Search Results for author: Yunyao Li

Found 50 papers, 14 papers with code

Label Definitions Improve Semantic Role Labeling

1 code implementation NAACL 2022 Li Zhang, Ishan Jindal, Yunyao Li

Given a sentence and the predicate, a semantic role label is assigned to each argument of the predicate.

Semantic Role Labeling Sentence

Improving Cross-lingual Text Classification with Zero-shot Instance-Weighting

no code implementations ACL (RepL4NLP) 2021 Irene Li, Prithviraj Sen, Huaiyu Zhu, Yunyao Li, Dragomir Radev

In this paper, we propose zero-shot instance-weighting, a general model-agnostic zero-shot learning framework for improving CLTC by leveraging source instance weighting.

text-classification Text Classification +1

Time Sensitive Knowledge Editing through Efficient Finetuning

no code implementations6 Jun 2024 Xiou Ge, Ali Mousavi, Edouard Grave, Armand Joulin, Kun Qian, Benjamin Han, Mostafa Arefiyan, Yunyao Li

It is thus essential to design effective methods to both update obsolete knowledge and induce new knowledge into LLMs.

Benchmarking knowledge editing

Entity Disambiguation via Fusion Entity Decoding

no code implementations2 Apr 2024 Junxiong Wang, Ali Mousavi, Omar Attia, Ronak Pradeep, Saloni Potdar, Alexander M. Rush, Umar Farooq Minhas, Yunyao Li

Existing generative approaches demonstrate improved accuracy compared to classification approaches under the standardized ZELDA benchmark.

Decoder Entity Disambiguation +2

Increasing Coverage and Precision of Textual Information in Multilingual Knowledge Graphs

1 code implementation27 Nov 2023 Simone Conia, Min Li, Daniel Lee, Umar Farooq Minhas, Ihab Ilyas, Yunyao Li

Recent work in Natural Language Processing and Computer Vision has been using textual information -- e. g., entity names and descriptions -- available in knowledge graphs to ground neural models to high-quality structured data.

Entity Linking Machine Translation +1

FairytaleCQA: Integrating a Commonsense Knowledge Graph into Children's Storybook Narratives

no code implementations16 Nov 2023 Jiaju Chen, Yuxuan Lu, Shao Zhang, Bingsheng Yao, Yuanzhe Dong, Ying Xu, Yunyao Li, Qianwen Wang, Dakuo Wang, Yuling Sun

AI models (including LLM) often rely on narrative question-answering (QA) datasets to provide customized QA functionalities to support downstream children education applications; however, existing datasets only include QA pairs that are grounded within the given storybook content, but children can learn more when teachers refer the storybook content to real-world knowledge (e. g., commonsense knowledge).

Question Answering World Knowledge

FLEEK: Factual Error Detection and Correction with Evidence Retrieved from External Knowledge

no code implementations26 Oct 2023 Farima Fatahi Bayat, Kun Qian, Benjamin Han, Yisi Sang, Anton Belyi, Samira Khorshidi, Fei Wu, Ihab F. Ilyas, Yunyao Li

Detecting factual errors in textual information, whether generated by large language models (LLM) or curated by humans, is crucial for making informed decisions.


Construction of Paired Knowledge Graph-Text Datasets Informed by Cyclic Evaluation

no code implementations20 Sep 2023 Ali Mousavi, Xin Zhan, He Bai, Peng Shi, Theo Rekatsinas, Benjamin Han, Yunyao Li, Jeff Pound, Josh Susskind, Natalie Schluter, Ihab Ilyas, Navdeep Jaitly

Guided by these observations, we construct a new, improved dataset called LAGRANGE using heuristics meant to improve equivalence between KG and text and show the impact of each of the heuristics on cyclic evaluation.

Hallucination Knowledge Graphs

Beyond Labels: Empowering Human Annotators with Natural Language Explanations through a Novel Active-Learning Architecture

1 code implementation22 May 2023 Bingsheng Yao, Ishan Jindal, Lucian Popa, Yannis Katsis, Sayan Ghosh, Lihong He, Yuxuan Lu, Shashank Srivastava, Yunyao Li, James Hendler, Dakuo Wang

Our AL architecture leverages an explanation-generation model to produce explanations guided by human explanations, a prediction model that utilizes generated explanations toward prediction faithfully, and a novel data diversity-based AL sampling strategy that benefits from the explanation annotations.

Active Learning Decision Making +3

Growing and Serving Large Open-domain Knowledge Graphs

no code implementations16 May 2023 Ihab F. Ilyas, JP Lacerda, Yunyao Li, Umar Farooq Minhas, Ali Mousavi, Jeffrey Pound, Theodoros Rekatsinas, Chiraag Sumanth

We then describe how our platform, including graph embeddings, can be leveraged to create a Semantic Annotation service that links unstructured Web documents to entities in our KG.

Entity Linking Fact Verification +2

PriMeSRL-Eval: A Practical Quality Metric for Semantic Role Labeling Systems Evaluation

1 code implementation12 Oct 2022 Ishan Jindal, Alexandre Rademaker, Khoi-Nguyen Tran, Huaiyu Zhu, Hiroshi Kanayama, Marina Danilevsky, Yunyao Li

In this paper, we address key practical issues with existing evaluation scripts and propose a more strict SRL evaluation metric PriMeSRL.

Semantic Role Labeling Sentence

Domain Representative Keywords Selection: A Probabilistic Approach

1 code implementation Findings (ACL) 2022 Pritom Saha Akash, Jie Huang, Kevin Chen-Chuan Chang, Yunyao Li, Lucian Popa, ChengXiang Zhai

We propose a probabilistic approach to select a subset of a \textit{target domain representative keywords} from a candidate set, contrasting with a context domain.

