Search Results for author: Jiang Guo

Found 23 papers, 10 papers with code

Towards a Holistic Evaluation of LLMs on Factual Knowledge Recall

no code implementations24 Apr 2024 Jiaqing Yuan, Lin Pan, Chung-Wei Hang, Jiang Guo, Jiarong Jiang, Bonan Min, Patrick Ng, Zhiguo Wang

By further decoupling model known and unknown knowledge, we find the degradation is attributed to exemplars that contradict a model's known knowledge, as well as the number of such exemplars.


Propagation and Pitfalls: Reasoning-based Assessment of Knowledge Editing through Counterfactual Tasks

no code implementations31 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.

counterfactual knowledge editing

UNITE: A Unified Benchmark for Text-to-SQL Evaluation

1 code implementation25 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.


RxnScribe: A Sequence Generation Model for Reaction Diagram Parsing

1 code implementation19 May 2023 Yujie Qian, Jiang Guo, Zhengkai Tu, Connor W. Coley, Regina Barzilay

Reaction diagram parsing is the task of extracting reaction schemes from a diagram in the chemistry literature.

Structured Prediction

Designing thermal radiation metamaterials via hybrid adversarial autoencoder and Bayesian optimization

no code implementations26 Apr 2022 Dezhao Zhu, Jiang Guo, Gang Yu, C. Y. Zhao, Hong Wang, Shenghong Ju

Designing thermal radiation metamaterials is challenging especially for problems with high degrees of freedom and complex objective.

Bayesian Optimization

Curriculum CycleGAN for Textual Sentiment Domain Adaptation with Multiple Sources

1 code implementation17 Nov 2020 Sicheng Zhao, Yang Xiao, Jiang Guo, Xiangyu Yue, Jufeng Yang, Ravi Krishna, Pengfei Xu, Kurt Keutzer

C-CycleGAN transfers source samples at instance-level to an intermediate domain that is closer to the target domain with sentiment semantics preserved and without losing discriminative features.

Domain Adaptation Generative Adversarial Network +2

Cross-Lingual BERT Transformation for Zero-Shot Dependency Parsing

1 code implementation IJCNLP 2019 Yuxuan Wang, Wanxiang Che, Jiang Guo, Yijia Liu, Ting Liu

In this approach, a linear transformation is learned from contextual word alignments to align the contextualized embeddings independently trained in different languages.

Dependency Parsing Language Modelling +2

GraphIE: A Graph-Based Framework for Information Extraction

2 code implementations NAACL 2019 Yujie Qian, Enrico Santus, Zhijing Jin, Jiang Guo, Regina Barzilay

Most modern Information Extraction (IE) systems are implemented as sequential taggers and only model local dependencies.

The HIT-SCIR System for End-to-End Parsing of Universal Dependencies

no code implementations CONLL 2017 Wanxiang Che, Jiang Guo, Yuxuan Wang, Bo Zheng, Huaipeng Zhao, Yang Liu, Dechuan Teng, Ting Liu

Our system includes three pipelined components: \textit{tokenization}, \textit{Part-of-Speech} (POS) \textit{tagging} and \textit{dependency parsing}.

Dependency Parsing Information Retrieval +4

A Unified Architecture for Semantic Role Labeling and Relation Classification

no code implementations COLING 2016 Jiang Guo, Wanxiang Che, Haifeng Wang, Ting Liu, Jun Xu

This paper describes a unified neural architecture for identifying and classifying multi-typed semantic relations between words in a sentence.

Classification Feature Engineering +9

A General Framework for Content-enhanced Network Representation Learning

no code implementations10 Oct 2016 Xiaofei Sun, Jiang Guo, Xiao Ding, Ting Liu

This paper investigates the problem of network embedding, which aims at learning low-dimensional vector representation of nodes in networks.

Network Embedding Node Classification

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