---
title: "TACL 2023 — all accepted papers with summaries and citations"
description: "All 98 papers of TACL 2023, the most cited first; those with our summary link to it. Among them: A Cross-Linguistic Pressure for Uniform…"
canonical: "https://research.elamur.ai/free/en/venues/tacl/2023/papers/"
---
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# TACL 2023: all accepted papers

98 papers · the most cited first · [← TACL 2023](https://md.research.elamur.ai/free/en/venues/tacl/2023/)

1. **[A Cross-Linguistic Pressure for Uniform Information Density in Word Order ↗](https://aclanthology.org/2023.tacl-1.59/)**Thomas Hikaru Clark, Clara Meister, Tiago Pimentel et al.
2. **[Abstractive Meeting Summarization: A Survey ↗](https://aclanthology.org/2023.tacl-1.49/)**Virgile Rennard, Guokan Shang, Julie Hunter et al.
3. **[AfriSpeech-200: Pan-African Accented Speech Dataset for Clinical and General Domain ASR ↗](https://aclanthology.org/2023.tacl-1.93/)**Tobi Olatunji, Tejumade Afonja, Aditya Yadavalli et al.
4. **[Aggretriever: A Simple Approach to Aggregate Textual Representations for Robust Dense Passage Retrieval ↗](https://aclanthology.org/2023.tacl-1.26/)**Sheng-Chieh Lin, Minghan Li, Jimmy Lin
5. **[An Efficient Self-Supervised Cross-View Training For Sentence Embedding ↗](https://aclanthology.org/2023.tacl-1.89/)**Peerat Limkonchotiwat, Wuttikorn Ponwitayarat, Lalita Lowphansirikul et al.
6. **[An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://md.research.elamur.ai/free/en/papers/chen-2023-empirical-survey-data-augmentation-limited/)**Jiaao Chen, Derek Tam, Colin Raffel et al.*our summary*
7. **[Assessing the Capacity of Transformer to Abstract Syntactic Representations: A Contrastive Analysis Based on Long-distance Agreement ↗](https://aclanthology.org/2023.tacl-1.2/)**Bingzhi Li, Guillaume Wisniewski, Benoît Crabbé
8. **[Benchmarking the Generation of Fact Checking Explanations ↗](https://aclanthology.org/2023.tacl-1.71/)**Daniel Russo, Serra Sinem Tekiroğlu, Marco Guerini
9. **[Bridging the Gap between Synthetic and Natural Questions via Sentence Decomposition for Semantic Parsing ↗](https://aclanthology.org/2023.tacl-1.22/)**Yilin Niu, Fei Huang, Wei Liu et al.
10. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/)**Patrick Fernandes, Aman Madaan, Emmy Liu et al.*our summary*
11. **[Calibrated Interpretation: Confidence Estimation in Semantic Parsing ↗](https://aclanthology.org/2023.tacl-1.69/)**Elias Stengel-Eskin, Benjamin Van Durme
12. **[Can Authorship Representation Learning Capture Stylistic Features? ↗](https://aclanthology.org/2023.tacl-1.80/)**Andrew Wang, Cristina Aggazzotti, Rebecca Kotula et al.
13. **[Chinese Idiom Paraphrasing](https://md.research.elamur.ai/free/en/papers/qiang-2023-chinese-idiom-paraphrasing/)**Jipeng Qiang, Yang Li, Chaowei Zhang et al.*our summary*
14. **[Collective Human Opinions in Semantic Textual Similarity ↗](https://aclanthology.org/2023.tacl-1.56/)**Yuxia Wang, Shimin Tao, Ning Xie et al.
15. **[Communication Drives the Emergence of Language Universals in Neural Agents: Evidence from the Word-order/Case-marking Trade-off ↗](https://aclanthology.org/2023.tacl-1.58/)**Yuchen Lian, Arianna Bisazza, Tessa Verhoef
16. **[Compositional Zero-Shot Domain Transfer with Text-to-Text Models ↗](https://aclanthology.org/2023.tacl-1.62/)**Fangyu Liu, Qianchu Liu, Shruthi Bannur et al.
17. **[Conditional Generation with a Question-Answering Blueprint ↗](https://aclanthology.org/2023.tacl-1.55/)**Shashi Narayan, Joshua Maynez, Reinald Kim Amplayo et al.
18. **[Coreference Resolution through a seq2seq Transition-Based System](https://md.research.elamur.ai/free/en/papers/bohnet-2023-coreference-resolution-through-seq2seq-transition/)**Bernd Bohnet, Chris Alberti, Michael Collins*our summary*
19. **[Cross-Lingual Dialogue Dataset Creation via Outline-Based Generation ↗](https://aclanthology.org/2023.tacl-1.9/)**Olga Majewska, Evgeniia Razumovskaia, Edoardo M. Ponti et al.
