A taxonomy and review of generalization research in NLP
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Arabella J. Sinclair | Mikel Artetxe | Koustuv Sinha | D. Hupkes | Verna Dankers | Naomi Saphra | Tiago Pimentel | Khuyagbaatar Batsuren | Yanai Elazar | Christos Christodoulopoulos | Zhijing Jin | Dennis Ulmer | Maria Ryskina | Ryan Cotterell | Leila Khalatbari | Rita Frieske | Mario Giulianelli | Karim Lasri | Florian Schottmann | Kaiser Sun
[1] Yoav Goldberg,et al. Measuring Causal Effects of Data Statistics on Language Model's 'Factual' Predictions , 2022, ArXiv.
[2] Christophe Servan,et al. On the cross-lingual transferability of multilingual prototypical models across NLU tasks , 2022, METANLP.
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[15] Tianchuan Du,et al. Towards Generalizeable Semantic Product Search by Text Similarity Pre-training on Search Click Logs , 2022, ECNLP.
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[18] E. Mosca,et al. “That Is a Suspicious Reaction!”: Interpreting Logits Variation to Detect NLP Adversarial Attacks , 2022, ACL.
[19] Andrew M. Dai,et al. PaLM: Scaling Language Modeling with Pathways , 2022, J. Mach. Learn. Res..
[20] Lu Wang,et al. Efficient Argument Structure Extraction with Transfer Learning and Active Learning , 2022, FINDINGS.
[21] Lisa Anne Hendricks,et al. Training Compute-Optimal Large Language Models , 2022, ArXiv.
[22] Dilek Z. Hakkani-Tür,et al. What is wrong with you?: Leveraging User Sentiment for Automatic Dialog Evaluation , 2022, FINDINGS.
[23] Dipankar Das,et al. Can Unsupervised Knowledge Transfer from Social Discussions Help Argument Mining? , 2022, ACL.
[24] Alessandro Sordoni,et al. Better Language Model with Hypernym Class Prediction , 2022, ACL.
[25] Seong Jae Hwang,et al. The Change that Matters in Discourse Parsing: Estimating the Impact of Domain Shift on Parser Error , 2022, FINDINGS.
[26] Tal Linzen,et al. Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models , 2022, FINDINGS.
[27] Reut Tsarfaty,et al. Morphological Reinflection with Multiple Arguments: An Extended Annotation schema and a Georgian Case Study , 2022, ACL.
[28] M. Shoeybi,et al. Multi-Stage Prompting for Knowledgeable Dialogue Generation , 2022, FINDINGS.
[29] Orhan Firat,et al. Multilingual Mix: Example Interpolation Improves Multilingual Neural Machine Translation , 2022, ACL.
[30] P. Blunsom,et al. Revisiting the Compositional Generalization Abilities of Neural Sequence Models , 2022, ACL.
[31] Shafiq R. Joty,et al. Continual Few-shot Relation Learning via Embedding Space Regularization and Data Augmentation , 2022, ACL.
[32] Tao Shen,et al. ClarET: Pre-training a Correlation-Aware Context-To-Event Transformer for Event-Centric Generation and Classification , 2022, ACL.
[33] Peter A. Cholak,et al. Overcoming a Theoretical Limitation of Self-Attention , 2022, ACL.
[34] Yixin Cao,et al. Prompt for Extraction? PAIE: Prompting Argument Interaction for Event Argument Extraction , 2022, ACL.
[35] Matt Gardner,et al. Impact of Pretraining Term Frequencies on Few-Shot Reasoning , 2022, ArXiv.
[36] Alexander M. Rush,et al. PromptSource: An Integrated Development Environment and Repository for Natural Language Prompts , 2022, ACL.
[37] Reza Yazdani Aminabadi,et al. Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model , 2022, ArXiv.
[38] Zhilin Yang,et al. ZeroPrompt: Scaling Prompt-Based Pretraining to 1, 000 Tasks Improves Zero-Shot Generalization , 2022, EMNLP.
