---
title: "Workshop on Trustworthy NLP 2023 — all accepted papers"
description: "All 28 papers of Workshop on Trustworthy NLP 2023, the most cited first; those with our summary link to it."
canonical: "https://research.elamur.ai/free/en/venues/trustnlp/2023/papers/"
---
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# Workshop on Trustworthy NLP 2023: all accepted papers

28 papers · the most cited first · [← Workshop on Trustworthy NLP 2023](https://md.research.elamur.ai/free/en/venues/trustnlp/2023/)

1. **[Can we trust the evaluation on ChatGPT?](https://md.research.elamur.ai/free/en/papers/aiyappa-2023-can-we-trust-evaluation-chatgpt/)**Rachith Aiyappa, Jisun An, Haewoon Kwak et al.*68 citations · our summary*
2. **[Privacy- and Utility-Preserving NLP with Anonymized data: A case study of Pseudonymization ↗](https://aclanthology.org/2023.trustnlp-1.20/)**Oleksandr Yermilov, Vipul Raheja, Artem Chernodub*30 citations*
3. **[Detecting Personal Information in Training Corpora: an Analysis ↗](https://aclanthology.org/2023.trustnlp-1.18/)**Nishant Subramani, Sasha Luccioni, Jesse Dodge et al.*20 citations*
4. **[Training Data Extraction From Pre-trained Language Models: A Survey ↗](https://aclanthology.org/2023.trustnlp-1.23/)**Shotaro Ishihara*19 citations*
5. **[Automated Ableism: An Exploration of Explicit Disability Biases in Sentiment and Toxicity Analysis Models ↗](https://aclanthology.org/2023.trustnlp-1.3/)**Pranav Narayanan Venkit, Mukund Srinath, Shomir Wilson*15 citations*
6. **[Distinguishing Fact from Fiction: A Benchmark Dataset for Identifying Machine-Generated Scientific Papers in the LLM Era. ↗](https://aclanthology.org/2023.trustnlp-1.17/)**Edoardo Mosca, Mohamed Hesham Ibrahim Abdalla, Paolo Basso et al.*14 citations*
7. **[Improving Factuality of Abstractive Summarization via Contrastive Reward Learning ↗](https://aclanthology.org/2023.trustnlp-1.6/)**I-chun Chern, Zhiruo Wang, Sanjan Das et al.*11 citations*
8. **[Strength in Numbers: Estimating Confidence of Large Language Models by Prompt Agreement ↗](https://aclanthology.org/2023.trustnlp-1.28/)**Gwenyth Portillo Wightman, Alexandra Delucia, Mark Dredze*10 citations*
9. **[Reliability Check: An Analysis of GPT-3's Response to Sensitive Topics and Prompt Wording ↗](https://aclanthology.org/2023.trustnlp-1.8/)**Aisha Khatun, Daniel Brown*9 citations*
10. **[GPTs Don't Keep Secrets: Searching for Backdoor Watermark Triggers in Autoregressive Language Models ↗](https://aclanthology.org/2023.trustnlp-1.21/)**Evan Lucas, Timothy Havens*7 citations*
11. **[Guiding Text-to-Text Privatization by Syntax ↗](https://aclanthology.org/2023.trustnlp-1.14/)**Stefan Arnold, Dilara Yesilbas, Sven Weinzierl*6 citations*
12. **[IMBERT: Making BERT Immune to Insertion-based Backdoor Attacks ↗](https://aclanthology.org/2023.trustnlp-1.25/)**Xuanli He, Jun Wang, Benjamin Rubinstein et al.*6 citations*
13. **[Expanding Scope: Adapting English Adversarial Attacks to Chinese ↗](https://aclanthology.org/2023.trustnlp-1.24/)**Hanyu Liu, Chengyuan Cai, Yanjun Qi*5 citations*
14. **[Pay Attention to the Robustness of Chinese Minority Language Models! Syllable-level Textual Adversarial Attack on Tibetan Script ↗](https://aclanthology.org/2023.trustnlp-1.4/)**Xi Cao, Dolma Dawa, Nuo Qun et al.*5 citations*
15. **[A Keyword Based Approach to Understanding the Overpenalization of Marginalized Groups by English Marginal Abuse Models on Twitter](https://md.research.elamur.ai/free/en/papers/yee-2023-keyword-based-approach-understanding-overpenalization/)**Kyra Yee, Alice Schoenauer Sebag, Olivia Redfield et al.*4 citations · our summary*
16. **[Towards Faithful Explanations for Text Classification with Robustness Improvement and Explanation Guided Training ↗](https://aclanthology.org/2023.trustnlp-1.1/)**Dongfang Li, Baotian Hu, Qingcai Chen et al.*4 citations*
17. **[An Empirical Study of Metrics to Measure Representational Harms in Pre-Trained Language Models](https://md.research.elamur.ai/free/en/papers/hosseini-2023-empirical-study-metrics-measure-representational/)**Saghar Hosseini, Hamid Palangi, Ahmed Hassan Awadallah*3 citations · our summary*
18. **[DEPTH+: An Enhanced Depth Metric for Wikipedia Corpora Quality ↗](https://aclanthology.org/2023.trustnlp-1.16/)**Saied Alshahrani, Norah Alshahrani, Jeanna Matthews*3 citations*
19. **[Make Text Unlearnable: Exploiting Effective Patterns to Protect Personal Data ↗](https://aclanthology.org/2023.trustnlp-1.22/)**Xinzhe Li, Ming Liu*3 citations*
20. **[Driving Context into Text-to-Text Privatization ↗](https://aclanthology.org/2023.trustnlp-1.2/)**Stefan Arnold, Dilara Yesilbas, Sven Weinzierl*2 citations*
21. **[Enabling Classifiers to Make Judgements Explicitly Aligned with Human Values ↗](https://aclanthology.org/2023.trustnlp-1.27/)**Yejin Bang, Tiezheng Yu, Andrea Madotto et al.*2 citations*
22. **[Enhancing textual counterfactual explanation intelligibility through Counterfactual Feature Importance ↗](https://aclanthology.org/2023.trustnlp-1.19/)**Milan Bhan, Jean-noel Vittaut, Nicolas Chesneau et al.*2 citations*
23. **[On The Real-world Performance of Machine Translation: Exploring Social Media Post-authors' Perspectives ↗](https://aclanthology.org/2023.trustnlp-1.26/)**Ananya Gupta, Jae Takeuchi, Bart Knijnenburg*2 citations*
24. **[Are fairness metric scores enough to assess discrimination biases in machine learning? ↗](https://aclanthology.org/2023.trustnlp-1.15/)**Fanny Jourdan, Laurent Risser, Jean-michel Loubes et al.*1 citation*
25. **[Debunking Biases in Attention ↗](https://aclanthology.org/2023.trustnlp-1.13/)**Shijing Chen, Usman Naseem, Imran Razzak*1 citation*
26. **[Examining the Causal Impact of First Names on Language Models: The Case of Social Commonsense Reasoning ↗](https://aclanthology.org/2023.trustnlp-1.7/)**Sullam Jeoung, Jana Diesner, Halil Kilicoglu*1 citation*
27. **[Linguistic Properties of Truthful Response ↗](https://aclanthology.org/2023.trustnlp-1.12/)**Bruce W. Lee, Benedict Florance Arockiaraj, Helen Jin*1 citation*
28. **[Sample Attackability in Natural Language Adversarial Attacks ↗](https://aclanthology.org/2023.trustnlp-1.9/)**Vyas Raina, Mark Gales*1 citation*
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