📰 INLG 2023 — accepted papers

INLG 2023 is the 2023 edition of the International Natural Language Generation Conference (INLG), held in Prague, Czechia, September 2023 (publisher: Association for Computational Linguistics). The ACL Anthology lists 59 papers of it in 2 tracks; our library holds 2 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 Prague, Czechia · 🗓 September 2023

Tracks

Main55System Demonstrations4

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

1. The Next Chapter: A Study of Large Language Models in Storytelling ↗Zhuohan Xie, Trevor Cohn, Jey Han Lau28 citations
2. Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of PrivacyDaphne Ippolito, Florian Tramer, Milad Nasr et al.27 citations · our summary
3. This is not correct! Negation-aware Evaluation of Language Generation Systems ↗Miriam Anschütz, Diego Miguel Lozano, Georg Groh13 citations
4. Summaries as Captions: Generating Figure Captions for Scientific Documents with Automated Text Summarization ↗Chieh-Yang Huang, Ting-Yao Hsu, Ryan Rossi et al.8 citations
5. Leveraging Low-resource Parallel Data for Text Style Transfer ↗Sourabrata Mukherjee, Ondrej Dusek6 citations
6. Metric-Based In-context Learning: A Case Study in Text Simplification ↗Subhadra Vadlamannati, Gözde Şahin6 citations
7. Tackling Hallucinations in Neural Chart Summarization ↗Saad Obaid ul Islam, Iza Škrjanec, Ondrej Dusek et al.6 citations
8. Trustworthiness of Children Stories Generated by Large Language Models ↗Prabin Bhandari, Hannah Brennan6 citations
9. Claim Optimization in Computational Argumentation ↗Gabriella Skitalinskaya, Maximilian Spliethöver, Henning Wachsmuth5 citations
10. Generating Multiple Questions from Presentation Transcripts: A Pilot Study on Earnings Conference Calls ↗Yining Juan, Chung-Chi Chen, Hen-Hsen Huang et al.4 citations

All accepted papers (59)

The most cited first; 2 with our summary link to their page here, the others to the original.

1. The Next Chapter: A Study of Large Language Models in Storytelling ↗Zhuohan Xie, Trevor Cohn, Jey Han Lau28 citations
2. Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of PrivacyDaphne Ippolito, Florian Tramer, Milad Nasr et al.27 citations · our summary
3. This is not correct! Negation-aware Evaluation of Language Generation Systems ↗Miriam Anschütz, Diego Miguel Lozano, Georg Groh13 citations
4. Summaries as Captions: Generating Figure Captions for Scientific Documents with Automated Text Summarization ↗Chieh-Yang Huang, Ting-Yao Hsu, Ryan Rossi et al.8 citations
5. Leveraging Low-resource Parallel Data for Text Style Transfer ↗Sourabrata Mukherjee, Ondrej Dusek6 citations
6. Metric-Based In-context Learning: A Case Study in Text Simplification ↗Subhadra Vadlamannati, Gözde Şahin6 citations
7. Tackling Hallucinations in Neural Chart Summarization ↗Saad Obaid ul Islam, Iza Škrjanec, Ondrej Dusek et al.6 citations
8. Trustworthiness of Children Stories Generated by Large Language Models ↗Prabin Bhandari, Hannah Brennan6 citations
9. Claim Optimization in Computational Argumentation ↗Gabriella Skitalinskaya, Maximilian Spliethöver, Henning Wachsmuth5 citations
10. Generating Multiple Questions from Presentation Transcripts: A Pilot Study on Earnings Conference Calls ↗Yining Juan, Chung-Chi Chen, Hen-Hsen Huang et al.4 citations
11. Reverse-Engineering Decoding Strategies Given Blackbox Access to a Language Generation System ↗Daphne Ippolito, Nicholas Carlini, Katherine Lee et al.4 citations
12. XF2T: Cross-lingual Fact-to-Text Generation for Low-Resource Languages ↗Shivprasad Sagare, Tushar Abhishek, Bhavyajeet Singh et al.4 citations
13. Entropy-based Sampling for Abstractive Multi-document Summarization in Low-resource Settings ↗Laura Mascarell, Ribin Chalumattu, Julien Heitmann3 citations
14. GAN-LM: Generative Adversarial Network using Language Models for Downstream Applications ↗Dae Yon Hwang, Yaroslav Nechaev, Cyprien de Lichy et al.3 citations
15. Memories for Virtual AI Characters ↗Fabian Landwehr, Erika Varis Doggett, Romann M. Weber3 citations
16. Reducing named entity hallucination risk to ensure faithful summary generation ↗Eunice Akani, Benoit Favre, Frederic Bechet et al.3 citations
17. ChatGPT's Information Seeking Strategy: Insights from the 20-Questions Game ↗Leonardo Bertolazzi, Davide Mazzaccara, Filippo Merlo et al.2 citations
18. Enhancing factualness and controllability of Data-to-Text Generation via data Views and constraints ↗Craig Thomson, Clement Rebuffel, Ehud Reiter et al.2 citations
19. Fine-Tuning GPT-3 for Synthetic Danish News Generation ↗Mina Almasi, Anton Schiønning2 citations
20. Guided Beam Search to Improve Generalization in Low-Resource Data-to-Text Generation ↗Nicolas Garneau, Luc Lamontagne2 citations
21. System-Initiated Transitions from Chit-Chat to Task-Oriented Dialogues with Transition Info Extractor and Transition Sentence Generator ↗Ye Liu, Stefan Ultes, Wolfgang Minker et al.2 citations
22. Beyond the Bias: Unveiling the Quality of Implicit Causality Prompt Continuations in Language Models ↗Judith Sieker, Oliver Bott, Torgrim Solstad et al.1 citation
23. Exploring the Naturalness of Cognitive Status-Informed Referring Form Selection Models ↗Gabriel Del Castillo, Grace Clark, Zhao Han et al.1 citation
24. Generating clickbait spoilers with an ensemble of large language models ↗Mateusz Woźny, Mateusz Lango1 citation
25. HL Dataset: Visually-grounded Description of Scenes, Actions and Rationales ↗Michele Cafagna, Kees van Deemter, Albert Gatt1 citation

See all 59 papers in INLG 2023 — accepted papers →

📄 Papers with our summary in our library (2)

The most cited first (OpenAlex citations plus our library's).

1. Preventing Generation of Verbatim Memorization in Language Models Gives a False Sense of PrivacyInternational Natural Language Generation Conference (INLG)Daphne Ippolito, Florian Tramer, Milad Nasr, et al.2023 · 68 citations
2. Sentence-level Feedback Generation for English Language Learners: Does Data Augmentation Help?International Natural Language Generation Conference (INLG)Shabnam Behzad, Amir Zeldes, Nathan Schneider2023 · 3 citations

🧭 Top topics

Topics of its works in our library, with the number of works on each.

🧠Language models & pretraining (1)🖍️Grammatical error correction & learner language (1)English (1)

📚 Fields

🎭Arts and Humanities (2)🖥️Computer Science (2)

🧑‍🔬 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🏛️ Top institutions

Institutions on the bylines of its works here, by the number of works.

🏢GoogleMountain View · United States1 work here🎓Georgetown UniversityWashington · United States1 work here🎓Cornell UniversityIthaca · United States1 work here🎓ETH ZurichZurich · Switzerland1 work here

Place and dates from the event's site or the ACL Anthology; works and citations from OpenAlex and our library.

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