[39] Dragomir R. Radev,et al. UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models , 2022, EMNLP.
[40] Yuri Burda,et al. Grokking: Generalization Beyond Overfitting on Small Algorithmic Datasets , 2022, ArXiv.
[41] Zoey Liu,et al. Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation , 2022, TACL.
[42] Xi Victoria Lin,et al. Few-shot Learning with Multilingual Generative Language Models , 2021, EMNLP.
[43] Xi Victoria Lin,et al. Efficient Large Scale Language Modeling with Mixtures of Experts , 2021, EMNLP.
[44] Po-Sen Huang,et al. Scaling Language Models: Methods, Analysis & Insights from Training Gopher , 2021, ArXiv.
[45] Jane A. Yu,et al. Quantifying Adaptability in Pre-trained Language Models with 500 Tasks , 2021, NAACL.
[46] Sanket Vaibhav Mehta,et al. ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning , 2021, ArXiv.
[47] Edward Grefenstette,et al. A Survey of Zero-shot Generalisation in Deep Reinforcement Learning , 2021, J. Artif. Intell. Res..
[48] Dawn Song,et al. Grounded Graph Decoding Improves Compositional Generalization in Question Answering , 2021, EMNLP.
[49] Jacob Andreas,et al. How Do Neural Sequence Models Generalize? Local and Global Cues for Out-of-Distribution Prediction , 2021, EMNLP.
[50] Daniel Khashabi,et al. Hey AI, Can You Solve Complex Tasks by Talking to Agents? , 2021, FINDINGS.
[51] Sanket Vaibhav Mehta,et al. Improving Compositional Generalization with Self-Training for Data-to-Text Generation , 2021, ACL.
[52] H. Mobahi,et al. Sharpness-Aware Minimization Improves Language Model Generalization , 2021, ACL.
[53] Bin Ma,et al. A Unified Speaker Adaptation Approach for ASR , 2021, EMNLP.
[54] Phu Mon Htut,et al. BBQ: A hand-built bias benchmark for question answering , 2021, FINDINGS.
[55] Alexander M. Rush,et al. Multitask Prompted Training Enables Zero-Shot Task Generalization , 2021, ICLR.
[56] Greg Durrett,et al. ASPECTNEWS: Aspect-Oriented Summarization of News Documents , 2021, ACL.
[57] Alexander M. Fraser,et al. Why don’t people use character-level machine translation? , 2021, FINDINGS.
[58] Ashwin Srinivasan,et al. Zero-Shot Dense Retrieval with Momentum Adversarial Domain Invariant Representations , 2021, FINDINGS.
[59] Dzmitry Bahdanau,et al. LAGr: Label Aligned Graphs for Better Systematic Generalization in Semantic Parsing , 2021, ACL.
[60] Stanislas Dehaene,et al. Causal Transformers Perform Below Chance on Recursive Nested Constructions, Unlike Humans , 2021, ArXiv.
[61] Dzmitry Bahdanau,et al. Compositional Generalization in Dependency Parsing , 2021, ACL.
[62] Chenhao Tan,et al. Investigating the Effect of Natural Language Explanations on Out-of-Distribution Generalization in Few-shot NLI , 2021, INSIGHTS.
[63] Mirella Lapata,et al. Disentangled Sequence to Sequence Learning for Compositional Generalization , 2021, ACL.
[64] Zhengyuan Liu,et al. DMRST: A Joint Framework for Document-Level Multilingual RST Discourse Segmentation and Parsing , 2021, CODI.
[65] Zhengyuan Liu,et al. Improving Multi-Party Dialogue Discourse Parsing via Domain Integration , 2021, CODI.
[66] Mark O. Riedl,et al. Situated Dialogue Learning through Procedural Environment Generation , 2021, ACL.
[67] David Restrepo Amariles,et al. JuriBERT: A Masked-Language Model Adaptation for French Legal Text , 2021, NLLP.
[68] Aleksandr Drozd,et al. Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics , 2021, INSIGHTS.
