Search Results for author: Lifu Huang

Found 34 papers, 10 papers with code

Semi-supervised New Event Type Induction and Event Detection

no code implementations EMNLP 2020 Lifu Huang, Heng Ji

We design a Semi-Supervised Vector Quantized Variational Autoencoder framework to automatically learn a discrete latent type representation for each seen and unseen type and optimize them using seen type event annotations.

Event Detection Event Extraction

The Future is not One-dimensional: Complex Event Schema Induction by Graph Modeling for Event Prediction

1 code implementation EMNLP 2021 Manling Li, Sha Li, Zhenhailong Wang, Lifu Huang, Kyunghyun Cho, Heng Ji, Jiawei Han, Clare Voss

We introduce a new concept of Temporal Complex Event Schema: a graph-based schema representation that encompasses events, arguments, temporal connections and argument relations.

Inferring Commonsense Explanations as Prompts for Future Event Generation

no code implementations18 Jan 2022 Li Lin, Yixin Cao, Lifu Huang, Shuang Li, Xuming Hu, Lijie Wen, Jianmin Wang

GM further takes the commonsense knowledge as prompts to guide and enforce the generation of logistically coherent future events.

Text Generation

MuMuQA: Multimedia Multi-Hop News Question Answering via Cross-Media Knowledge Extraction and Grounding

no code implementations20 Dec 2021 Revanth Gangi Reddy, Xilin Rui, Manling Li, Xudong Lin, Haoyang Wen, Jaemin Cho, Lifu Huang, Mohit Bansal, Avirup Sil, Shih-Fu Chang, Alexander Schwing, Heng Ji

Specifically, the task involves multi-hop questions that require reasoning over image-caption pairs to identify the grounded visual object being referred to and then predicting a span from the news body text to answer the question.

Data Augmentation Question-Answer-Generation +1

Query and Extract: Refining Event Extraction as Type-oriented Binary Decoding

no code implementations14 Oct 2021 Sijia Wang, Mo Yu, Shiyu Chang, Lichao Sun, Lifu Huang

We propose a novel event extraction framework that takes event types and argument roles as natural language queries to extract candidate triggers and arguments from the input text.

Event Extraction Multi-class Classification

How Knowledge Graph and Attention Help? A Qualitative Analysis into Bag-level Relation Extraction

1 code implementation ACL 2021 Zikun Hu, Yixin Cao, Lifu Huang, Tat-Seng Chua

In this paper, we contribute a dataset and propose a paradigm to quantitatively evaluate the effect of attention and KG on bag-level relation extraction (RE).

Relation Extraction

How Knowledge Graph and Attention Help? A Quantitative Analysis into Bag-level Relation Extraction

1 code implementation26 Jul 2021 Zikun Hu, Yixin Cao, Lifu Huang, Tat-Seng Chua

In this paper, we contribute a dataset and propose a paradigm to quantitatively evaluate the effect of attention and KG on bag-level relation extraction (RE).

Relation Extraction

Extracting Temporal Event Relation with Syntactic-Guided Temporal Graph Transformer

no code implementations19 Apr 2021 Shuaicheng Zhang, Lifu Huang, Qiang Ning

Extracting temporal relations (e. g., before, after, concurrent) among events is crucial to natural language understanding.

Natural Language Understanding Relation Classification

Future is not One-dimensional: Graph Modeling based Complex Event Schema Induction for Event Prediction

no code implementations13 Apr 2021 Manling Li, Sha Li, Zhenhailong Wang, Lifu Huang, Kyunghyun Cho, Heng Ji, Jiawei Han, Clare Voss

We introduce the concept of Temporal Complex Event Schema: a graph-based schema representation that encompasses events, arguments, temporal connections and argument relations.

Global Attention for Name Tagging

no code implementations CONLL 2018 Boliang Zhang, Spencer Whitehead, Lifu Huang, Heng Ji

Many name tagging approaches use local contextual information with much success, but fail when the local context is ambiguous or limited.

ReviewRobot: Explainable Paper Review Generation based on Knowledge Synthesis

1 code implementation INLG (ACL) 2020 Qingyun Wang, Qi Zeng, Lifu Huang, Kevin Knight, Heng Ji, Nazneen Fatema Rajani

To assist human review process, we build a novel ReviewRobot to automatically assign a review score and write comments for multiple categories such as novelty and meaningful comparison.

Review Generation

Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning

no code implementations IJCNLP 2019 Lifu Huang, Ronan Le Bras, Chandra Bhagavatula, Yejin Choi

In this paper, we introduce Cosmos QA, a large-scale dataset of 35, 600 problems that require commonsense-based reading comprehension, formulated as multiple-choice questions.

