no code implementations • 14 Oct 2024 • Mingwen Dong, Nischal Ashok Kumar, Yiqun Hu, Anuj Chauhan, Chung-Wei Hang, Shuaichen Chang, Lin Pan, Wuwei Lan, Henghui Zhu, Jiarong Jiang, Patrick Ng, Zhiguo Wang
Previous text-to-SQL datasets and systems have primarily focused on user questions with clear intentions that can be answered.
no code implementations • 18 Sep 2024 • Hideo Kobayashi, Wuwei Lan, Peng Shi, Shuaichen Chang, Jiang Guo, Henghui Zhu, Zhiguo Wang, Patrick Ng
While significant progress has been made on the text-to-SQL task, recent solutions repeatedly encode the same database schema for every question, resulting in unnecessary high inference cost and often overlooking crucial database knowledge.
1 code implementation • 31 Jan 2024 • Wenyue Hua, Jiang Guo, Mingwen Dong, Henghui Zhu, Patrick Ng, Zhiguo Wang
Our analysis over the chain-of-thought generation of edited models further uncover key reasons behind the inadequacy of existing knowledge editing methods from a reasoning standpoint, involving aspects on fact-wise editing, fact recall ability, and coherence in generation.
no code implementations • 30 May 2023 • Xingyu Fu, Sheng Zhang, Gukyeong Kwon, Pramuditha Perera, Henghui Zhu, Yuhao Zhang, Alexander Hanbo Li, William Yang Wang, Zhiguo Wang, Vittorio Castelli, Patrick Ng, Dan Roth, Bing Xiang
The open-ended Visual Question Answering (VQA) task requires AI models to jointly reason over visual and natural language inputs using world knowledge.
1 code implementation • 25 May 2023 • Wuwei Lan, Zhiguo Wang, Anuj Chauhan, Henghui Zhu, Alexander Li, Jiang Guo, Sheng Zhang, Chung-Wei Hang, Joseph Lilien, Yiqun Hu, Lin Pan, Mingwen Dong, Jun Wang, Jiarong Jiang, Stephen Ash, Vittorio Castelli, Patrick Ng, Bing Xiang
A practical text-to-SQL system should generalize well on a wide variety of natural language questions, unseen database schemas, and novel SQL query structures.
2 code implementations • 21 Jan 2023 • Shuaichen Chang, Jun Wang, Mingwen Dong, Lin Pan, Henghui Zhu, Alexander Hanbo Li, Wuwei Lan, Sheng Zhang, Jiarong Jiang, Joseph Lilien, Steve Ash, William Yang Wang, Zhiguo Wang, Vittorio Castelli, Patrick Ng, Bing Xiang
Neural text-to-SQL models have achieved remarkable performance in translating natural language questions into SQL queries.
1 code implementation • 30 Sep 2022 • Donghan Yu, Sheng Zhang, Patrick Ng, Henghui Zhu, Alexander Hanbo Li, Jun Wang, Yiqun Hu, William Wang, Zhiguo Wang, Bing Xiang
Question answering over knowledge bases (KBs) aims to answer natural language questions with factual information such as entities and relations in KBs.
1 code implementation • 3 Mar 2022 • Andy T. Liu, Wei Xiao, Henghui Zhu, Dejiao Zhang, Shang-Wen Li, Andrew Arnold
Recently, prompt-based learning for pre-trained language models has succeeded in few-shot Named Entity Recognition (NER) by exploiting prompts as task guidance to increase label efficiency.
no code implementations • NAACL 2022 • Xisen Jin, Dejiao Zhang, Henghui Zhu, Wei Xiao, Shang-Wen Li, Xiaokai Wei, Andrew Arnold, Xiang Ren
We evaluate PTLM's ability to adapt to new corpora while retaining learned knowledge in earlier corpora.
2 code implementations • Findings (ACL) 2022 • Dejiao Zhang, Wei Xiao, Henghui Zhu, Xiaofei Ma, Andrew O. Arnold
We then define an instance discrimination task regarding this neighborhood and generate the virtual augmentation in an adversarial training manner.
1 code implementation • EMNLP 2021 • Dejiao Zhang, Shang-Wen Li, Wei Xiao, Henghui Zhu, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang
Many recent successes in sentence representation learning have been achieved by simply fine-tuning on the Natural Language Inference (NLI) datasets with triplet loss or siamese loss.
1 code implementation • ACL 2021 • Alexander Hanbo Li, Patrick Ng, Peng Xu, Henghui Zhu, Zhiguo Wang, Bing Xiang
However, a large amount of world's knowledge is stored in structured databases, and need to be accessed using query languages such as SQL.
