Search Results for author: Zhu Zhang

Found 26 papers, 6 papers with code

Few-Shot Learning for Chronic Disease Management: Leveraging Large Language Models and Multi-Prompt Engineering with Medical Knowledge Injection

no code implementations16 Jan 2024 Haoxin Liu, Wenli Zhang, Jiaheng Xie, Buomsoo Kim, Zhu Zhang, Yidong Chai

On the depression detection task, our method (F1 = 0. 975~0. 978) significantly outperforms traditional supervised learning paradigms, including feature engineering (F1 = 0. 760) and architecture engineering (F1 = 0. 756).

Depression Detection Feature Engineering +3

Self-Checker: Plug-and-Play Modules for Fact-Checking with Large Language Models

no code implementations24 May 2023 Miaoran Li, Baolin Peng, Michel Galley, Jianfeng Gao, Zhu Zhang

Fact-checking is an essential task in NLP that is commonly utilized for validating the factual accuracy of claims.

Fact Checking In-Context Learning

Enhancing Task Bot Engagement with Synthesized Open-Domain Dialog

no code implementations20 Dec 2022 Miaoran Li, Baolin Peng, Michel Galley, Jianfeng Gao, Zhu Zhang

To better mimic human-level conversations that usually fuse various dialog modes, it is essential to build a system that can effectively handle both TOD and ODD and access different knowledge sources.

Open-Domain Dialog

OPERA: Harmonizing Task-Oriented Dialogs and Information Seeking Experience

1 code implementation24 Jun 2022 Miaoran Li, Baolin Peng, Jianfeng Gao, Zhu Zhang

Existing studies in conversational AI mostly treat task-oriented dialog (TOD) and question answering (QA) as separate tasks.

Question Answering

Gene Function Prediction with Gene Interaction Networks: A Context Graph Kernel Approach

no code implementations22 Apr 2022 Xin Li, Hsinchun Chen, Jiexun Li, Zhu Zhang

Predicting gene functions is a challenge for biologists in the post genomic era.

SYNERGY: Building Task Bots at Scale Using Symbolic Knowledge and Machine Teaching

no code implementations21 Oct 2021 Baolin Peng, Chunyuan Li, Zhu Zhang, Jinchao Li, Chenguang Zhu, Jianfeng Gao

We propose SYNERGY, a hybrid learning framework where a task bot is developed in two steps: (i) Symbolic knowledge to neural networks: Large amounts of simulated dialog sessions are generated based on task-specific symbolic knowledge which is represented as a task schema consisting of dialog flows and task-oriented databases.

Cascaded Prediction Network via Segment Tree for Temporal Video Grounding

no code implementations CVPR 2021 Yang Zhao, Zhou Zhao, Zhu Zhang, Zhijie Lin

Temporal video grounding aims to localize the target segment which is semantically aligned with the given sentence in an untrimmed video.

Sentence Video Grounding

Learning to Rehearse in Long Sequence Memorization

no code implementations2 Jun 2021 Zhu Zhang, Chang Zhou, Jianxin Ma, Zhijie Lin, Jingren Zhou, Hongxia Yang, Zhou Zhao

Further, we design a history sampler to select informative fragments for rehearsal training, making the memory focus on the crucial information.

Memorization Question Answering +1

Connecting Language and Vision for Natural Language-Based Vehicle Retrieval

1 code implementation31 May 2021 Shuai Bai, Zhedong Zheng, Xiaohan Wang, Junyang Lin, Zhu Zhang, Chang Zhou, Yi Yang, Hongxia Yang

In this paper, we apply one new modality, i. e., the language description, to search the vehicle of interest and explore the potential of this task in the real-world scenario.

Language Modelling Management +2

M6-UFC: Unifying Multi-Modal Controls for Conditional Image Synthesis via Non-Autoregressive Generative Transformers

no code implementations NeurIPS 2021 Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, Hongxia Yang

Conditional image synthesis aims to create an image according to some multi-modal guidance in the forms of textual descriptions, reference images, and image blocks to preserve, as well as their combinations.

Image Generation

UFC-BERT: Unifying Multi-Modal Controls for Conditional Image Synthesis

no code implementations NeurIPS 2021 Zhu Zhang, Jianxin Ma, Chang Zhou, Rui Men, Zhikang Li, Ming Ding, Jie Tang, Jingren Zhou, Hongxia Yang

Conditional image synthesis aims to create an image according to some multi-modal guidance in the forms of textual descriptions, reference images, and image blocks to preserve, as well as their combinations.

