id stringlengths 8 23 | title stringlengths 24 120 | abstract stringlengths 323 2.05k ⌀ | year int64 2.02k 2.02k | url stringlengths 34 49 | venues stringclasses 9
values | reading_list stringlengths 4.41k 62.7k |
|---|---|---|---|---|---|---|
C16-3001 | Compositional Distributional Models of Meaning | Compositional distributional models of meaning (CDMs) provide a function that produces a vectorial representation for a phrase or a sentence by composing the vectors of its words. Being the natural evolution of the traditional and well-studied distributional models at the word level, CDMs are steadily evolving to a pop... | 2,016 | https://aclanthology.org/C16-3001/ | COLING | [{'id': 8360910, 'paperId': '37efe2ef1b9d27cc598361a8013ec888a6f7c4d8', 'title': 'Nouns are Vectors, Adjectives are Matrices: Representing Adjective-Noun Constructions in Semantic Space', 'authors': [{'authorId': '145283199', 'name': 'Marco Baroni'}, {'authorId': '2713535', 'name': 'Roberto Zamparelli'}], 'venue': 'Con... |
P19-4004 | Computational Analysis of Political Texts: Bridging Research Efforts Across Communities | In the last twenty years, political scientists started adopting and developing natural language processing (NLP) methods more actively in order to exploit text as an additional source of data in their analyses. Over the last decade the usage of computational methods for analysis of political texts has drastically expan... | 2,019 | https://aclanthology.org/P19-4004/ | ACL | [{'id': 16196219, 'paperId': 'b9921fb4d1448058642897797e77bdaf8f444404', 'title': 'Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts', 'authors': [{'authorId': '2361828', 'name': 'Justin Grimmer'}, {'authorId': '28924497', 'name': 'Brandon M Stewart'}], 'venue': 'Political... |
2020.acl-tutorials.1 | Interpretability and Analysis in Neural NLP | While deep learning has transformed the natural language processing (NLP) field and impacted the larger computational linguistics community, the rise of neural networks is stained by their opaque nature: It is challenging to interpret the inner workings of neural network models, and explicate their behavior. Therefore,... | 2,020 | https://aclanthology.org/2020.acl-tutorials.1 | ACL | [{'id': 56657817, 'paperId': '668f42a4d4094f0a66d402a16087e14269b31a1f', 'title': 'Analysis Methods in Neural Language Processing: A Survey', 'authors': [{'authorId': '2083259', 'name': 'Yonatan Belinkov'}, {'authorId': '145898106', 'name': 'James R. Glass'}], 'venue': 'Transactions of the Association for Computational... |
2020.acl-tutorials.2 | Integrating Ethics into the NLP Curriculum | To raise awareness among future NLP practitioners and prevent inertia in the field, we need to place ethics in the curriculum for all NLP students—not as an elective, but as a core part of their education. Our goal in this tutorial is to empower NLP researchers and practitioners with tools and resources to teach others... | 2,020 | https://aclanthology.org/2020.acl-tutorials.2 | ACL | [{'id': 26039972, 'paperId': '0e661bd2cfe94ed58e4e2abc1409c75b98c2582c', 'title': 'Dual use and the ethical responsibility of scientists', 'authors': [{'authorId': '3920554', 'name': 'Hans-Jörg Ehni'}], 'venue': 'Archivum Immunologiae et Therapiae Experimentalis', 'abstract': 'The main normative problem in the context ... |
2020.acl-tutorials.3 | Achieving Common Ground in Multi-modal Dialogue | All communication aims at achieving common ground (grounding): interlocutors can work together effectively only with mutual beliefs about what the state of the world is, about what their goals are, and about how they plan to make their goals a reality. Computational dialogue research offers some classic results on grou... | 2,020 | https://aclanthology.org/2020.acl-tutorials.3 | ACL | [{'id': 153811205, 'paperId': '5a9cac54de14e58697d0315fe3c01f3dbe69c186', 'title': 'Grounding in communication', 'authors': [{'authorId': '29224904', 'name': 'H. H. Clark'}, {'authorId': '71463834', 'name': 'S. Brennan'}], 'venue': 'Perspectives on socially shared cognition', 'abstract': "GROUNDING It takes two people ... |
