📰 BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP 2023 — accepted papers

BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP 2023 is the 2023 edition of the BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, held in Singapore, December 2023 (publisher: Association for Computational Linguistics). The ACL Anthology lists 29 papers of it; our library holds 2 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

📍 Singapore · 🗓 December 2023

Most cited papers

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

1. Emergent Linear Representations in World Models of Self-Supervised Sequence Models ↗Neel Nanda, Andrew Lee, Martin Wattenberg35 citations
2. Explaining Data Patterns in Natural Language with Language Models ↗Chandan Singh, John X. Morris, Jyoti Aneja et al.14 citations
3. Layered Bias: Interpreting Bias in Pretrained Large Language Models ↗Nirmalendu Prakash, Roy Ka-Wei Lee11 citations
4. Self-Consistency of Large Language Models under Ambiguity ↗Henning Bartsch, Ole Jorgensen, Domenic Rosati et al.10 citations
5. Knowledge-Grounded Natural Language Recommendation Explanation ↗Anthony Colas, Jun Araki, Zhengyu Zhou et al.5 citations
6. Evaluating Transformer's Ability to Learn Mildly Context-Sensitive Languages ↗Shunjie Wang, Shane Steinert-Threlkeld4 citations
7. Investigating the Effect of Discourse Connectives on Transformer Surprisal: Language Models Understand Connectives, Even So They Are Surprised ↗Yan Cong, Emmanuele Chersoni, Yu-Yin Hsu et al.4 citations
8. Memory Injections: Correcting Multi-Hop Reasoning Failures During Inference in Transformer-Based Language Models ↗Mansi Sakarvadia, Aswathy Ajith, Arham Khan et al.4 citations
9. Rigorously Assessing Natural Language Explanations of Neurons ↗Jing Huang, Atticus Geiger, Karel D'Oosterlinck et al.3 citations
10. When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! PrincipleJudith Sieker, Sina Zarrieß3 citations · our summary

All accepted papers (29)

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

1. Emergent Linear Representations in World Models of Self-Supervised Sequence Models ↗Neel Nanda, Andrew Lee, Martin Wattenberg35 citations
2. Explaining Data Patterns in Natural Language with Language Models ↗Chandan Singh, John X. Morris, Jyoti Aneja et al.14 citations
3. Layered Bias: Interpreting Bias in Pretrained Large Language Models ↗Nirmalendu Prakash, Roy Ka-Wei Lee11 citations
4. Self-Consistency of Large Language Models under Ambiguity ↗Henning Bartsch, Ole Jorgensen, Domenic Rosati et al.10 citations
5. Knowledge-Grounded Natural Language Recommendation Explanation ↗Anthony Colas, Jun Araki, Zhengyu Zhou et al.5 citations
6. Evaluating Transformer's Ability to Learn Mildly Context-Sensitive Languages ↗Shunjie Wang, Shane Steinert-Threlkeld4 citations
7. Investigating the Effect of Discourse Connectives on Transformer Surprisal: Language Models Understand Connectives, Even So They Are Surprised ↗Yan Cong, Emmanuele Chersoni, Yu-Yin Hsu et al.4 citations
8. Memory Injections: Correcting Multi-Hop Reasoning Failures During Inference in Transformer-Based Language Models ↗Mansi Sakarvadia, Aswathy Ajith, Arham Khan et al.4 citations
9. Rigorously Assessing Natural Language Explanations of Neurons ↗Jing Huang, Atticus Geiger, Karel D'Oosterlinck et al.3 citations
10. When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! PrincipleJudith Sieker, Sina Zarrieß3 citations · our summary
11. Causal Abstraction for Chain-of-Thought Reasoning in Arithmetic Word Problems ↗Juanhe (TJ) Tan2 citations
12. Enhancing Interpretability Using Human Similarity Judgements to Prune Word Embeddings ↗Natalia Flechas Manrique, Wanqian Bao, Aurelie Herbelot et al.2 citations
13. Probing Quantifier Comprehension in Large Language Models: Another Example of Inverse Scaling ↗Akshat Gupta2 citations
14. Identifying and Adapting Transformer-Components Responsible for Gender Bias in an English Language Model ↗Abhijith Chintam, Rahel Beloch, Willem Zuidema et al.1 citation
15. Investigating the Encoding of Words in BERT's Neurons Using Feature Textualization ↗Tanja Baeumel, Soniya Vijayakumar, Josef van Genabith et al.1 citation
16. On Quick Kisses and How to Make Them Count: A Study on Event Construal in Light Verb Constructions with BERTChenxin Liu, Emmanuele Chersoni1 citation · our summary
17. Why Bother with Geometry? On the Relevance of Linear Decompositions of Transformer Embeddings ↗Timothee Mickus, Raúl Vázquez1 citation
18. “Honey, Tell Me What's Wrong”, Global Explanation of Textual Discriminative Models through Cooperative Generation ↗Antoine Chaffin, Julien Delaunay1 citation
19. Character-Level Chinese Backpack Language Models ↗Hao Sun, John Hewitt
20. Disentangling the Linguistic Competence of Privacy-Preserving BERT ↗Stefan Arnold, Nils Kemmerzell, Annika Schreiner
21. How Much Consistency Is Your Accuracy Worth? ↗Jacob K. Johnson, Ana Marasović
22. Introducing VULCAN: A Visualization Tool for Understanding Our Models and Data by Example ↗Jonas Groschwitz
23. Investigating Semantic Subspaces of Transformer Sentence Embeddings through Linear Structural Probing ↗Dmitry Nikolaev, Sebastian Padó
24. METAPROBE: A Representation- and Task-Agnostic Probe ↗Yichu Zhou, Vivek Srikumar
25. NPIs Aren't Exactly Easy: Variation in Licensing across Large Language Models ↗Deanna DeCarlo, William Palmer, Michael Wilson et al.

See all 29 papers in BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP 2023 — accepted papers →

📄 Papers with our summary in our library (2)

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

1. When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! PrincipleJudith Sieker, Sina Zarrieß2023 · 9 citations
2. On Quick Kisses and How to Make Them Count: A Study on Event Construal in Light Verb Constructions with BERTBlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLPChenxin Liu, Emmanuele Chersoni2023 · 2 citations

🧭 Top topics

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

😉Implicature (1)🧠Language models & pretraining (1)🔬Interpretability (1)🧷Idioms & multiword expressions (1)English (1)

📚 Fields

🎭Arts and Humanities (2)🖥️Computer Science (1)🧠Neuroscience (1)💭Psychology (1)

🧑‍🔬 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.

🎓Hong Kong Polytechnic UniversityHong Kong · China1 work here🎓Bielefeld UniversityBielefeld · Germany1 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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