Chenguang Zhu

Orcid: 0000-0001-6955-8924

Affiliations:
  • Microsoft Research, Redmond, WA, USA
  • Stanford University, Computer Science Department, CA, USA (PhD 2016)


According to our database1, Chenguang Zhu authored at least 101 papers between 2012 and 2024.

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Timeline

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Bibliography

2024
Knowledge-augmented Methods for Natural Language Processing
Springer Briefs in Computer Science, Springer, ISBN: 978-981-97-0749-2, 2024

Law of the Weakest Link: Cross Capabilities of Large Language Models.
CoRR, 2024

See What LLMs Cannot Answer: A Self-Challenge Framework for Uncovering LLM Weaknesses.
CoRR, 2024

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data.
Proceedings of the Findings of the Association for Computational Linguistics: NAACL 2024, 2024

PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documents.
Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics, 2024

How Does In-Context Learning Help Prompt Tuning?
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2024, 2024

Small Models are Valuable Plug-ins for Large Language Models.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

2023
MACSum: Controllable Summarization with Mixed Attributes.
Trans. Assoc. Comput. Linguistics, 2023

The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions.
CoRR, 2023

PEARL: Prompting Large Language Models to Plan and Execute Actions Over Long Documents.
CoRR, 2023

i-Code Studio: A Configurable and Composable Framework for Integrative AI.
CoRR, 2023

LMGQS: A Large-scale Dataset for Query-focused Summarization.
CoRR, 2023

i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data.
CoRR, 2023

G-Eval: NLG Evaluation using GPT-4 with Better Human Alignment.
CoRR, 2023

Knowledge-Augmented Methods for Natural Language Processing.
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Any-to-Any Generation via Composable Diffusion.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Generate rather than Retrieve: Large Language Models are Strong Context Generators.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Auto-Instruct: Automatic Instruction Generation and Ranking for Black-Box Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

InheritSumm: A General, Versatile and Compact Summarizer by Distilling from GPT.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

LMGQS: A Large-scale Dataset for Query-focused Summarization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Automatic Prompt Optimization with "Gradient Descent" and Beam Search.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

The Shifted and The Overlooked: A Task-oriented Investigation of User-GPT Interactions.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

In-Context Demonstration Selection with Cross Entropy Difference.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Improving Commonsense in Vision-Language Models via Knowledge Graph Riddles.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Unifying Vision, Text, and Layout for Universal Document Processing.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

UniSumm and SummZoo: Unified Model and Diverse Benchmark for Few-Shot Summarization.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

i-Code: An Integrative and Composable Multimodal Learning Framework.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
A Survey of Knowledge-enhanced Text Generation.
ACM Comput. Surv., January, 2022

UniSumm: Unified Few-shot Summarization with Multi-Task Pre-Training and Prefix-Tuning.
CoRR, 2022

Empowering Language Models with Knowledge Graph Reasoning for Question Answering.
CoRR, 2022

Towards a Unified Multi-Dimensional Evaluator for Text Generation.
CoRR, 2022

FAST: Improving Controllability for Text Generation with Feedback Aware Self-Training.
CoRR, 2022

Z-Code++: A Pre-trained Language Model Optimized for Abstractive Summarization.
CoRR, 2022

Impossible Triangle: What's Next for Pre-trained Language Models?
CoRR, 2022

Unsupervised Summarization with Customized Granularities.
CoRR, 2022

Language Models with Image Descriptors are Strong Few-Shot Video-Language Learners.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

REVIVE: Regional Visual Representation Matters in Knowledge-Based Visual Question Answering.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Human Parity on CommonsenseQA: Augmenting Self-Attention with External Attention.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Unsupervised Multi-Granularity Summarization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Towards a Unified Multi-Dimensional Evaluator for Text Generation.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

A Unified Encoder-Decoder Framework with Entity Memory.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Narrate Dialogues for Better Summarization.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

ParaTag: A Dataset of Paraphrase Tagging for Fine-Grained Labels, NLG Evaluation, and Data Augmentation.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Automatic Rule Induction for Efficient Semi-Supervised Learning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Leveraging Locality in Abstractive Text Summarization.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Empowering Language Models with Knowledge Graph Reasoning for Open-Domain Question Answering.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Retrieval Augmentation for Commonsense Reasoning: A Unified Approach.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Task Compass: Scaling Multi-task Pre-training with Task Prefix.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

