16 citations · 28 across the 18 of their papers we have counts for
21 papers
Teacher Perception of Automatically Extracted Grammar Concepts for L2 Language Learning
Aditi Chaudhary, Arun Sampath, Ashwin Sheshadri +2
One of the challenges in language teaching is how best to organize rules regarding syntax, semantics, or phonology in a meaningful manner. This not only requires content creators t…
Ambiguity-Aware In-Context Learning with Large Language Models
Lingyu Gao, Aditi Chaudhary, Krishna Srinivasan +3
In-context learning (ICL) i.e. showing LLMs only a few task-specific demonstrations has led to downstream gains with no task-specific fine-tuning required. However, LLMs are sensit…
Exploring the Viability of Synthetic Query Generation for Relevance Prediction
Aditi Chaudhary, Karthik Raman, Krishna Srinivasan +3
Query-document relevance prediction is a critical problem in Information Retrieval systems. This problem has increasingly been tackled using (pretrained) transformer-based models w…
Salient Span Masking for Temporal Understanding
Jeremy R. Cole, Aditi Chaudhary, Bhuwan Dhingra +1
Salient Span Masking (SSM) has shown itself to be an effective strategy to improve closed-book question answering performance. SSM extends general masked language model pretraining…
Teacher Perception of Automatically Extracted Grammar Concepts for L2 Language Learning
Aditi Chaudhary, Arun Sampath, Ashwin Sheshadri +2
One of the challenges of language teaching is how to organize the rules regarding syntax, semantics, or phonology of the language in a meaningful manner. This not only requires ped…
AUTOLEX: An Automatic Framework for Linguistic Exploration
Aditi Chaudhary, Zaid Sheikh, David R Mortensen +2
Each language has its own complex systems of word, phrase, and sentence construction, the guiding principles of which are often summarized in grammar descriptions for the consumpti…
When is Wall a Pared and when a Muro? -- Extracting Rules Governing Lexical Selection
Aditi Chaudhary, Kayo Yin, Antonios Anastasopoulos +1
Learning fine-grained distinctions between vocabulary items is a key challenge in learning a new language. For example, the noun "wall" has different lexical manifestations in Span…
Do Context-Aware Translation Models Pay the Right Attention?
Kayo Yin, Patrick Fernandes, Danish Pruthi +3
Context-aware machine translation models are designed to leverage contextual information, but often fail to do so. As a result, they inaccurately disambiguate pronouns and polysemo…
Evaluating the Morphosyntactic Well-formedness of Generated Texts
Adithya Pratapa, Antonios Anastasopoulos, Shruti Rijhwani +4
Text generation systems are ubiquitous in natural language processing applications. However, evaluation of these systems remains a challenge, especially in multilingual settings. I…
Reducing Confusion in Active Learning for Part-Of-Speech Tagging
Aditi Chaudhary, Antonios Anastasopoulos, Zaid Sheikh +1
Active learning (AL) uses a data selection algorithm to select useful training samples to minimize annotation cost. This is now an essential tool for building low-resource syntacti…
SIGTYP 2020 Shared Task: Prediction of Typological Features
Johannes Bjerva, Elizabeth Salesky, Sabrina J. Mielke +6
Typological knowledge bases (KBs) such as WALS (Dryer and Haspelmath, 2013) contain information about linguistic properties of the world's languages. They have been shown to be use…
DICT-MLM: Improved Multilingual Pre-Training using Bilingual Dictionaries
Aditi Chaudhary, Karthik Raman, Krishna Srinivasan +1
Pre-trained multilingual language models such as mBERT have shown immense gains for several natural language processing (NLP) tasks, especially in the zero-shot cross-lingual setti…
Automatic Extraction of Rules Governing Morphological Agreement
Aditi Chaudhary, Antonios Anastasopoulos, Adithya Pratapa +4
Creating a descriptive grammar of a language is an indispensable step for language documentation and preservation. However, at the same time it is a tedious, time-consuming task. I…
A Summary of the First Workshop on Language Technology for Language Documentation and Revitalization
Graham Neubig, Shruti Rijhwani, Alexis Palmer +21
Despite recent advances in natural language processing and other language technology, the application of such technology to language documentation and conservation has been limited…
Gesture controlled environment using sixth sense technology and its implementation in IoT
Shubhankar Mohan, Aditi Chaudhary, Prachie Gupta +1
This paper proposes an idea of building an interface to merge the existing technologies like Image processing, Internet of Things, Sixth sense, etc. at one place to reduce the hard…
A Little Annotation does a Lot of Good: A Study in Bootstrapping Low-resource Named Entity Recognizers
Aditi Chaudhary, Jiateng Xie, Zaid Sheikh +2
Most state-of-the-art models for named entity recognition (NER) rely on the availability of large amounts of labeled data, making them challenging to extend to new, lower-resourced…
Dr.Quad at MEDIQA 2019: Towards Textual Inference and Question Entailment using contextualized representations
Vinayshekhar Bannihatti Kumar, Ashwin Srinivasan, Aditi Chaudhary +3
This paper presents the submissions by Team Dr.Quad to the ACL-BioNLP 2019 shared task on Textual Inference and Question Entailment in the Medical Domain. Our system is based on th…
CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology
Aditi Chaudhary, Elizabeth Salesky, Gayatri Bhat +3
This paper presents the submission by the CMU-01 team to the SIGMORPHON 2019 task 2 of Morphological Analysis and Lemmatization in Context. This task requires us to produce the lem…
The ARIEL-CMU Systems for LoReHLT18
Aditi Chaudhary, Siddharth Dalmia, Junjie Hu +27
This paper describes the ARIEL-CMU submissions to the Low Resource Human Language Technologies (LoReHLT) 2018 evaluations for the tasks Machine Translation (MT), Entity Discovery a…
Weighted Global Normalization for Multiple Choice Reading Comprehension over Long Documents
Aditi Chaudhary, Bhargavi Paranjape, Michiel de Jong
Motivated by recent evidence pointing out the fragility of high-performing span prediction models, we direct our attention to multiple choice reading comprehension. In particular,…
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations
Aditi Chaudhary, Chunting Zhou, Lori Levin +3
Much work in Natural Language Processing (NLP) has been for resource-rich languages, making generalization to new, less-resourced languages challenging. We present two approaches f…