2020.acl-tutorials.4 | Reviewing Natural Language Processing Research | This tutorial will cover the theory and practice of reviewing research in natural language processing. Heavy reviewing burdens on natural language processing researchers have made it clear that our community needs to increase the size of our pool of potential reviewers. Simultaneously, notable “false negatives”—rejecti... | 2,020 | https://aclanthology.org/2020.acl-tutorials.4 | ACL | [{'id': 154339, 'paperId': '33ff45f364dac785b8bd4e3bf70fb169dc1d39b4', 'title': "Who's afraid of peer review?", 'authors': [{'authorId': '145179131', 'name': 'J. Bohannon'}], 'venue': 'Science', 'abstract': 'Dozens of open-access journals targeted in an elaborate Science sting accepted a spoof research article, raising... |
2020.acl-tutorials.6 | Multi-modal Information Extraction from Text, Semi-structured, and Tabular Data on the Web | The World Wide Web contains vast quantities of textual information in several forms: unstructured text, template-based semi-structured webpages (which present data in key-value pairs and lists), and tables. Methods for extracting information from these sources and converting it to a structured form have been a target o... | 2,020 | https://aclanthology.org/2020.acl-tutorials.6 | ACL | [{'id': 13091007, 'paperId': '7a12502ba5b9686e37b0ec9d86a2dc7f4b7022ac', 'title': 'Web-scale information extraction with vertex', 'authors': [{'authorId': '2627799', 'name': 'P. Gulhane'}, {'authorId': '2136102', 'name': 'Amit Madaan'}, {'authorId': '3259494', 'name': 'Rupesh R. Mehta'}, {'authorId': '2311735', 'name':... |
2020.acl-tutorials.7 | Commonsense Reasoning for Natural Language Processing | Commonsense knowledge, such as knowing that “bumping into people annoys them” or “rain makes the road slippery”, helps humans navigate everyday situations seamlessly. Yet, endowing machines with such human-like commonsense reasoning capabilities has remained an elusive goal of artificial intelligence research for decad... | 2,020 | https://aclanthology.org/2020.acl-tutorials.7 | ACL | [{'id': 91184338, 'paperId': 'b1832b749528755dfcbe462717f4f5afc07243b8', 'title': 'Commonsense Reasoning for Natural Language Understanding: A Survey of Benchmarks, Resources, and Approaches', 'authors': [{'authorId': '89093987', 'name': 'Shane Storks'}, {'authorId': '3193409', 'name': 'Qiaozi Gao'}, {'authorId': '1707... |
2020.coling-tutorials.1 | Cross-lingual Semantic Representation for NLP with UCCA | This is an introductory tutorial to UCCA (Universal Conceptual Cognitive Annotation), a cross-linguistically applicable framework for semantic representation, with corpora annotated in English, German and French, and ongoing annotation in Russian and Hebrew. UCCA builds on extensive typological work and supports rapid ... | 2,020 | https://aclanthology.org/2020.coling-tutorials.1/ | COLING | [{'id': 60742189, 'paperId': '54ffc8f1cb11ec21eb14a6706b8b6d9b192a1b32', 'title': 'A Semantic Approach to English Grammar', 'authors': [{'authorId': '34256957', 'name': 'R. Dixon'}], 'venue': '', 'abstract': 'This book shows how grammar helps people communicate and looks at the ways grammar and meaning interrelate. The... |
2020.coling-tutorials.2 | Embeddings in Natural Language Processing | Embeddings have been one of the most important topics of interest in NLP for the past decade. Representing knowledge through a low-dimensional vector which is easily integrable in modern machine learning models has played a central role in the development of the field. Embedding techniques initially focused on words bu... | 2,020 | https://aclanthology.org/2020.coling-tutorials.2/ | COLING | [{'id': 15829786, 'paperId': 'e569d99f3a0fcfa038631dda2b44c73a6e8e97b8', 'title': 'Dimensions of meaning', 'authors': [{'authorId': '144418438', 'name': 'Hinrich Schütze'}], 'venue': "Supercomputing '92", 'abstract': 'The representation of documents and queries as vectors in a high-dimensional space is well-established... |