[69] D. Katz,et al. LexGLUE: A Benchmark Dataset for Legal Language Understanding in English , 2021, ACL.
[70] Mohit Bansal,et al. Inducing Transformer’s Compositional Generalization Ability via Auxiliary Sequence Prediction Tasks , 2021, EMNLP.
[71] Dan Friedman,et al. Single-dataset Experts for Multi-dataset Question Answering , 2021, EMNLP.
[72] Kai-Wei Chang,et al. Relation-Guided Pre-Training for Open-Domain Question Answering , 2021, EMNLP.
[73] Kevin Gimpel,et al. On Generalization in Coreference Resolution , 2021, CRAC.
[74] Kazuma Hashimoto,et al. RNG-KBQA: Generation Augmented Iterative Ranking for Knowledge Base Question Answering , 2021, Annual Meeting of the Association for Computational Linguistics.
[75] Marco Luca Sbodio,et al. Neural Unification for Logic Reasoning over Natural Language , 2021, EMNLP.
[76] Sarkar Snigdha Sarathi Das,et al. CONTaiNER: Few-Shot Named Entity Recognition via Contrastive Learning , 2021, ACL.
[77] Ellie Pavlick,et al. Frequency Effects on Syntactic Rule Learning in Transformers , 2021, EMNLP.
[78] I. Augenstein,et al. How Does Counterfactually Augmented Data Impact Models for Social Computing Constructs? , 2021, EMNLP.
[79] Xianpei Han,et al. Honey or Poison? Solving the Trigger Curse in Few-shot Event Detection via Causal Intervention , 2021, EMNLP.
[80] Albert Y.S. Lam,et al. Effectiveness of Pre-training for Few-shot Intent Classification , 2021, EMNLP.
[81] Michael J.Q. Zhang,et al. SituatedQA: Incorporating Extra-Linguistic Contexts into QA , 2021, EMNLP.
[82] Songfang Huang,et al. Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning , 2021, EMNLP.
[83] Matthew Purver,et al. Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalization , 2021, EMNLP.
[84] Nikhil Ramesh,et al. Entity-Based Knowledge Conflicts in Question Answering , 2021, EMNLP.
[85] Mari Ostendorf,et al. DIALKI: Knowledge Identification in Conversational Systems through Dialogue-Document Contextualization , 2021, EMNLP.
[86] Zhou Yu,et al. Zero-Shot Dialogue State Tracking via Cross-Task Transfer , 2021, EMNLP.
[87] Qi Zhang,et al. Low-Resource Dialogue Summarization with Domain-Agnostic Multi-Source Pretraining , 2021, EMNLP.
[88] Eric Nyberg,et al. Exploring Strategies for Generalizable Commonsense Reasoning with Pre-trained Models , 2021, EMNLP.
[89] Miguel Ballesteros,et al. How much pretraining data do language models need to learn syntax? , 2021, EMNLP.
[90] Jonathan Herzig,et al. Finding needles in a haystack: Sampling Structurally-diverse Training Sets from Synthetic Data for Compositional Generalization , 2021, EMNLP.
[91] M Saiful Bari,et al. Nearest Neighbour Few-Shot Learning for Cross-lingual Classification , 2021, EMNLP.
[92] Quoc V. Le,et al. Finetuned Language Models Are Zero-Shot Learners , 2021, ICLR.
[93] S. Riedel,et al. Challenges in Generalization in Open Domain Question Answering , 2021, NAACL-HLT.
[94] Xu Sun,et al. Text AutoAugment: Learning Compositional Augmentation Policy for Text Classification , 2021, EMNLP.
[95] Einat Minkov,et al. Fight Fire with Fire: Fine-tuning Hate Detectors using Large Samples of Generated Hate Speech , 2021, EMNLP.
[96] Jin Yong Yoo,et al. Towards Improving Adversarial Training of NLP Models , 2021, EMNLP.
[97] Peng Cui,et al. Towards Out-Of-Distribution Generalization: A Survey , 2021, ArXiv.
[98] Xiaoxi Mao,et al. LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation , 2021, TACL.