20. **[Cross-functional Analysis of Generalization in Behavioral Learning ↗](https://aclanthology.org/2023.tacl-1.60/)**Pedro Henrique Luz de Araujo, Benjamin Roth
21. **[DMDD: A Large-Scale Dataset for Dataset Mentions Detection ↗](https://aclanthology.org/2023.tacl-1.64/)**Huitong Pan, Qi Zhang, Eduard Dragut et al.
22. **[Data-driven Parsing Evaluation for Child-Parent Interactions](https://md.research.elamur.ai/free/en/papers/liu-2023-data-driven-parsing-evaluation-child/)**Zoey Liu, Emily Prud'hommeaux*our summary*
23. **[Design Choices for Crowdsourcing Implicit Discourse Relations: Revealing the Biases Introduced by Task Design](https://md.research.elamur.ai/free/en/papers/pyatkin-2023-design-choices-crowdsourcing-implicit-discourse/)**Valentina Pyatkin, Frances Yung, Merel C. J. Scholman et al.*our summary*
24. **[Direct Speech Translation for Automatic Subtitling ↗](https://aclanthology.org/2023.tacl-1.77/)**Sara Papi, Marco Gaido, Alina Karakanta et al.
25. **[Directed Acyclic Transformer Pre-training for High-quality Non-autoregressive Text Generation ↗](https://aclanthology.org/2023.tacl-1.53/)**Fei Huang, Pei Ke, Minlie Huang
26. **[Discontinuous Combinatory Constituency Parsing ↗](https://aclanthology.org/2023.tacl-1.16/)**Zhousi Chen, Mamoru Komachi
27. **[Discover, Explain, Improve: An Automatic Slice Detection Benchmark for Natural Language Processing ↗](https://aclanthology.org/2023.tacl-1.87/)**Wenyue Hua, Lifeng Jin, Linfeng Song et al.
28. **[Domain-Specific Word Embeddings with Structure Prediction ↗](https://aclanthology.org/2023.tacl-1.19/)**David Lassner, Stephanie Brandl, Anne Baillot et al.
29. **[Dubbing in Practice: A Large Scale Study of Human Localization With Insights for Automatic Dubbing ↗](https://aclanthology.org/2023.tacl-1.25/)**William Brannon, Yogesh Virkar, Brian Thompson
30. **[Efficient Long-Text Understanding with Short-Text Models](https://md.research.elamur.ai/free/en/papers/ivgi-2023-efficient-long-text-understanding-short/)**Maor Ivgi, Uri Shaham, Jonathan Berant*our summary*
31. **[Efficient Methods for Natural Language Processing: A Survey](https://md.research.elamur.ai/free/en/papers/treviso-2023-efficient-methods-natural-language-processing/)**Marcos Treviso, Ji-Ung Lee, Tianchu Ji et al.*our summary*
32. **[Erasure of Unaligned Attributes from Neural Representations ↗](https://aclanthology.org/2023.tacl-1.29/)**Shun Shao, Yftah Ziser, Shay B. Cohen
33. **[Evaluating Transformer Models and Human Behaviors on Chinese Character Naming ↗](https://aclanthology.org/2023.tacl-1.44/)**Xiaomeng Ma, Lingyu Gao
34. **[Evaluating a Century of Progress on the Cognitive Science of Adjective Ordering ↗](https://aclanthology.org/2023.tacl-1.67/)**William Dyer, Charles Torres, Gregory Scontras et al.
35. **[Expectations over Unspoken Alternatives Predict Pragmatic Inferences](https://md.research.elamur.ai/free/en/papers/hu-2023-expectations-over-unspoken-alternatives-predict/)**Jennifer Hu, Roger Levy, Judith Degen et al.*our summary*
36. **[Exploring Contrast Consistency of Open-Domain Question Answering Systems on Minimally Edited Questions ↗](https://aclanthology.org/2023.tacl-1.61/)**Zhihan Zhang, Wenhao Yu, Zheng Ning et al.
37. **[FRMT: A Benchmark for Few-Shot Region-Aware Machine Translation](https://md.research.elamur.ai/free/en/papers/riley-2023-frmt-benchmark-few-shot-region/)**Parker Riley, Timothy Dozat, Jan A. Botha et al.*our summary*
38. **[FeelingBlue: A Corpus for Understanding the Emotional Connotation of Color in Context ↗](https://aclanthology.org/2023.tacl-1.11/)**Amith Ananthram, Olivia Winn, Smaranda Muresan
39. **[General then Personal: Decoupling and Pre-training for Personalized Headline Generation ↗](https://aclanthology.org/2023.tacl-1.90/)**Yun-Zhu Song, Yi-Syuan Chen, Lu Wang et al.
