Zilong Wang

Affiliations:
  • University of California, San Diego, CA, USA
  • Peking University, Institute of Computer Science and Technology, ijing, China


According to our database1, Zilong Wang authored at least 25 papers between 2019 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
OfficeBench: Benchmarking Language Agents across Multiple Applications for Office Automation.
CoRR, 2024

Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting.
CoRR, 2024

MetaIE: Distilling a Meta Model from LLM for All Kinds of Information Extraction Tasks.
CoRR, 2024

LDB: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step.
CoRR, 2024

TableRAG: Million-Token Table Understanding with Language Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

DOCMASTER: A Unified Platform for Annotation, Training, & Inference in Document Question-Answering.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: System Demonstrations, 2024

Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Incubating Text Classifiers Following User Instruction with Nothing but LLM.
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

Towards Few-shot Entity Recognition in Document Images: A Graph Neural Network Approach Robust to Image Manipulation.
Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step by Step.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

LMDX: Language Model-based Document Information Extraction and Localization.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

Answer is All You Need: Instruction-following Text Embedding via Answering the Question.
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

Can LLM Replace Stack Overflow? A Study on Robustness and Reliability of Large Language Model Code Generation.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
EmojiLM: Modeling the New Emoji Language.
CoRR, 2023

A Study on Robustness and Reliability of Large Language Model Code Generation.
CoRR, 2023

Towards Zero-shot Relation Extraction in Web Mining: A Multimodal Approach with Relative XML Path.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

2022
MGDoc: Pre-training with Multi-granular Hierarchy for Document Image Understanding.
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Formulating Few-shot Fine-tuning Towards Language Model Pre-training: A Pilot Study on Named Entity Recognition.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Towards Few-shot Entity Recognition in Document Images: A Label-aware Sequence-to-Sequence Framework.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021
GroupLink: An End-to-end Multitask Method for Word Grouping and Relation Extraction in Form Understanding.
CoRR, 2021

LayoutReader: Pre-training of Text and Layout for Reading Order Detection.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
TransModality: An End2End Fusion Method with Transformer for Multimodal Sentiment Analysis.
Proceedings of the WWW '20: The Web Conference 2020, Taipei, Taiwan, April 20-24, 2020, 2020

DocStruct: A Multimodal Method to Extract Hierarchy Structure in Document for General Form Understanding.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Exploring Semantic Capacity of Terms.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
BAB-QA: A New Neural Model for Emotion Detection in Multi-party Dialogue.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2019


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