[99] J. Schmidhuber,et al. The Devil is in the Detail: Simple Tricks Improve Systematic Generalization of Transformers , 2021, EMNLP.
[100] Elia Bruni,et al. The Paradox of the Compositionality of Natural Language: A Neural Machine Translation Case Study , 2021, ACL.
[101] Reut Tsarfaty,et al. (Un)solving Morphological Inflection: Lemma Overlap Artificially Inflates Models’ Performance , 2021, ACL.
[102] J. Ainslie,et al. Making Transformers Solve Compositional Tasks , 2021, ACL.
[103] Luke Zettlemoyer,et al. Noisy Channel Language Model Prompting for Few-Shot Text Classification , 2021, ACL.
[104] Olivier Bonami,et al. Not quite there yet: Combining analogical patterns and encoder-decoder networks for cognitively plausible inflection , 2021, Proceedings of the 18th SIGMORPHON Workshop on Computational Research in Phonetics, Phonology, and Morphology.
[105] Panagiotis Kouris,et al. Abstractive Text Summarization: Enhancing Sequence-to-Sequence Models Using Word Sense Disambiguation and Semantic Content Generalization , 2021, CL.
[106] Ramón Fernández Astudillo,et al. Structural Guidance for Transformer Language Models , 2021, ACL.
[107] Emmanuele Chersoni,et al. Did the Cat Drink the Coffee? Challenging Transformers with Generalized Event Knowledge , 2021, STARSEM.
[108] Y. Gal,et al. Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks , 2021, NeurIPS Datasets and Benchmarks.
[109] Kyle Lo,et al. FLEX: Unifying Evaluation for Few-Shot NLP , 2021, NeurIPS.
[110] Mingyue Han,et al. Doing Good or Doing Right? Exploring the Weakness of Commonsense Causal Reasoning Models , 2021, ACL.
[111] E. Kharitonov,et al. Can Transformers Jump Around Right in Natural Language? Assessing Performance Transfer from SCAN , 2021, BLACKBOXNLP.
[112] He He,et al. An Investigation of the (In)effectiveness of Counterfactually Augmented Data , 2021, ACL.
[113] Hongxia Jin,et al. Enhancing the generalization for Intent Classification and Out-of-Domain Detection in SLU , 2021, ACL.
[114] Rifat Shahriyar,et al. XL-Sum: Large-Scale Multilingual Abstractive Summarization for 44 Languages , 2021, FINDINGS.
[115] Matthew Richardson,et al. KaggleDBQA: Realistic Evaluation of Text-to-SQL Parsers , 2021, ACL.
[116] Pradeep Ravikumar,et al. Improving Compositional Generalization in Classification Tasks via Structure Annotations , 2021, ACL.
[117] Vivek Srikumar,et al. X-Fact: A New Benchmark Dataset for Multilingual Fact Checking , 2021, ACL.
[118] Nurul Lubis,et al. Domain-independent User Simulation with Transformers for Task-oriented Dialogue Systems , 2021, SIGDIAL.
[119] Marco Baroni. On the proper role of linguistically-oriented deep net analysis in linguistic theorizing , 2021, ArXiv.
[120] Dilek Z. Hakkani-Tür,et al. Generative Conversational Networks , 2021, SIGDIAL.
[121] Dietrich Klakow,et al. Modeling Profanity and Hate Speech in Social Media with Semantic Subspaces , 2021, WOAH.
[122] Sebastian Ruder,et al. Parameter-efficient Multi-task Fine-tuning for Transformers via Shared Hypernetworks , 2021, ACL.
[123] Marco Damonte,et al. One Semantic Parser to Parse Them All: Sequence to Sequence Multi-Task Learning on Semantic Parsing Datasets , 2021, STARSEM.
[124] Megha Srivastava,et al. Question Generation for Adaptive Education , 2021, ACL.
[125] Kenny Smith,et al. Meta-Learning to Compositionally Generalize , 2021, ACL.
[126] Jacob Andreas,et al. Lexicon Learning for Few Shot Sequence Modeling , 2021, ACL.
