Search Results for author: Kyusong Lee

Found 20 papers, 8 papers with code

Real-time Transformer-based Open-Vocabulary Detection with Efficient Fusion Head

1 code implementation11 Mar 2024 Tiancheng Zhao, Peng Liu, Xuan He, Lu Zhang, Kyusong Lee

End-to-end transformer-based detectors (DETRs) have shown exceptional performance in both closed-set and open-vocabulary object detection (OVD) tasks through the integration of language modalities.

Object object-detection +2

How to Evaluate the Generalization of Detection? A Benchmark for Comprehensive Open-Vocabulary Detection

2 code implementations25 Aug 2023 Yiyang Yao, Peng Liu, Tiancheng Zhao, Qianqian Zhang, Jiajia Liao, Chunxin Fang, Kyusong Lee, Qing Wang

Extensive experimental results show that existing top OVD models all fail on the new tasks except for simple object types, demonstrating the value of the proposed dataset in pinpointing the weakness of current OVD models and guiding future research.

Object Detection

OmDet: Large-scale vision-language multi-dataset pre-training with multimodal detection network

1 code implementation10 Sep 2022 Tiancheng Zhao, Peng Liu, Kyusong Lee

The advancement of object detection (OD) in open-vocabulary and open-world scenarios is a critical challenge in computer vision.

Continual Learning Object +2

VL-CheckList: Evaluating Pre-trained Vision-Language Models with Objects, Attributes and Relations

1 code implementation1 Jul 2022 Tiancheng Zhao, Tianqi Zhang, Mingwei Zhu, Haozhan Shen, Kyusong Lee, Xiaopeng Lu, Jianwei Yin

Inspired by the CheckList for testing natural language processing, we exploit VL-CheckList, a novel framework to understand the capabilities of VLP models.

When is it permissible for artificial intelligence to lie? A trust-based approach

no code implementations9 Mar 2021 Tae Wan Kim, Tong, Lu, Kyusong Lee, Zhaoqi Cheng, Yanhan Tang, John Hooker

Conversational Artificial Intelligence (AI) used in industry settings can be trained to closely mimic human behaviors, including lying and deception.

Chatbot Cultural Vocal Bursts Intensity Prediction

SF-QA: Simple and Fair Evaluation Library for Open-domain Question Answering

1 code implementation EACL 2021 Xiaopeng Lu, Kyusong Lee, Tiancheng Zhao

Although open-domain question answering (QA) draws great attention in recent years, it requires large amounts of resources for building the full system and is often difficult to reproduce previous results due to complex configurations.

Open-Domain Question Answering

VisualSparta: An Embarrassingly Simple Approach to Large-scale Text-to-Image Search with Weighted Bag-of-words

1 code implementation ACL 2021 Xiaopeng Lu, Tiancheng Zhao, Kyusong Lee

To the best of our knowledge, VisualSparta is the first transformer-based text-to-image retrieval model that can achieve real-time searching for large-scale datasets, with significant accuracy improvement compared to previous state-of-the-art methods.

Cross-Modal Retrieval Image Retrieval +2

Talk to Papers: Bringing Neural Question Answering to Academic Search

no code implementations ACL 2020 Tianchang Zhao, Kyusong Lee

We introduce Talk to Papers, which exploits the recent open-domain question answering (QA) techniques to improve the current experience of academic search.

Natural Language Queries Open-Domain Question Answering

DialCrowd: A toolkit for easy dialog system assessment

no code implementations WS 2018 Kyusong Lee, Tiancheng Zhao, Alan W. black, Maxine Eskenazi

When creating a dialog system, developers need to test each version to ensure that it is performing correctly.

Chatbot

DialPort: Connecting the Spoken Dialog Research Community to Real User Data

no code implementations8 Jun 2016 Tiancheng Zhao, Kyusong Lee, Maxine Eskenazi

This paper describes a new spoken dialog portal that connects systems produced by the spoken dialog academic research community and gives them access to real users.

Grammatical Error Annotation for Korean Learners of Spoken English

no code implementations LREC 2012 Hongsuck Seo, Kyusong Lee, Gary Geunbae Lee, Soo-Ok Kweon, Hae-Ri Kim

The goal of our research is to build a grammatical error-tagged corpus for Korean learners of Spoken English dubbed Postech Learner Corpus.

Grammatical Error Detection

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