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CLiMP: A Benchmark for Chinese Language Model Evaluation
Linguistically informed analyses of language models (LMs) contribute to ...
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Coloring the Black Box: What Synesthesia Tells Us about Character Embeddings
In contrast to their word- or sentence-level counterparts, character emb...
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Tackling the Low-resource Challenge for Canonical Segmentation
Canonical morphological segmentation consists of dividing words into the...
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Acrostic Poem Generation
We propose a new task in the area of computational creativity: acrostic ...
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The NYU-CUBoulder Systems for SIGMORPHON 2020 Task 0 and Task 2
We describe the NYU-CUBoulder systems for the SIGMORPHON 2020 Task 0 on ...
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The SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion
In this paper, we describe the findings of the SIGMORPHON 2020 shared ta...
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Self-Training for Unsupervised Parsing with PRPN
Neural unsupervised parsing (UP) models learn to parse without access to...
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English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too
Intermediate-task training has been shown to substantially improve pretr...
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The IMS-CUBoulder System for the SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion
In this paper, we present the systems of the University of Stuttgart IMS...
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Unsupervised Morphological Paradigm Completion
We propose the task of unsupervised morphological paradigm completion. G...
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Intermediate-Task Transfer Learning with Pretrained Models for Natural Language Understanding: When and Why Does It Work?
While pretrained models such as BERT have shown large gains across natur...
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Weakly Supervised POS Taggers Perform Poorly on Truly Low-Resource Languages
Part-of-speech (POS) taggers for low-resource languages which are exclus...
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Learning to Learn Morphological Inflection for Resource-Poor Languages
We propose to cast the task of morphological inflection - mapping a lemm...
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Grammatical Gender, Neo-Whorfianism, and Word Embeddings: A Data-Driven Approach to Linguistic Relativity
The relation between language and thought has occupied linguists for at ...
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Acquisition of Inflectional Morphology in Artificial Neural Networks With Prior Knowledge
How does knowledge of one language's morphology influence learning of in...
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Towards Realistic Practices In Low-Resource Natural Language Processing: The Development Set
Development sets are impractical to obtain for real low-resource languag...
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Transductive Auxiliary Task Self-Training for Neural Multi-Task Models
Multi-task learning and self-training are two common ways to improve a m...
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Probing for Semantic Classes: Diagnosing the Meaning Content of Word Embeddings
Word embeddings typically represent different meanings of a word in a si...
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Subword-Level Language Identification for Intra-Word Code-Switching
Language identification for code-switching (CS), the phenomenon of alter...
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Verb Argument Structure Alternations in Word and Sentence Embeddings
Verbs occur in different syntactic environments, or frames. We investiga...
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The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection
The CoNLL--SIGMORPHON 2018 shared task on supervised learning of morphol...
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Neural Transductive Learning and Beyond: Morphological Generation in the Minimal-Resource Setting
Neural state-of-the-art sequence-to-sequence (seq2seq) models often do n...
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Sentence-Level Fluency Evaluation: References Help, But Can Be Spared!
Motivated by recent findings on the probabilistic modeling of acceptabil...
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Evaluating Word Embeddings in Multi-label Classification Using Fine-grained Name Typing
Embedding models typically associate each word with a single real-valued...
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Lost in Translation: Analysis of Information Loss During Machine Translation Between Polysynthetic and Fusional Languages
Machine translation from polysynthetic to fusional languages is a challe...
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Fortification of Neural Morphological Segmentation Models for Polysynthetic Minimal-Resource Languages
Morphological segmentation for polysynthetic languages is challenging, b...
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Unlabeled Data for Morphological Generation With Character-Based Sequence-to-Sequence Models
We present a semi-supervised way of training a character-based encoder-d...
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One-Shot Neural Cross-Lingual Transfer for Paradigm Completion
We present a novel cross-lingual transfer method for paradigm completion...
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Comparative Study of CNN and RNN for Natural Language Processing
Deep neural networks (DNN) have revolutionized the field of natural lang...
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Neural Multi-Source Morphological Reinflection
We explore the task of multi-source morphological reinflection, which ge...
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Single-Model Encoder-Decoder with Explicit Morphological Representation for Reinflection
Morphological reinflection is the task of generating a target form given...
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