[127] Pascale Fung,et al. X2Parser: Cross-Lingual and Cross-Domain Framework for Task-Oriented Compositional Semantic Parsing , 2021, REPL4NLP.
[128] Ethan Gotlieb Wilcox,et al. A Targeted Assessment of Incremental Processing in Neural Language Models and Humans , 2021, ACL.
[129] Kai-Wei Chang,et al. Syntax-augmented Multilingual BERT for Cross-lingual Transfer , 2021, ACL.
[130] Milad Shokouhi,et al. A Dataset and Baselines for Multilingual Reply Suggestion , 2021, ACL.
[131] Prateek Yadav,et al. multiPRover: Generating Multiple Proofs for Improved Interpretability in Rule Reasoning , 2021, NAACL.
[132] Marten van Schijndel,et al. Uncovering Constraint-Based Behavior in Neural Models via Targeted Fine-Tuning , 2021, ACL.
[133] Chinmay Choudhary,et al. Improving the Performance of UDify with Linguistic Typology Knowledge , 2021, SIGTYP.
[134] Sarah Ita Levitan,et al. Detecting Multilingual COVID-19 Misinformation on Social Media via Contextualized Embeddings , 2021, NLP4IF.
[135] Marco Brambilla,et al. Content-based Stance Classification of Tweets about the 2020 Italian Constitutional Referendum , 2021, SOCIALNLP.
[136] Ekaterina Vylomova,et al. Anlirika: An LSTM–CNN Flow Twister for Spoken Language Identification , 2021, SIGTYP.
[137] Francis M. Tyers,et al. Do RNN States Encode Abstract Phonological Alternations? , 2021, NAACL.
[138] Ahmed Khoumsi,et al. Domain Adaptation for Arabic Cross-Domain and Cross-Dialect Sentiment Analysis from Contextualized Word Embedding , 2021, NAACL.
[139] Jacob Andreas,et al. Compositional Generalization for Neural Semantic Parsing via Span-level Supervised Attention , 2021, NAACL.
[140] Yongjing Yin,et al. On Compositional Generalization of Neural Machine Translation , 2021, ACL.
[141] Constantin Orasan,et al. An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformers , 2021, ACL.
[142] Diyi Yang,et al. HiddenCut: Simple Data Augmentation for Natural Language Understanding with Better Generalizability , 2021, ACL.
[143] Ce Zhang,et al. Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models , 2021, ACL.
[144] Jakub Szymanik,et al. Language Models Use Monotonicity to Assess NPI Licensing , 2021, FINDINGS.
[145] Xiaodong Liu,et al. Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization , 2021, ACL.
[146] Douwe Kiela,et al. True Few-Shot Learning with Language Models , 2021, NeurIPS.
[147] Minlie Huang,et al. OpenMEVA: A Benchmark for Evaluating Open-ended Story Generation Metrics , 2021, ACL.
[148] Mingxuan Wang,et al. Learning Language Specific Sub-network for Multilingual Machine Translation , 2021, ACL.
[149] Haitao Zheng,et al. Few-NERD: A Few-shot Named Entity Recognition Dataset , 2021, ACL.
[150] Gholamreza Haffari,et al. Neural-Symbolic Commonsense Reasoner with Relation Predictors , 2021, ACL.
[151] Kathleen McKeown,et al. Adversarial Learning for Zero-Shot Stance Detection on Social Media , 2021, NAACL.
[152] I. Kobayashi,et al. OCHADAI-KYOTO at SemEval-2021 Task 1: Enhancing Model Generalization and Robustness for Lexical Complexity Prediction , 2021, SEMEVAL.
[153] Zili Zhou,et al. Encoding Explanatory Knowledge for Zero-shot Science Question Answering , 2021, IWCS.
[154] Gerasimos Lampouras,et al. Generalising Multilingual Concept-to-Text NLG with Language Agnostic Delexicalisation , 2021, ACL.
[155] Juho Lee,et al. Learning to Perturb Word Embeddings for Out-of-distribution QA , 2021, ACL.