40. **[Generative Spoken Dialogue Language Modeling](https://md.research.elamur.ai/free/en/papers/nguyen-2023-generative-spoken-dialogue-language-modeling/)**Tu Anh Nguyen, Eugene Kharitonov, Jade Copet et al.*our summary*
41. **[Hallucinations in Large Multilingual Translation Models](https://md.research.elamur.ai/free/en/papers/guerreiro-2023-hallucinations-large-multilingual-translation-models/)**Nuno M. Guerreiro, Duarte M. Alves, Jonas Waldendorf et al.*our summary*
42. **[Hate Speech Classifiers Learn Normative Social Stereotypes ↗](https://aclanthology.org/2023.tacl-1.18/)**Aida Mostafazadeh Davani, Mohammad Atari, Brendan Kennedy et al.
43. **[Helpful Neighbors: Leveraging Neighbors in Geographic Feature Pronunciation ↗](https://aclanthology.org/2023.tacl-1.6/)**Llion Jones, Richard Sproat, Haruko Ishikawa et al.
44. **[How Abstract Is Linguistic Generalization in Large Language Models? Experiments with Argument Structure ↗](https://aclanthology.org/2023.tacl-1.78/)**Michael Wilson, Jackson Petty, Robert Frank
45. **[How Much Do Language Models Copy From Their Training Data? Evaluating Linguistic Novelty in Text Generation Using RAVEN](https://md.research.elamur.ai/free/en/papers/mccoy-2023-how-much-do-language-models/)**R. Thomas McCoy, Paul Smolensky, Tal Linzen et al.*our summary*
46. **[Improving Low-Resource Cross-lingual Parsing with Expected Statistic Regularization ↗](https://aclanthology.org/2023.tacl-1.8/)**Thomas Effland, Michael Collins
47. **[Improving Multitask Retrieval by Promoting Task Specialization ↗](https://aclanthology.org/2023.tacl-1.68/)**Wenzheng Zhang, Chenyan Xiong, Karl Stratos et al.
48. **[Improving the Domain Adaptation of Retrieval Augmented Generation (RAG) Models for Open Domain Question Answering](https://md.research.elamur.ai/free/en/papers/siriwardhana-2023-improving-domain-adaptation-retrieval-augmented/)**Shamane Siriwardhana, Rivindu Weerasekera, Elliott Wen et al.*our summary*
49. **[In-Context Retrieval-Augmented Language Models ↗](https://aclanthology.org/2023.tacl-1.75/)**Ori Ram, Yoav Levine, Itay Dalmedigos et al.
50. **[InSCIt: Information-Seeking Conversations with Mixed-Initiative Interactions ↗](https://aclanthology.org/2023.tacl-1.27/)**Zeqiu Wu, Ryu Parish, Hao Cheng et al.
51. **[Intent-calibrated Self-training for Answer Selection in Open-domain Dialogues ↗](https://aclanthology.org/2023.tacl-1.70/)**Wentao Deng, Jiahuan Pei, Zhaochun Ren et al.
52. **[Introduction to Mathematical Language Processing: Informal Proofs, Word Problems, and Supporting Tasks ↗](https://aclanthology.org/2023.tacl-1.66/)**Jordan Meadows, André Freitas
53. **[Learning More from Mixed Emotions: A Label Refinement Method for Emotion Recognition in Conversations ↗](https://aclanthology.org/2023.tacl-1.84/)**Jintao Wen, Geng Tu, Rui Li et al.
54. **[Learning to Paraphrase Sentences to Different Complexity Levels ↗](https://aclanthology.org/2023.tacl-1.76/)**Alison Chi, Li-Kuang Chen, Yi-Chen Chang et al.
55. **[Less is More: Mitigate Spurious Correlations for Open-Domain Dialogue Response Generation Models by Causal Discovery ↗](https://aclanthology.org/2023.tacl-1.30/)**Tao Feng, Lizhen Qu, Gholamreza Haffari
56. **[Locally Typical Sampling](https://md.research.elamur.ai/free/en/papers/meister-2023-locally-typical-sampling/)**Clara Meister, Tiago Pimentel, Gian Wiher et al.*our summary*
57. **[MACSum: Controllable Summarization with Mixed Attributes ↗](https://aclanthology.org/2023.tacl-1.46/)**Yusen Zhang, Yang Liu, Ziyi Yang et al.
