Yi Yang

Orcid: 0009-0002-0348-826X

Affiliations:
  • Hong Kong University of Science and Technology, Department of Information Systems and Operations Management, Hong Kong
  • Northwestern University, Evanston, IL, USA (PhD 2015)


According to our database1, Yi Yang authored at least 54 papers between 2013 and 2024.

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

Timeline

Legend:

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PhD thesis 
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Links

Online presence:

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Bibliography

2024
Should Fairness be a Metric or a Model? A Model-based Framework for Assessing Bias in Machine Learning Pipelines.
ACM Trans. Inf. Syst., July, 2024

TM-OKC: An Unsupervised Topic Model for Text in Online Knowledge Communities.
MIS Q., 2024

LLM-Measure: Generating Valid, Consistent, and Reproducible Text-Based Measures for Social Science Research.
CoRR, 2024

EconNLI: Evaluating Large Language Models on Economics Reasoning.
CoRR, 2024

Improving Weak-to-Strong Generalization with Reliability-Aware Alignment.
CoRR, 2024

Understanding Privacy Risks of Embeddings Induced by Large Language Models.
CoRR, 2024

Beyond Surface Similarity: Detecting Subtle Semantic Shifts in Financial Narratives.
CoRR, 2024

Do LLMs Know about Hallucination? An Empirical Investigation of LLM's Hidden States.
CoRR, 2024

MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries.
CoRR, 2024

Self-Explainable Next POI Recommendation.
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2024

Exploring the Relationship between In-Context Learning and Instruction Tuning.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

2023
sDTM: A Supervised Bayesian Deep Topic Model for Text Analytics.
Inf. Syst. Res., March, 2023

Deep Cross-Attention Network for Crowdfunding Success Prediction.
IEEE Trans. Multim., 2023

Unlocking the Power of Voice for Financial Risk Prediction: A Theory-Driven Deep Learning Design Approach.
MIS Q., 2023

Model Stealing Attack against Recommender System.
CoRR, 2023

Model Stealing Attack against Graph Classification with Authenticity, Uncertainty and Diversity.
CoRR, 2023

Bias A-head? Analyzing Bias in Transformer-Based Language Model Attention Heads.
CoRR, 2023

FinEntity: Entity-level Sentiment Classification for Financial Texts.
CoRR, 2023

InvestLM: A Large Language Model for Investment using Financial Domain Instruction Tuning.
CoRR, 2023

FinEntity: Entity-level Sentiment Classification for Financial Texts.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Is ChatGPT a Financial Expert? Evaluating Language Models on Financial Natural Language Processing.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Predict the Future from the Past? On the Temporal Data Distribution Shift in Financial Sentiment Classifications.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Causal-Debias: Unifying Debiasing in Pretrained Language Models and Fine-tuning via Causal Invariant Learning.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Debiasing Intrinsic Bias and Application Bias Jointly via Invariant Risk Minimization (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Exploring Hypergraph of Earnings Call for Risk Prediction (Student Abstract).
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Extracting Actionable Insights from Text Data: A Stable Topic Model Approach.
MIS Q., 2022

Analyzing Firm Reports for Volatility Prediction: A Knowledge-Driven Text-Embedding Approach.
INFORMS J. Comput., 2022

Benchmarking Intersectional Biases in NLP.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

BARLE: Background-Aware Representation Learning for Background Shift Out-of-Distribution Detection.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Auto-Debias: Debiasing Masked Language Models with Automated Biased Prompts.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Buy Tesla, Sell Ford: Assessing Implicit Stock Market Preference in Pre-trained Language Models.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2022

2021
Unifying Online and Offline Preference for Social Link Prediction.
INFORMS J. Comput., 2021

Rumor Detection on Social Media with Event Augmentations.
Proceedings of the SIGIR '21: The 44th International ACM SIGIR Conference on Research and Development in Information Retrieval, 2021

Learning Numeracy: A Simple Yet Effective Number Embedding Approach Using Knowledge Graph.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2021, 2021

Constructing a Psychometric Testbed for Fair Natural Language Processing.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
FinBERT: A Pretrained Language Model for Financial Communications.
CoRR, 2020

Generating Plausible Counterfactual Explanations for Deep Transformers in Financial Text Classification.
Proceedings of the 28th International Conference on Computational Linguistics, 2020

Neural Topic Model with Attention for Supervised Learning.
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

Interpretable Operational Risk Classification with Semi-Supervised Variational Autoencoder.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Interpreting Twitter User Geolocation.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
What You Say and How You Say It Matters: Predicting Stock Volatility Using Verbal and Vocal Cues.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
vec2Link: Unifying Heterogeneous Data for Social Link Prediction.
Proceedings of the 27th ACM International Conference on Information and Knowledge Management, 2018

2016
Beating the Artificial Chaos: Fighting OSN Spam Using Its Own Templates.
IEEE/ACM Trans. Netw., 2016

The Stability and Usability of Statistical Topic Models.
ACM Trans. Interact. Intell. Syst., 2016

Improving Topic Model Stability for Effective Document Exploration.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

2015
User-directed Non-Disruptive Topic Model Update for Effective Exploration of Dynamic Content.
Proceedings of the 20th International Conference on Intelligent User Interfaces, 2015

Efficient Methods for Incorporating Knowledge into Topic Models.
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, 2015

Efficient Methods for Inferring Large Sparse Topic Hierarchies.
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, 2015

2014
Incorporating conditional random fields and active learning to improve sentiment identification.
Neural Networks, 2014

Learning Representations for Weakly Supervised Natural Language Processing Tasks.
Comput. Linguistics, 2014

A Systematic Framework for Sentiment Identification by Modeling User Social Effects.
Proceedings of the 2014 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT), Warsaw, Poland, August 11-14, 2014, 2014

Spam ain't as diverse as it seems: throttling OSN spam with templates underneath.
Proceedings of the 30th Annual Computer Security Applications Conference, 2014

2013
WebSAIL Wikifier: English Entity Linking at TAC 2013.
Proceedings of the Sixth Text Analysis Conference, 2013

Overcoming the Memory Bottleneck in Distributed Training of Latent Variable Models of Text.
Proceedings of the Human Language Technologies: Conference of the North American Chapter of the Association of Computational Linguistics, 2013


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