Search Results for author: Sharifah Mahani Aljunied

Found 8 papers, 4 papers with code

M3Exam: A Multilingual, Multimodal, Multilevel Benchmark for Examining Large Language Models

1 code implementation NeurIPS 2023 Wenxuan Zhang, Sharifah Mahani Aljunied, Chang Gao, Yew Ken Chia, Lidong Bing

M3Exam exhibits three unique characteristics: (1) multilingualism, encompassing questions from multiple countries that require strong multilingual proficiency and cultural knowledge; (2) multimodality, accounting for the multimodal nature of many exam questions to test the model's multimodal understanding capability; and (3) multilevel structure, featuring exams from three critical educational periods to comprehensively assess a model's proficiency at different levels.

Domain-Expanded ASTE: Rethinking Generalization in Aspect Sentiment Triplet Extraction

no code implementations23 May 2023 Yew Ken Chia, Hui Chen, Wei Han, Guizhen Chen, Sharifah Mahani Aljunied, Soujanya Poria, Lidong Bing

Aspect Sentiment Triplet Extraction (ASTE) is a subtask of Aspect-Based Sentiment Analysis (ABSA) that considers each opinion term, their expressed sentiment, and the corresponding aspect targets.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +2

A Dataset for Hyper-Relational Extraction and a Cube-Filling Approach

1 code implementation18 Nov 2022 Yew Ken Chia, Lidong Bing, Sharifah Mahani Aljunied, Luo Si, Soujanya Poria

Hence, we propose CubeRE, a cube-filling model inspired by table-filling approaches and explicitly considers the interaction between relation triplets and qualifiers.

graph construction Hyper-Relational Extraction +1

GlobalWoZ: Globalizing MultiWoZ to Develop Multilingual Task-Oriented Dialogue Systems

1 code implementation ACL 2022 Bosheng Ding, Junjie Hu, Lidong Bing, Sharifah Mahani Aljunied, Shafiq Joty, Luo Si, Chunyan Miao

Much recent progress in task-oriented dialogue (ToD) systems has been driven by available annotation data across multiple domains for training.

Task-Oriented Dialogue Systems

Improving Low-Resource Named Entity Recognition using Joint Sentence and Token Labeling

no code implementations ACL 2020 Canasai Kruengkrai, Thien Hai Nguyen, Sharifah Mahani Aljunied, Lidong Bing

Exploiting sentence-level labels, which are easy to obtain, is one of the plausible methods to improve low-resource named entity recognition (NER), where token-level labels are costly to annotate.

Binary Classification Classification +7

TaLAPi --- A Thai Linguistically Annotated Corpus for Language Processing

no code implementations LREC 2014 AiTi Aw, Sharifah Mahani Aljunied, Nattadaporn Lertcheva, Sasiwimon Kalunsima

To reduce the ambiguities in POS tagging and to provide rich information for facilitating Thai syntactic analysis, we adapted the POS tags used in ORCHID and propose a framework to tag Thai text and also addresses the tagging of loan and foreign words based on the proposed segmentation strategy.

POS POS Tagging +1

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