph Structures for Commonsense Reasoning

no code implementations1 Jan 2021 Jun Yan, Mrigank Raman, Tianyu Zhang, Ryan Rossi, Handong Zhao, Sungchul Kim, Nedim Lipka, Xiang Ren

Recently, neural-symbolic architectures have achieved success on commonsense reasoning through effectively encoding relational structures retrieved from external knowledge graphs (KGs) and obtained state-of-the-art results in tasks such as (commonsense) question answering and natural language inference.

Knowledge Graphs Natural Language Inference +1

Neural Contextual Bandits with Deep Representation and Shallow Exploration

no code implementations NeurIPS 2021 Pan Xu, Zheng Wen, Handong Zhao, Quanquan Gu

We study a general class of contextual bandits, where each context-action pair is associated with a raw feature vector, but the reward generating function is unknown.

Multi-Armed Bandits Representation Learning

Self-Supervised Relationship Probing

no code implementations NeurIPS 2020 Jiuxiang Gu, Jason Kuen, Shafiq Joty, Jianfei Cai, Vlad Morariu, Handong Zhao, Tong Sun

Structured representations of images that model visual relationships are beneficial for many vision and vision-language applications.

Contrastive Learning Language Modelling +1

CAFE: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation

1 code implementation29 Oct 2020 Yikun Xian, Zuohui Fu, Handong Zhao, Yingqiang Ge, Xu Chen, Qiaoying Huang, Shijie Geng, Zhou Qin, Gerard de Melo, S. Muthukrishnan, Yongfeng Zhang

User profiles can capture prominent user behaviors from the history, and provide valuable signals about which kinds of path patterns are more likely to lead to potential items of interest for the user.

Explainable Recommendation Knowledge Graphs +1

Open-Edit: Open-Domain Image Manipulation with Open-Vocabulary Instructions

1 code implementation ECCV 2020 Xihui Liu, Zhe Lin, Jianming Zhang, Handong Zhao, Quan Tran, Xiaogang Wang, Hongsheng Li

We propose a novel algorithm, named Open-Edit, which is the first attempt on open-domain image manipulation with open-vocabulary instructions.

Image Manipulation

Structured Policy Iteration for Linear Quadratic Regulator

no code implementations ICML 2020 Youngsuk Park, Ryan A. Rossi, Zheng Wen, Gang Wu, Handong Zhao

In this paper, we introduce the \textit{Structured Policy Iteration} (S-PI) for LQR, a method capable of deriving a structured linear policy.

Learnable Subspace Clustering

1 code implementation9 Apr 2020 Jun Li, Hongfu Liu, Zhiqiang Tao, Handong Zhao, Yun Fu

This paper studies the large-scale subspace clustering (LSSC) problem with million data points.

Cross-Domain Document Object Detection: Benchmark Suite and Method

1 code implementation CVPR 2020 Kai Li, Curtis Wigington, Chris Tensmeyer, Handong Zhao, Nikolaos Barmpalios, Vlad I. Morariu, Varun Manjunatha, Tong Sun, Yun Fu

We establish a benchmark suite consisting of different types of PDF document datasets that can be utilized for cross-domain DOD model training and evaluation.

object-detection Object Detection

Learning Robust Data Representation: A Knowledge Flow Perspective

no code implementations28 Sep 2019 Zhengming Ding, Ming Shao, Handong Zhao, Sheng Li

It is always demanding to learn robust visual representation for various learning problems; however, this learning and maintenance process usually suffers from noise, incompleteness or knowledge domain mismatch.

Representation Learning Transfer Learning

Scene Graph Generation with External Knowledge and Image Reconstruction

no code implementations CVPR 2019 Jiuxiang Gu, Handong Zhao, Zhe Lin, Sheng Li, Jianfei Cai, Mingyang Ling

Scene graph generation has received growing attention with the advancements in image understanding tasks such as object detection, attributes and relationship prediction,~\etc.

Graph Generation Image Reconstruction +5

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