2020.coling-tutorials.5 | A guide to the dataset explosion in QA, NLI, and commonsense reasoning | Question answering, natural language inference and commonsense reasoning are increasingly popular as general NLP system benchmarks, driving both modeling and dataset work. Only for question answering we already have over 100 datasets, with over 40 published after 2018. However, most new datasets get “solved” soon after... | 2,020 | https://aclanthology.org/2020.coling-tutorials.5/ | COLING | [{'id': 182952898, 'paperId': 'a1f000b88e81f02b2a0d7a4097171428364af8c7', 'title': 'A Survey on Neural Machine Reading Comprehension', 'authors': [{'authorId': '2064466537', 'name': 'Boyu Qiu'}, {'authorId': '2118183867', 'name': 'Xu Chen'}, {'authorId': '2073589', 'name': 'Jungang Xu'}, {'authorId': '46676156', 'name'... |
2020.coling-tutorials.6 | A Crash Course in Automatic Grammatical Error Correction | Grammatical Error Correction (GEC) is the task of automatically detecting and correcting all types of errors in written text. Although most research has focused on correcting errors in the context of English as a Second Language (ESL), GEC can also be applied to other languages and native text. The main application of ... | 2,020 | https://aclanthology.org/2020.coling-tutorials.6/ | COLING | [{'id': 219306476, 'paperId': '20499f3c6fe9f84a12c9def941e2e12846a00c77', 'title': 'The CoNLL-2014 Shared Task on Grammatical Error Correction', 'authors': [{'authorId': '34789794', 'name': 'H. Ng'}, {'authorId': '2069266', 'name': 'S. Wu'}, {'authorId': '145693410', 'name': 'Ted Briscoe'}, {'authorId': '3271719', 'nam... |
2020.coling-tutorials.7 | Endangered Languages meet Modern NLP | This tutorial will focus on NLP for endangered languages documentation and revitalization. First, we will acquaint the attendees with the process and the challenges of language documentation, showing how the needs of the language communities and the documentary linguists map to specific NLP tasks. We will then present ... | 2,020 | https://aclanthology.org/2020.coling-tutorials.7/ | COLING | [{'id': 48356442, 'paperId': 'b4aa5354e88564b2e4eeee3019ed04e5388042f3', 'title': 'Challenges of language technologies for the indigenous languages of the Americas', 'authors': [{'authorId': '153151470', 'name': 'Manuel Mager'}, {'authorId': '1409305289', 'name': 'Ximena Gutierrez-Vasques'}, {'authorId': '32889164', 'n... |
2020.emnlp-tutorials.1 | Machine Reasoning: Technology, Dilemma and Future | Machine reasoning research aims to build interpretable AI systems that can solve problems or draw conclusions from what they are told (i.e. facts and observations) and already know (i.e. models, common sense and knowledge) under certain constraints. In this tutorial, we will (1) describe the motivation of this tutorial... | 2,020 | https://aclanthology.org/2020.emnlp-tutorials.1 | EMNLP | [{'id': 63671278, 'paperId': '20394c89e24d9060ecc69b8a58bdab7833c5b5bd', 'title': 'Markov Logic: A Unifying Framework for Statistical Relational Learning', 'authors': [{'authorId': '1746034', 'name': 'L. Getoor'}, {'authorId': '1685978', 'name': 'B. Taskar'}], 'venue': '', 'abstract': 'This chapter contains sections ti... |
2020.emnlp-tutorials.2 | Fact-Checking, Fake News, Propaganda, and Media Bias: Truth Seeking in the Post-Truth Era | The rise of social media has democratized content creation and has made it easy for everybody to share and spread information online. On the positive side, this has given rise to citizen journalism, thus enabling much faster dissemination of information compared to what was possible with newspapers, radio, and TV. On t... | 2,020 | https://aclanthology.org/2020.emnlp-tutorials.2 | EMNLP | [{'id': 207718082, 'paperId': 'cb40a5e6d4fc0290452345791bb91040aed76961', 'title': 'Fake News Detection on Social Media: A Data Mining Perspective', 'authors': [{'authorId': '145800151', 'name': 'Kai Shu'}, {'authorId': '2880010', 'name': 'A. Sliva'}, {'authorId': '2893721', 'name': 'Suhang Wang'}, {'authorId': '173663... |