LNN-EL: A Neuro-Symbolic Approach to Short-text Entity Linking

1 code implementation ACL 2021 Hang Jiang, Sairam Gurajada, Qiuhao Lu, Sumit Neelam, Lucian Popa, Prithviraj Sen, Yunyao Li, Alexander Gray

Entity linking (EL), the task of disambiguating mentions in text by linking them to entities in a knowledge graph, is crucial for text understanding, question answering or conversational systems.

Entity Linking Inductive Bias +2

Deep Learning on Graphs for Natural Language Processing

no code implementations NAACL 2021 Lingfei Wu, Yu Chen, Heng Ji, Yunyao Li

Due to its great power in modeling non-Euclidean data like graphs or manifolds, deep learning on graph techniques (i. e., Graph Neural Networks (GNNs)) have opened a new door to solving challenging graph-related NLP problems.

graph construction Graph Representation Learning +10

TableLab: An Interactive Table Extraction System with Adaptive Deep Learning

no code implementations16 Feb 2021 Nancy Xin Ru Wang, Douglas Burdick, Yunyao Li

Perfect extraction quality is difficult to achieve with one single out-of-box model due to (1) the wide variety of table styles, (2) the lack of training data representing this variety and (3) the inherent ambiguity and subjectivity of table definitions between end-users.

Table Extraction

CLAR: A Cross-Lingual Argument Regularizer for Semantic Role Labeling

no code implementations Findings of the Association for Computational Linguistics 2020 Ishan Jindal, Yunyao Li, Siddhartha Brahma, Huaiyu Zhu

Although different languages have different argument annotations, polyglot training, the idea of training one model on multiple languages, has previously been shown to outperform monolingual baselines, especially for low resource languages.

Semantic Role Labeling Sentence

Learning Structured Representations of Entity Names using Active Learning and Weak Supervision

1 code implementation EMNLP 2020 Kun Qian, Poornima Chozhiyath Raman, Yunyao Li, Lucian Popa

Structured representations of entity names are useful for many entity-related tasks such as entity normalization and variant generation.

Active Learning

Answering Complex Questions by Combining Information from Curated and Extracted Knowledge Bases

no code implementations WS 2020 Nikita Bhutani, Xinyi Zheng, Kun Qian, Yunyao Li, H. Jagadish

Knowledge-based question answering (KB{\_}QA) has long focused on simple questions that can be answered from a single knowledge source, a manually curated or an automatically extracted KB.

Question Answering

Jennifer for COVID-19: An NLP-Powered Chatbot Built for the People and by the People to Combat Misinformation

no code implementations ACL 2020 Yunyao Li, Gr, Tyrone ison, Patricia Silveyra, Ali Douraghy, Xinyu Guan, Thomas Kieselbach, Chengkai Li, Haiqi Zhang

Just as SARS-CoV-2, a new form of coronavirus continues to infect a growing number of people around the world, harmful misinformation about the outbreak also continues to spread.

Chatbot Misinformation

Towards Universal Semantic Representation

no code implementations WS 2019 Huaiyu Zhu, Yunyao Li, Laura Chiticariu

Natural language understanding at the semantic level and independent of language variations is of great practical value.

Abstract Meaning Representation Natural Language Understanding +1

HEIDL: Learning Linguistic Expressions with Deep Learning and Human-in-the-Loop

no code implementations ACL 2019 Yiwei Yang, Eser Kandogan, Yunyao Li, Walter S. Lasecki, Prithviraj Sen

While the role of humans is increasingly recognized in machine learning community, representation of and interaction with models in current human-in-the-loop machine learning (HITL-ML) approaches are too low-level and far-removed from human's conceptual models.

BIG-bench Machine Learning

Low-resource Deep Entity Resolution with Transfer and Active Learning

no code implementations ACL 2019 Jungo Kasai, Kun Qian, Sairam Gurajada, Yunyao Li, Lucian Popa

Recent adaptation of deep learning methods for ER mitigates the need for dataset-specific feature engineering by constructing distributed representations of entity records.

Active Learning Entity Resolution +2

DIMSIM: An Accurate Chinese Phonetic Similarity Algorithm Based on Learned High Dimensional Encoding

1 code implementation CONLL 2018 Min Li, Marina Danilevsky, Sara Noeman, Yunyao Li

Phonetic similarity algorithms identify words and phrases with similar pronunciation which are used in many natural language processing tasks.

Spelling Correction

SystemT: Declarative Text Understanding for Enterprise

no code implementations NAACL 2018 Laura Chiticariu, Marina Danilevsky, Yunyao Li, Frederick Reiss, Huaiyu Zhu

The rise of enterprise applications over unstructured and semi-structured documents poses new challenges to text understanding systems across multiple dimensions.

Document Classification Entity Extraction using GAN +3

Multilingual Information Extraction with PolyglotIE

no code implementations COLING 2016 Alan Akbik, Laura Chiticariu, Marina Danilevsky, Yonas Kbrom, Yunyao Li, Huaiyu Zhu

We present PolyglotIE, a web-based tool for developing extractors that perform Information Extraction (IE) over multilingual data.

Semantic Parsing

K-SRL: Instance-based Learning for Semantic Role Labeling

no code implementations COLING 2016 Alan Akbik, Yunyao Li

To overcome this challenge, we propose the use of instance-based learning that performs no explicit generalization, but rather extrapolates predictions from the most similar instances in the training data.

Machine Translation Question Answering +1

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