Search Results for author: Zhengzhong Liu

Found 25 papers, 10 papers with code

Pandora: Towards General World Model with Natural Language Actions and Video States

no code implementations12 Jun 2024 Jiannan Xiang, Guangyi Liu, Yi Gu, Qiyue Gao, Yuting Ning, Yuheng Zha, Zeyu Feng, Tianhua Tao, Shibo Hao, Yemin Shi, Zhengzhong Liu, Eric P. Xing, Zhiting Hu

This paper makes a step towards building a general world model by introducing Pandora, a hybrid autoregressive-diffusion model that simulates world states by generating videos and allows real-time control with free-text actions.

SlimPajama-DC: Understanding Data Combinations for LLM Training

1 code implementation19 Sep 2023 Zhiqiang Shen, Tianhua Tao, Liqun Ma, Willie Neiswanger, Zhengzhong Liu, Hongyi Wang, Bowen Tan, Joel Hestness, Natalia Vassilieva, Daria Soboleva, Eric Xing

This paper aims to understand the impacts of various data combinations (e. g., web text, Wikipedia, GitHub, books) on the pretraining of large language models using SlimPajama.

ASDOT: Any-Shot Data-to-Text Generation with Pretrained Language Models

1 code implementation9 Oct 2022 Jiannan Xiang, Zhengzhong Liu, Yucheng Zhou, Eric P. Xing, Zhiting Hu

In the data disambiguation stage, we employ the prompted GPT-3 model to understand possibly ambiguous triples from the input data and convert each into a short sentence with reduced ambiguity.

Data-to-Text Generation Sentence +1

Text Generation with Efficient (Soft) $Q$-Learning

no code implementations29 Sep 2021 Han Guo, Bowen Tan, Zhengzhong Liu, Eric Xing, Zhiting Hu

We apply the approach to a wide range of text generation tasks, including learning from noisy/negative examples, adversarial attacks, and prompt generation.

Q-Learning Reinforcement Learning (RL) +1

Compression, Transduction, and Creation: A Unified Framework for Evaluating Natural Language Generation

1 code implementation EMNLP 2021 Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu

Based on the nature of information change from input to output, we classify NLG tasks into compression (e. g., summarization), transduction (e. g., text rewriting), and creation (e. g., dialog).

nlg evaluation Style Transfer +2

Cross-document Event Identity via Dense Annotation

1 code implementation CoNLL (EMNLP) 2021 Adithya Pratapa, Zhengzhong Liu, Kimihiro Hasegawa, Linwei Li, Yukari Yamakawa, Shikun Zhang, Teruko Mitamura

To this end, we design a new annotation workflow with careful quality control and an easy-to-use annotation interface.

Efficient (Soft) Q-Learning for Text Generation with Limited Good Data

1 code implementation14 Jun 2021 Han Guo, Bowen Tan, Zhengzhong Liu, Eric P. Xing, Zhiting Hu

We apply the approach to a wide range of novel text generation tasks, including learning from noisy/negative examples, adversarial attacks, and prompt generation.

Q-Learning Reinforcement Learning (RL) +1

A Data-Centric Framework for Composable NLP Workflows

1 code implementation EMNLP 2020 Zhengzhong Liu, Guanxiong Ding, Avinash Bukkittu, Mansi Gupta, Pengzhi Gao, Atif Ahmed, Shikun Zhang, Xin Gao, Swapnil Singhavi, Linwei Li, Wei Wei, Zecong Hu, Haoran Shi, Haoying Zhang, Xiaodan Liang, Teruko Mitamura, Eric P. Xing, Zhiting Hu

Empirical natural language processing (NLP) systems in application domains (e. g., healthcare, finance, education) involve interoperation among multiple components, ranging from data ingestion, human annotation, to text retrieval, analysis, generation, and visualization.

Retrieval Text Retrieval

A Two-Step Approach for Implicit Event Argument Detection

no code implementations ACL 2020 Zhisong Zhang, Xiang Kong, Zhengzhong Liu, Xuezhe Ma, Eduard Hovy

It remains a challenge to detect implicit arguments, calling for more future work of document-level modeling for this task.

Sentence Vocal Bursts Valence Prediction

Automatic Event Salience Identification

1 code implementation EMNLP 2018 Zhengzhong Liu, Chenyan Xiong, Teruko Mitamura, Eduard Hovy

Our analyses demonstrate that our neural model captures interesting connections between salience and discourse unit relations (e. g., scripts and frame structures).

Towards Better Text Understanding and Retrieval through Kernel Entity Salience Modeling

no code implementations3 May 2018 Chenyan Xiong, Zhengzhong Liu, Jamie Callan, Tie-Yan Liu

The salience model also improves ad hoc search accuracy, providing effective ranking features by modeling the salience of query entities in candidate documents.

Retrieval

Harnessing Deep Neural Networks with Logic Rules

2 code implementations ACL 2016 Zhiting Hu, Xuezhe Ma, Zhengzhong Liu, Eduard Hovy, Eric Xing

Combining deep neural networks with structured logic rules is desirable to harness flexibility and reduce uninterpretability of the neural models.

named-entity-recognition Named Entity Recognition +2

Unsupervised Ranking Model for Entity Coreference Resolution

no code implementations NAACL 2016 Xuezhe Ma, Zhengzhong Liu, Eduard Hovy

Coreference resolution is one of the first stages in deep language understanding and its importance has been well recognized in the natural language processing community.

coreference-resolution

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