1 code implementation • ACL 2021 • Feng Nan, Cicero Nogueira dos santos, Henghui Zhu, Patrick Ng, Kathleen McKeown, Ramesh Nallapati, Dejiao Zhang, Zhiguo Wang, Andrew O. Arnold, Bing Xiang
A commonly observed problem with the state-of-the art abstractive summarization models is that the generated summaries can be factually inconsistent with the input documents.
2 code implementations • NAACL 2021 • Dejiao Zhang, Feng Nan, Xiaokai Wei, Shangwen Li, Henghui Zhu, Kathleen McKeown, Ramesh Nallapati, Andrew Arnold, Bing Xiang
Unsupervised clustering aims at discovering the semantic categories of data according to some distance measured in the representation space.
Ranked #1 on Short Text Clustering on AG News
1 code implementation • EACL 2021 • Feng Nan, Ramesh Nallapati, Zhiguo Wang, Cicero Nogueira dos santos, Henghui Zhu, Dejiao Zhang, Kathleen McKeown, Bing Xiang
A key challenge for abstractive summarization is ensuring factual consistency of the generated summary with respect to the original document.
no code implementations • EACL 2021 • Shuyang Li, Jin Cao, Mukund Sridhar, Henghui Zhu, Shang-Wen Li, Wael Hamza, Julian McAuley
Dialog State Tracking (DST), an integral part of modern dialog systems, aims to track user preferences and constraints (slots) in task-oriented dialogs.
3 code implementations • 18 Dec 2020 • Peng Shi, Patrick Ng, Zhiguo Wang, Henghui Zhu, Alexander Hanbo Li, Jun Wang, Cicero Nogueira dos santos, Bing Xiang
Most recently, there has been significant interest in learning contextual representations for various NLP tasks, by leveraging large scale text corpora to train large neural language models with self-supervised learning objectives, such as Masked Language Model (MLM).
Ranked #7 on Semantic Parsing on spider
1 code implementation • COLING 2020 • Boran Hao, Henghui Zhu, Ioannis Paschalidis
Domain knowledge is important for building Natural Language Processing (NLP) systems for low-resource settings, such as in the clinical domain.
1 code implementation • ACL 2021 • Yifan Gao, Henghui Zhu, Patrick Ng, Cicero Nogueira dos santos, Zhiguo Wang, Feng Nan, Dejiao Zhang, Ramesh Nallapati, Andrew O. Arnold, Bing Xiang
When multiple plausible answers are found, the system should rewrite the question for each answer to resolve the ambiguity.
no code implementations • Findings of the Association for Computational Linguistics 2020 • Dejiao Zhang, Ramesh Nallapati, Henghui Zhu, Feng Nan, Cicero Nogueira dos santos, Kathleen McKeown, Bing Xiang
Unsupervised domain adaptation addresses the problem of leveraging labeled data in a source domain to learn a well-performing model in a target domain where labels are unavailable.
Cross-Lingual Document Classification Document Classification +2
no code implementations • EMNLP (ClinicalNLP) 2020 • Morteza Pourreza Shahri, Amir Tahmasebi, Bingyang Ye, Henghui Zhu, Javed Aslam, Timothy Ferris
We present an ensemble method that consolidates the predictions of three models, capturing various attributes of textual information for automatic labeling of sentences with section labels.
1 code implementation • 25 Nov 2019 • Henghui Zhu, Feng Nan, Zhiguo Wang, Ramesh Nallapati, Bing Xiang
In this work, we define the problem of conversation structure modeling as identifying the parent utterance(s) to which each utterance in the conversation responds to.
no code implementations • WS 2019 • Elena Sergeeva, Henghui Zhu, Amir Tahmasebi, Peter Szolovits
Since the introduction of context-aware token representation techniques such as Embeddings from Language Models (ELMo) and Bidirectional Encoder Representations from Transformers (BERT), there has been numerous reports on improved performance on a variety of natural language tasks.
1 code implementation • 24 Oct 2018 • Henghui Zhu, Ioannis Ch. Paschalidis, Amir Tahmasebi
Next, a bidirectional LSTM-CRF model is trained for clinical concept extraction using the contextual word embedding model.
no code implementations • 31 May 2017 • Henghui Zhu, Feng Nan, Ioannis Paschalidis, Venkatesh Saligrama
Deep neural network (DNN) based approaches hold significant potential for reinforcement learning (RL) and have already shown remarkable gains over state-of-art methods in a number of applications.
no code implementations • 21 Jan 2017 • Manjesh K. Hanawal, Hao liu, Henghui Zhu, Ioannis Ch. Paschalidis
We assume that the policy belongs to a class of parameterized policies which are defined using features associated with the state-action pairs.