58. **[MENLI: Robust Evaluation Metrics from Natural Language Inference ↗](https://aclanthology.org/2023.tacl-1.47/)**Yanran Chen, Steffen Eger
59. **[MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages](https://md.research.elamur.ai/free/en/papers/zhang-2023-miracl-multilingual-retrieval-dataset-covering/)**Xinyu Zhang, Nandan Thakur, Odunayo Ogundepo et al.*our summary*
60. **[Meta-Learning a Cross-lingual Manifold for Semantic Parsing ↗](https://aclanthology.org/2023.tacl-1.4/)**Tom Sherborne, Mirella Lapata
61. **[MissModal: Increasing Robustness to Missing Modality in Multimodal Sentiment Analysis ↗](https://aclanthology.org/2023.tacl-1.94/)**Ronghao Lin, Haifeng Hu
62. **[Modeling Emotion Dynamics in Song Lyrics with State Space Models ↗](https://aclanthology.org/2023.tacl-1.10/)**Yingjin Song, Daniel Beck
63. **[Multi 3 WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems ↗](https://aclanthology.org/2023.tacl-1.79/)**Songbo Hu, Han Zhou, Mete Hergul et al.
64. **[Multilingual Coreference Resolution in Multiparty Dialogue](https://md.research.elamur.ai/free/en/papers/zheng-2023-multilingual-coreference-resolution-multiparty-dialogue/)**Boyuan Zheng, Patrick Xia, Mahsa Yarmohammadi et al.*our summary*
65. **[Naturalistic Causal Probing for Morpho-Syntax ↗](https://aclanthology.org/2023.tacl-1.23/)**Afra Amini, Tiago Pimentel, Clara Meister et al.
66. **[OPAL: Ontology-Aware Pretrained Language Model for End-to-End Task-Oriented Dialogue ↗](https://aclanthology.org/2023.tacl-1.5/)**Zhi Chen, Yuncong Liu, Lu Chen et al.
67. **[On Graph-based Reentrancy-free Semantic Parsing ↗](https://aclanthology.org/2023.tacl-1.41/)**Alban Petit, Caio Corro
68. **[On the Robustness of Dialogue History Representation in Conversational Question Answering: A Comprehensive Study and a New Prompt-based Method ↗](https://aclanthology.org/2023.tacl-1.21/)**Zorik Gekhman, Nadav Oved, Orgad Keller et al.
69. **[On the Role of Negative Precedent in Legal Outcome Prediction ↗](https://aclanthology.org/2023.tacl-1.3/)**Josef Valvoda, Ryan Cotterell, Simone Teufel
70. **[OpenFact: Factuality Enhanced Open Knowledge Extraction ↗](https://aclanthology.org/2023.tacl-1.40/)**Linfeng Song, Ante Wang, Xiaoman Pan et al.
71. **[Optimal Transport Posterior Alignment for Cross-lingual Semantic Parsing ↗](https://aclanthology.org/2023.tacl-1.81/)**Tom Sherborne, Tom Hosking, Mirella Lapata
72. **[PASTA: A Dataset for Modeling PArticipant STAtes in Narratives ↗](https://aclanthology.org/2023.tacl-1.73/)**Sayontan Ghosh, Mahnaz Koupaee, Isabella Chen et al.
73. **[PaniniQA: Enhancing Patient Education Through Interactive Question Answering ↗](https://aclanthology.org/2023.tacl-1.86/)**Pengshan Cai, Zonghai Yao, Fei Liu et al.
74. **[Pre-train, Prompt, and Recommendation: A Comprehensive Survey of Language Modeling Paradigm Adaptations in Recommender Systems ↗](https://aclanthology.org/2023.tacl-1.88/)**Peng Liu, Lemei Zhang, Jon Atle Gulla
75. **[QAmeleon: Multilingual QA with Only 5 Examples ↗](https://aclanthology.org/2023.tacl-1.98/)**Priyanka Agrawal, Chris Alberti, Fantine Huot et al.
76. **[Questions Are All You Need to Train a Dense Passage Retriever ↗](https://aclanthology.org/2023.tacl-1.35/)**Devendra Singh Sachan, Mike Lewis, Dani Yogatama et al.
77. **[Rank-Aware Negative Training for Semi-Supervised Text Classification ↗](https://aclanthology.org/2023.tacl-1.45/)**Ahmed Murtadha, Shengfeng Pan, Wen Bo et al.