[156] Kentaro Inui,et al. Learning to Learn to be Right for the Right Reasons , 2021, NAACL.
[157] Xiang Zhou,et al. Hidden Biases in Unreliable News Detection Datasets , 2021, EACL.
[158] Xiang Ren,et al. X-METRA-ADA: Cross-lingual Meta-Transfer learning Adaptation to Natural Language Understanding and Question Answering , 2021, NAACL.
[159] S. Riedel,et al. Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity , 2021, ACL.
[160] Ngoc Thang Vu,et al. AmericasNLI: Evaluating Zero-shot Natural Language Understanding of Pretrained Multilingual Models in Truly Low-resource Languages , 2021, ACL.
[161] Hannaneh Hajishirzi,et al. Cross-Task Generalization via Natural Language Crowdsourcing Instructions , 2021, ACL.
[162] Bill Yuchen Lin,et al. Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learning , 2021, EMNLP.
[163] S. Riedel,et al. Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation , 2021, EMNLP.
[164] Xiang Ren,et al. CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP , 2021, EMNLP.
[165] Nanyun Peng,et al. Improving Zero-Shot Cross-Lingual Transfer Learning via Robust Training , 2021, EMNLP.
[166] Oyvind Tafjord,et al. Explaining Answers with Entailment Trees , 2021, EMNLP.
[167] Marek Rei,et al. Memorisation versus Generalisation in Pre-trained Language Models , 2021, ACL.
[168] Dan Roth,et al. Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema , 2021, EMNLP.
[169] Diyi Yang,et al. Structure-Aware Abstractive Conversation Summarization via Discourse and Action Graphs , 2021, NAACL.
[170] Jinlan Fu,et al. XTREME-R: Towards More Challenging and Nuanced Multilingual Evaluation , 2021, EMNLP.
[171] Jason Weston,et al. Retrieval Augmentation Reduces Hallucination in Conversation , 2021, EMNLP.
[172] Shrey Desai,et al. Span Pointer Networks for Non-Autoregressive Task-Oriented Semantic Parsing , 2021, EMNLP.
[173] Douwe Kiela,et al. Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little , 2021, EMNLP.
[174] Snigdha Chaturvedi,et al. Is Everything in Order? A Simple Way to Order Sentences , 2021, EMNLP.
[175] Mans Hulden,et al. Can a Transformer Pass the Wug Test? Tuning Copying Bias in Neural Morphological Inflection Models , 2021, ACL.
[176] Xuezhi Wang,et al. Continual Learning for Text Classification with Information Disentanglement Based Regularization , 2021, NAACL.
[177] Wenpeng Yin,et al. Learning to Synthesize Data for Semantic Parsing , 2021, NAACL.
[178] T. Zhao,et al. Adversarial Regularization as Stackelberg Game: An Unrolled Optimization Approach , 2021, EMNLP.
[179] Dan Klein,et al. Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections , 2021, EMNLP.
[180] Kai Yu,et al. ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parser , 2021, NAACL.
[181] Tharindu Ranasinghe,et al. TransWiC at SemEval-2021 Task 2: Transformer-based Multilingual and Cross-lingual Word-in-Context Disambiguation , 2021, SEMEVAL.
[182] Zhiyi Ma,et al. Dynabench: Rethinking Benchmarking in NLP , 2021, NAACL.
[183] Erenay Dayanik,et al. Disentangling Document Topic and Author Gender in Multiple Languages: Lessons for Adversarial Debiasing , 2021, WASSA.
[184] Graham Neubig,et al. MasakhaNER: Named Entity Recognition for African Languages , 2021, Transactions of the Association for Computational Linguistics.
[185] Pascale Fung,et al. AdaptSum: Towards Low-Resource Domain Adaptation for Abstractive Summarization , 2021, NAACL.
[186] Timothy Baldwin,et al. Evaluating Document Coherence Modeling , 2021, Transactions of the Association for Computational Linguistics.