Machine Reading Comprehension

Biomedical Event Extraction based on Knowledge-driven Tree-LSTM

no code implementations NAACL 2019 Diya Li, Lifu Huang, Heng Ji, Jiawei Han

Event extraction for the biomedical domain is more challenging than that in the general news domain since it requires broader acquisition of domain-specific knowledge and deeper understanding of complex contexts.

Entity Linking Event Extraction

PaperRobot: Incremental Draft Generation of Scientific Ideas

2 code implementations ACL 2019 Qingyun Wang, Lifu Huang, Zhiying Jiang, Kevin Knight, Heng Ji, Mohit Bansal, Yi Luan

We present a PaperRobot who performs as an automatic research assistant by (1) conducting deep understanding of a large collection of human-written papers in a target domain and constructing comprehensive background knowledge graphs (KGs); (2) creating new ideas by predicting links from the background KGs, by combining graph attention and contextual text attention; (3) incrementally writing some key elements of a new paper based on memory-attention networks: from the input title along with predicted related entities to generate a paper abstract, from the abstract to generate conclusion and future work, and finally from future work to generate a title for a follow-on paper.

Graph Attention Knowledge Graphs +4

Genre Separation Network with Adversarial Training for Cross-genre Relation Extraction

no code implementations EMNLP 2018 Ge Shi, Chong Feng, Lifu Huang, Boliang Zhang, Heng Ji, Lejian Liao, He-Yan Huang

Relation Extraction suffers from dramatical performance decrease when training a model on one genre and directly applying it to a new genre, due to the distinct feature distributions.

Feature Engineering Relation Extraction +1

Chengyu Cloze Test

1 code implementation WS 2018 Zhiying Jiang, Boliang Zhang, Lifu Huang, Heng Ji

We present a neural recommendation model for Chengyu, which is a special type of Chinese idiom.

Cloze Test

Tracking State Changes in Procedural Text: A Challenge Dataset and Models for Process Paragraph Comprehension

no code implementations NAACL 2018 Bhavana Dalvi Mishra, Lifu Huang, Niket Tandon, Wen-tau Yih, Peter Clark

The new dataset, ProPara, is the first to contain natural (rather than machine-generated) text about a changing world along with a full annotation of entity states (location and existence) during those changes (81k datapoints).

Procedural Text Understanding

Paper Abstract Writing through Editing Mechanism

2 code implementations ACL 2018 Qingyun Wang, Zhi-Hao Zhou, Lifu Huang, Spencer Whitehead, Boliang Zhang, Heng Ji, Kevin Knight

We present a paper abstract writing system based on an attentive neural sequence-to-sequence model that can take a title as input and automatically generate an abstract.

Paper generation

Entity-aware Image Caption Generation

no code implementations EMNLP 2018 Di Lu, Spencer Whitehead, Lifu Huang, Heng Ji, Shih-Fu Chang

Current image captioning approaches generate descriptions which lack specific information, such as named entities that are involved in the images.

Image Captioning

Multi-lingual Common Semantic Space Construction via Cluster-consistent Word Embedding

no code implementations EMNLP 2018 Lifu Huang, Kyunghyun Cho, Boliang Zhang, Heng Ji, Kevin Knight

We construct a multilingual common semantic space based on distributional semantics, where words from multiple languages are projected into a shared space to enable knowledge and resource transfer across languages.

Word Alignment

Open Relation Extraction and Grounding

no code implementations IJCNLP 2017 Dian Yu, Lifu Huang, Heng Ji

Previous open Relation Extraction (open RE) approaches mainly rely on linguistic patterns and constraints to extract important relational triples from large-scale corpora.

Relation Extraction Slot Filling

Learning Phrase Embeddings from Paraphrases with GRUs

no code implementations WS 2017 Zhihao Zhou, Lifu Huang, Heng Ji

Learning phrase representations has been widely explored in many Natural Language Processing (NLP) tasks (e. g., Sentiment Analysis, Machine Translation) and has shown promising improvements.

Machine Translation Sentiment Analysis +1

Zero-Shot Transfer Learning for Event Extraction

1 code implementation ACL 2018 Lifu Huang, Heng Ji, Kyunghyun Cho, Clare R. Voss

Most previous event extraction studies have relied heavily on features derived from annotated event mentions, thus cannot be applied to new event types without annotation effort.

Event Extraction Transfer Learning

Improving Slot Filling Performance with Attentive Neural Networks on Dependency Structures

no code implementations EMNLP 2017 Lifu Huang, Avirup Sil, Heng Ji, Radu Florian

Slot Filling (SF) aims to extract the values of certain types of attributes (or slots, such as person:cities\_of\_residence) for a given entity from a large collection of source documents.

Relation Extraction Slot Filling

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