AdaPrompt: Adaptive Model Training for Prompt-based NLP.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

CLIP-Event: Connecting Text and Images with Event Structures.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

An Empirical Study of Training End-to-End Vision-and-Language Transformers.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2022

KG-FiD: Infusing Knowledge Graph in Fusion-in-Decoder for Open-Domain Question Answering.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Training Data is More Valuable than You Think: A Simple and Effective Method by Retrieving from Training Data.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

DYLE: Dynamic Latent Extraction for Abstractive Long-Input Summarization.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

End-to-End Segmentation-based News Summarization.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Leveraging Visual Knowledge in Language Tasks: An Empirical Study on Intermediate Pre-training for Cross-Modal Knowledge Transfer.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Leveraging Knowledge in Multilingual Commonsense Reasoning.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Diversifying Content Generation for Commonsense Reasoning with Mixture of Knowledge Graph Experts.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Dict-BERT: Enhancing Language Model Pre-training with Dictionary.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

Summ<sup>N</sup>: A Multi-Stage Summarization Framework for Long Input Dialogues and Documents.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

DialogLM: Pre-trained Model for Long Dialogue Understanding and Summarization.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

JAKET: Joint Pre-training of Knowledge Graph and Language Understanding.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
MLP Architectures for Vision-and-Language Modeling: An Empirical Study.
CoRR, 2021

SYNERGY: Building Task Bots at Scale Using Symbolic Knowledge and Machine Teaching.
CoRR, 2021

Does Knowledge Help General NLU? An Empirical Study.
CoRR, 2021

Leveraging Lead Bias for Zero-shot Abstractive News Summarization.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Enhancing Factual Consistency of Abstractive Summarization.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

SPLAT: Speech-Language Joint Pre-Training for Spoken Language Understanding.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Data Augmentation for Spoken Language Understanding via Pretrained Language Models.
Proceedings of the 22nd Annual Conference of the International Speech Communication Association, Interspeech 2021, Brno, Czechia, August 30, 2021

Sentence-Permuted Paragraph Generation.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Want To Reduce Labeling Cost? GPT-3 Can Help.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Injecting Entity Types into Entity-Guided Text Generation.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

An Exploratory Study on Long Dialogue Summarization: What Works and What's Next.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Fusing Context Into Knowledge Graph for Commonsense Question Answering.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

Retrieval Enhanced Model for Commonsense Generation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

RADDLE: An Evaluation Benchmark and Analysis Platform for Robust Task-oriented Dialog Systems.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020
Fusing Context Into Knowledge Graph for Commonsense Reasoning.
CoRR, 2020

Semi-Supervised Speech-Language Joint Pre-Training for Spoken Language Understanding.
CoRR, 2020

Mind The Facts: Knowledge-Boosted Coherent Abstractive Text Summarization.
CoRR, 2020

Meta Dialogue Policy Learning.
CoRR, 2020

Data Augmentation for Spoken Language Understanding via Pretrained Models.
CoRR, 2020

End-to-End Abstractive Summarization for Meetings.
CoRR, 2020

Boosting Factual Correctness of Abstractive Summarization with Knowledge Graph.
CoRR, 2020

Mixed-Lingual Pre-training for Cross-lingual Summarization.
Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing, 2020

A Hierarchical Network for Abstractive Meeting Summarization with Cross-Domain Pretraining.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

TED: A Pretrained Unsupervised Summarization Model with Theme Modeling and Denoising.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Few-shot Natural Language Generation for Task-Oriented Dialog.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

2019
Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization.
CoRR, 2019

SIM: A Slot-Independent Neural Model for Dialogue State Tracking.
Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue, 2019

Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering.
Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Multi-task Learning for Natural Language Generation in Task-Oriented Dialogue.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Embedding Imputation with Grounded Language Information.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering.
CoRR, 2018

Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Scientific Question Answering.
CoRR, 2018

2017
Reducing inefficiencies in taxi systems.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017

2015
Analysis and modeling of large-scale systems : taxis and social polling.
PhD thesis, 2015

Polling one's friends: A graph theoretic view.
Proceedings of the 53rd Annual Allerton Conference on Communication, 2015

2012
Information diffusion and external influence in networks.
Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2012


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