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Jiun-Yu Kao

7 accepted papers

2024

Mitigating Bias for Question Answering Models by Tracking Bias Influence

NAACL 2024long

Models of various NLP tasks have been shown to exhibit stereotypes, and the bias in the question answering (QA) models is especially harmful as the output answers might be directly consumed by the end users. There have been datasets to evaluate bias in QA models, while bias mitigation technique for…

Cited by 7SourcePDFScholar
2024

Prompting Vision-Language Models For Aspect-Controlled Generation of Referring Expressions

NAACL 2024findings

Referring Expression Generation (REG) is the task of generating a description that unambiguously identifies a given target in the scene. Different from Image Captioning (IC), REG requires learning fine-grained characteristics of not only the scene objects but also their surrounding context. Referrin…

Cited by 0SourcePDFScholar
2022

GRAVL-BERT: Graphical Visual-Linguistic Representations for Multimodal Coreference Resolution

COLING 2022main

Learning from multimodal data has become a popular research topic in recent years. Multimodal coreference resolution (MCR) is an important task in this area. MCR involves resolving the references across different modalities, e.g., text and images, which is a crucial capability for building next-gene…

2021

Alexa Conversations: An Extensible Data-driven Approach for Building Task-oriented Dialogue Systems

NAACL 2021system demonstrations

Traditional goal-oriented dialogue systems rely on various components such as natural language understanding, dialogue state tracking, policy learning and response generation. Training each component requires annotations which are hard to obtain for every new domain, limiting scalability of such sys…

Cited by 22SourcePDFScholar
2019

Hand Graph Representations for Unsupervised Segmentation of Complex Activities

ICASSP 2019accepted

Analysis of hand skeleton data can be used to understand patterns in manipulation and assembly tasks. This paper introduces a graph-based representation of hand skeleton data and proposes a method to perform unsupervised temporal segmentation of a sequence of sub-tasks in order to evaluate the effic…

Cited by 0SourceScholar
2017

Disc-GLasso: Discriminative graph learning with sparsity regularization

ICASSP 2017accepted

Learning graph topology from data is challenging. Previous work leads to learning graphs on which the graph signals used for training are smooth. In this paper, we propose an optimization framework for learning multiple graphs, each associated to a class of signals, such that representation of signa…

Cited by 0SourceScholar
2016

Geometric-guided label propagation for moving object detection

ICASSP 2016accepted

Moving object segmentation in video has uses in many applications and is a particularly challenging task when the video is acquired by a moving camera. Typical approaches that rely on principal component analysis (PCA) tend to extract scattered sparse components of the moving objects and generally f…

Cited by 0SourceScholar