[187] David Ifeoluwa Adelani,et al. The Effect of Domain and Diacritics in Yoruba–English Neural Machine Translation , 2021, MTSUMMIT.
[188] Sanjeev Khudanpur,et al. Learning Feature Weights using Reward Modeling for Denoising Parallel Corpora , 2021, WMT.
[189] Franck Dernoncourt,et al. Towards Interpreting and Mitigating Shortcut Learning Behavior of NLU models , 2021, NAACL.
[190] Emily M. Bender,et al. On the Dangers of Stochastic Parrots: Can Language Models Be Too Big? 🦜 , 2021, FAccT.
[191] Diana Inkpen,et al. Conditional Adversarial Networks for Multi-Domain Text Classification , 2021, ADAPTNLP.
[192] Phil Blunsom,et al. Mind the Gap: Assessing Temporal Generalization in Neural Language Models , 2021, NeurIPS.
[193] Karin Verspoor,et al. Memorization vs. Generalization : Quantifying Data Leakage in NLP Performance Evaluation , 2021, EACL.
[194] Lucas Weber,et al. Language Modelling as a Multi-Task Problem , 2021, EACL.
[195] Hitomi Yanaka,et al. Exploring Transitivity in Neural NLI Models through Veridicality , 2021, EACL.
[196] Sonal Gupta,et al. Muppet: Massive Multi-task Representations with Pre-Finetuning , 2021, EMNLP.
[197] Roi Reichart,et al. Model Compression for Domain Adaptation through Causal Effect Estimation , 2021, Transactions of the Association for Computational Linguistics.
[198] Xiang Ren,et al. Learning to Generate Task-Specific Adapters from Task Description , 2021, ACL.
[199] Valentin Hofmann,et al. Superbizarre Is Not Superb: Derivational Morphology Improves BERT’s Interpretation of Complex Words , 2021, ACL.
[200] Jackie Chi Kit Cheung,et al. Optimizing Deeper Transformers on Small Datasets , 2020, ACL.
[201] Jianfeng Gao,et al. RADDLE: An Evaluation Benchmark and Analysis Platform for Robust Task-oriented Dialog Systems , 2020, ACL.
[202] Mohit Bansal,et al. I like fish, especially dolphins: Addressing Contradictions in Dialogue Modeling , 2020, ACL.
[203] Magdalena Biesialska,et al. Continual Lifelong Learning in Natural Language Processing: A Survey , 2020, COLING.
[204] Pang Wei Koh,et al. WILDS: A Benchmark of in-the-Wild Distribution Shifts , 2020, ICML.
[205] Yoav Goldberg,et al. Amnesic Probing: Behavioral Explanation with Amnesic Counterfactuals , 2020, Transactions of the Association for Computational Linguistics.
[206] Nathan Schneider,et al. Supertagging the Long Tail with Tree-Structured Decoding of Complex Categories , 2020, Transactions of the Association for Computational Linguistics.
[207] Jiafeng Guo,et al. Event Coreference Resolution with their Paraphrases and Argument-aware Embeddings , 2020, COLING.
[208] Valeria de Paiva,et al. Hy-NLI: a Hybrid system for Natural Language Inference , 2020, COLING.
[209] Eduard Hovy,et al. On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT , 2020, STARSEM.
[210] Miikka Silfverberg,et al. Noise Isn’t Always Negative: Countering Exposure Bias in Sequence-to-Sequence Inflection Models , 2020, COLING.
[211] Robert Frank,et al. Sequence-to-Sequence Networks Learn the Meaning of Reflexive Anaphora , 2020, CRAC.
[212] Kentaro Inui,et al. Efficient Estimation of Influence of a Training Instance , 2020, SUSTAINLP.
[213] Matt Gardner,et al. Learning from Task Descriptions , 2020, EMNLP.
[214] Ramesh Nallapati,et al. Unsupervised Domain Adaptation for Cross-lingual Text Labeling , 2020, FINDINGS.
[215] Daniel Gillick,et al. Entity Linking in 100 Languages , 2020, EMNLP.
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