Image Generation

To Learn Effective Features: Understanding the Task-Specific Adaptation of MAML

no code implementations1 Jan 2021 Zhijie Lin, Zhou Zhao, Zhu Zhang, Huai Baoxing, Jing Yuan

Model Agnostic Meta-Learning~(MAML)~(\cite{finn2017model}) is one of the most well-known gradient-based meta learning algorithms, that learns the meta-initialization through the inner and outer optimization loop.

Contrastive Learning Meta-Learning

Ask Question with Double Hints: Visual Question Generation with Answer-awareness and Region-reference

no code implementations1 Jan 2021 Shen Kai, Lingfei Wu, Siliang Tang, Fangli Xu, Zhu Zhang, Yu Qiang, Yueting Zhuang

The task of visual question generation~(VQG) aims to generate human-like questions from an image and potentially other side information (e. g. answer type or the answer itself).

Graph-to-Sequence Question Generation +1

Continual Memory: Can We Reason After Long-Term Memorization?

no code implementations1 Jan 2021 Zhu Zhang, Chang Zhou, Zhou Zhao, Zhijie Lin, Jingren Zhou, Hongxia Yang

Existing reasoning tasks often follow the setting of "reasoning while experiencing", which has an important assumption that the raw contents can be always accessed while reasoning.

Memorization

RADDLE: An Evaluation Benchmark and Analysis Platform for Robust Task-oriented Dialog Systems

no code implementations ACL 2021 Baolin Peng, Chunyuan Li, Zhu Zhang, Chenguang Zhu, Jinchao Li, Jianfeng Gao

For task-oriented dialog systems to be maximally useful, it must be able to process conversations in a way that is (1) generalizable with a small number of training examples for new task domains, and (2) robust to user input in various styles, modalities or domains.

Counterfactual Contrastive Learning for Weakly-Supervised Vision-Language Grounding

no code implementations NeurIPS 2020 Zhu Zhang, Zhou Zhao, Zhijie Lin, Jieming Zhu, Xiuqiang He

Weakly-supervised vision-language grounding aims to localize a target moment in a video or a specific region in an image according to the given sentence query, where only video-level or image-level sentence annotations are provided during training.

Contrastive Learning counterfactual +2

Object-Aware Multi-Branch Relation Networks for Spatio-Temporal Video Grounding

no code implementations16 Aug 2020 Zhu Zhang, Zhou Zhao, Zhijie Lin, Baoxing Huai, Nicholas Jing Yuan

Spatio-temporal video grounding aims to retrieve the spatio-temporal tube of a queried object according to the given sentence.

Object Relation +4

Weakly-Supervised Video Moment Retrieval via Semantic Completion Network

no code implementations19 Nov 2019 Zhijie Lin, Zhou Zhao, Zhu Zhang, Qi. Wang, Huasheng Liu

Video moment retrieval is to search the moment that is most relevant to the given natural language query.

Moment Retrieval Retrieval +2

Localizing Unseen Activities in Video via Image Query

no code implementations28 Jun 2019 Zhu Zhang, Zhou Zhao, Zhijie Lin, Jingkuan Song, Deng Cai

Thus, we consider a new task to localize unseen activities in videos via image queries, named Image-Based Activity Localization.

Action Localization Video Understanding

Open-Ended Long-Form Video Question Answering via Hierarchical Convolutional Self-Attention Networks

no code implementations28 Jun 2019 Zhu Zhang, Zhou Zhao, Zhijie Lin, Jingkuan Song, Xiaofei He

Concretely, we first develop a hierarchical convolutional self-attention encoder to efficiently model long-form video contents, which builds the hierarchical structure for video sequences and captures question-aware long-range dependencies from video context.

Answer Generation Question Answering +1

Cross-Modal Interaction Networks for Query-Based Moment Retrieval in Videos

1 code implementation6 Jun 2019 Zhu Zhang, Zhijie Lin, Zhou Zhao, Zhenxin Xiao

Query-based moment retrieval aims to localize the most relevant moment in an untrimmed video according to the given natural language query.

Moment Retrieval Natural Language Queries +2

To Attend or not to Attend: A Case Study on Syntactic Structures for Semantic Relatedness

1 code implementation ACL 2018 Amulya Gupta, Zhu Zhang

With the recent success of Recurrent Neural Networks (RNNs) in Machine Translation (MT), attention mechanisms have become increasingly popular.

Machine Translation Paraphrase Identification +3

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