78. **[ReCOGS: How Incidental Details of a Logical Form Overshadow an Evaluation of Semantic Interpretation ↗](https://aclanthology.org/2023.tacl-1.96/)**Zhengxuan Wu, Christopher D. Manning, Christopher Potts
79. **[Reasoning over Public and Private Data in Retrieval-Based Systems ↗](https://aclanthology.org/2023.tacl-1.51/)**Simran Arora, Patrick Lewis, Angela Fan et al.
80. **[Removing Backdoors in Pre-trained Models by Regularized Continual Pre-training ↗](https://aclanthology.org/2023.tacl-1.91/)**Biru Zhu, Ganqu Cui, Yangyi Chen et al.
81. **[Shared Lexical Items as Triggers of Code Switching ↗](https://aclanthology.org/2023.tacl-1.83/)**Shuly Wintner, Safaa Shehadi, Yuli Zeira et al.
82. **[Speak, Read and Prompt: High-Fidelity Text-to-Speech with Minimal Supervision](https://md.research.elamur.ai/free/en/papers/kharitonov-2023-speak-read-prompt-high-fidelity/)**Eugene Kharitonov, Damien Vincent, Zalán Borsos et al.*our summary*
83. **[Sub-Character Tokenization for Chinese Pretrained Language Models ↗](https://aclanthology.org/2023.tacl-1.28/)**Chenglei Si, Zhengyan Zhang, Yingfa Chen et al.
84. **[Supervised Gradual Machine Learning for Aspect-Term Sentiment Analysis ↗](https://aclanthology.org/2023.tacl-1.42/)**Yanyan Wang, Qun Chen, Murtadha H.M. Ahmed et al.
85. **[T 2 -NER: A Two-Stage Span-Based Framework for Unified Named Entity Recognition with Templates ↗](https://aclanthology.org/2023.tacl-1.72/)**Peixin Huang, Xiang Zhao, Minghao Hu et al.
86. **[T3L: Translate-and-Test Transfer Learning for Cross-Lingual Text Classification ↗](https://aclanthology.org/2023.tacl-1.65/)**Inigo Jauregi Unanue, Gholamreza Haffari, Massimo Piccardi
87. **[Testing the Predictions of Surprisal Theory in 11 Languages](https://md.research.elamur.ai/free/en/papers/wilcox-2023-testing-predictions-surprisal-theory-11/)**Ethan G. Wilcox, Tiago Pimentel, Clara Meister et al.*our summary*
88. **[The Parallelism Tradeoff: Limitations of Log-Precision Transformers ↗](https://aclanthology.org/2023.tacl-1.31/)**William Merrill, Ashish Sabharwal
89. **[Time-and-Space-Efficient Weighted Deduction ↗](https://aclanthology.org/2023.tacl-1.54/)**Jason Eisner
90. **[Tracking Brand-Associated Polarity-Bearing Topics in User Reviews ↗](https://aclanthology.org/2023.tacl-1.24/)**Runcong Zhao, Lin Gui, Hanqi Yan et al.
91. **[Transformers for Tabular Data Representation: A Survey of Models and Applications ↗](https://aclanthology.org/2023.tacl-1.14/)**Gilbert Badaro, Mohammed Saeed, Paolo Papotti
92. **[Transparency Helps Reveal When Language Models Learn Meaning ↗](https://aclanthology.org/2023.tacl-1.36/)**Zhaofeng Wu, William Merrill, Hao Peng et al.
93. **[U-CORE: A Unified Deep Cluster-wise Contrastive Framework for Open Relation Extraction ↗](https://aclanthology.org/2023.tacl-1.74/)**Jie Zhou, Shenpo Dong, Yunxin Huang et al.
94. **[Understanding and Detecting Hallucinations in Neural Machine Translation via Model Introspection ↗](https://aclanthology.org/2023.tacl-1.32/)**Weijia Xu, Sweta Agrawal, Eleftheria Briakou et al.
95. **[Unleashing the True Potential of Sequence-to-Sequence Models for Sequence Tagging and Structure Parsing ↗](https://aclanthology.org/2023.tacl-1.34/)**Han He, Jinho D. Choi
96. **[Visual Spatial Reasoning ↗](https://aclanthology.org/2023.tacl-1.37/)**Fangyu Liu, Guy Emerson, Nigel Collier
97. **[Visual Writing Prompts: Character-Grounded Story Generation with Curated Image Sequences ↗](https://aclanthology.org/2023.tacl-1.33/)**Xudong Hong, Asad Sayeed, Khushboo Mehra et al.
98. **[Why Does Surprisal From Larger Transformer-Based Language Models Provide a Poorer Fit to Human Reading Times?](https://md.research.elamur.ai/free/en/papers/oh-2023-why-does-surprisal-larger-transformer/)**Byung-Doh Oh, William Schuler*our summary*
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