2020.emnlp-tutorials.3 | Interpreting Predictions of NLP Models | Although neural NLP models are highly expressive and empirically successful, they also systematically fail in counterintuitive ways and are opaque in their decision-making process. This tutorial will provide a background on interpretation techniques, i.e., methods for explaining the predictions of NLP models. We will f... | 2,020 | https://aclanthology.org/2020.emnlp-tutorials.3 | EMNLP | [{'id': 11319376, 'paperId': '5c39e37022661f81f79e481240ed9b175dec6513', 'title': 'Towards A Rigorous Science of Interpretable Machine Learning', 'authors': [{'authorId': '1388372395', 'name': 'F. Doshi-Velez'}, {'authorId': '3351164', 'name': 'Been Kim'}], 'venue': '', 'abstract': 'As machine learning systems become u... |
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ACL-rlg: A Dataset for Reading List Generation
About
ACL-rlg is the largest dataset of expert-crafted reading lists, containing 85 reading lists manually extracted from tutorial papers submitted to ACL-related conferences between 2020 and 2024. Data was sourced from ACL Anthology and cross-referenced with Semantic Scholar, enabling the extraction of metadata for articles beyond the ACL collection.
Content
The following data fields are available :
| Field | Type | Description |
|---|---|---|
id |
string |
Unique identifier of the tutorial paper in the ACL Anthology. |
title |
string |
Title of the tutorial paper. |
abstract |
string |
Abstract of the tutorial paper. |
year |
int64 |
Year of publication. |
url |
string |
ACL Anthology link to the paper. |
venues |
string |
Name of the venues the tutorial paper is published in. |
reading_list |
list[object] |
Reading list provided by the authors of the paper. Each record includes: • corpusid (int64): Semantic Scholar corpus ID. • paperId (string): Semantic Scholar paper ID. • title (string): Title of the referenced paper. • abstract (string): Abstract of the referenced paper. • authors (list[object]): Informations about referenced paper's authors. • venue (string): Name of the venue the referenced paper is published in. • year (int64): Year of publication of the referenced paper. • in_acl (bool): Boolean indicating if the referenced is referenced in ACL Anthology. • citationCount (int64): Citation count of the paper extracted from Semantic Scholar API. • section (string): Name of the section of the reading list the referenced paper is listed in. • subsection (string): Name of the subsection of the reading list the referenced paper is listed in. |
Licence
Dataset: CC BY-NC 4.0
If you use this dataset you may use, share, and adapt the dataset for non-commercial research or educational purposes only.
Citation
@inproceedings{aubert-beduchaud-etal-2025-acl,
title = "{ACL}-rlg: A Dataset for Reading List Generation",
author = "Aubert-B{\'e}duchaud, Julien and
Boudin, Florian and
Daille, B{\'e}atrice and
Dufour, Richard",
editor = "Rambow, Owen and
Wanner, Leo and
Apidianaki, Marianna and
Al-Khalifa, Hend and
Eugenio, Barbara Di and
Schockaert, Steven",
booktitle = "Proceedings of the 31st International Conference on Computational Linguistics",
month = jan,
year = "2025",
address = "Abu Dhabi, UAE",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.coling-main.327/",
pages = "4910--4919",
abstract = "Familiarizing oneself with a new scientific field and its existing literature can be daunting due to the large amount of available articles. Curated lists of academic references, or reading lists, compiled by experts, offer a structured way to gain a comprehensive overview of a domain or a specific scientific challenge. In this work, we introduce ACL-rlg, the largest open expert-annotated reading list dataset. We also provide multiple baselines for evaluating reading list generation and formally define it as a retrieval task. Our qualitative study highlights that traditional scholarly search engines and indexing methods perform poorly on this task, and GPT-4o, despite showing better results, exhibits signs of potential data contamination."
}
Julien Aubert-Béduchaud, Florian Boudin, Béatrice Daille, and Richard Dufour. 2025. ACL-rlg: A Dataset for Reading List Generation. In Proceedings of the 31st International Conference on Computational Linguistics, pages 4910–4919, Abu Dhabi, UAE. Association for Computational Linguistics.
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