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20162026
most citedAutomated assessment of non-native learner essays: Investigating the role of linguistic features

121 citations · 231 across the 32 of their papers we have counts for

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32 papers · 1 filter

cs.CL2026

Last Translation Benchmark

Vilém Zouhar, Niyati Bafna, Mukund Choudhary +263

For scientific progress, we need benchmarks that test the limits of state-of-the-art models, and evaluation methods that inform us about failure cases. As models get stronger, stan…

cs.CL2026

LLM Judges Can Be Too Generous When There Is No Reference Answer

Chalamalasetti Kranti, Sowmya Vajjala

LLM judges are increasingly being used to evaluate open-ended model responses, often in no-reference settings where a ground-truth answer is unavailable. However, can they reliably…

cs.CL2026

LLM Judges Inconsistently Disagree Across Safety Criteria and Harm Categories

Krishnapriya Vishnubhotla, Sowmya Vajjala, Akriti Vij +1

We evaluate the consistency of automated judges in conducting a multi-dimensional safety evaluation in a reference-free setup. Our results indicate that Large Language Models are u…

cs.CL2026

ComplexityMT: Benchmarking the Interaction Between Text Complexity and Machine Translation

Joseph Marvin Imperial, Junhong Liang, Belal Shoer +9

When a text is translated, does the translation retain the complexity of the original? We introduce ComplexityMT, a new challenge for assessing how text complexity and machine tran…

cs.CL2026

Translating Classical Poetry into Modern Prose

Chalamalasetti Kranti, Sowmya Vajjala

We built a dataset for the task of poem-to-prose translation from 13th-17th Century Telugu classical poetry to contemporary Telugu and English prose, which we call Padyam2Gadyam. T…

cs.CL2026

CommonLID: Re-evaluating State-of-the-Art Language Identification Performance on Web Data

Pedro Ortiz Suarez, Laurie Burchell, Catherine Arnett +94

Language identification (LID) is a fundamental step in curating multilingual corpora. However, LID models still perform poorly for many languages, especially on the noisy and heter…

cs.CL2025

IndicGEC: Powerful Models, or a Measurement Mirage?

Sowmya Vajjala

In this paper, we report the results of the TeamNRC's participation in the BHASHA-Task 1 Grammatical Error Correction shared task https://github.com/BHASHA-Workshop/IndicGEC2025/ f…

cs.CL2025

MetricalARGS: A Taxonomy for Studying Metrical Poetry with LLMs

Chalamalasetti Kranti, Sowmya Vajjala

Prior NLP work studying poetry has focused primarily on automatic poem generation and summarization. Many languages have well-studied traditions of poetic meter which enforce const…

cs.CL2025

MATA: Mindful Assessment of the Telugu Abilities of Large Language Models

Chalamalasetti Kranti, Sowmya Vajjala

In this paper, we introduce MATA, a novel evaluation dataset to assess the ability of Large Language Models (LLMs) in Telugu language, comprising 729 carefully curated multiple-cho…

cs.CL2025

Test Set Quality in Multilingual LLM Evaluation

Chalamalasetti Kranti, Gabriel Bernier-Colborne, Yvan Gauthier +1

Several multilingual benchmark datasets have been developed in a semi-automatic manner in the recent past to measure progress and understand the state-of-the-art in the multilingua…

cs.CL2025

The Problem with Safety Classification is not just the Models

Sowmya Vajjala

Studying the robustness of Large Language Models (LLMs) to unsafe behaviors is an important topic of research today. Building safety classification models or guard models, which ar…

cs.CL2025

Opportunities and Challenges of LLMs in Education: An NLP Perspective

Sowmya Vajjala, Bashar Alhafni, Stefano Bannò +2

Interest in the role of large language models (LLMs) in education is increasing, considering the new opportunities they offer for teaching, learning, and assessment. In this paper,…

cs.CL2025★ 2 cited

UniversalCEFR: Enabling Open Multilingual Research on Language Proficiency Assessment

Joseph Marvin Imperial, Abdullah Barayan, Regina Stodden +16

We introduce UniversalCEFR, a large-scale multilingual and multidimensional dataset of texts annotated with CEFR (Common European Framework of Reference) levels in 13 languages. To…

cs.CL2025★ 4 cited

Does Synthetic Data Help Named Entity Recognition for Low-Resource Languages?

Gaurav Kamath, Sowmya Vajjala

Named Entity Recognition(NER) for low-resource languages aims to produce robust systems for languages where there is limited labeled training data available, and has been an area o…

cs.CL2025★ 2 cited

Text Classification in the LLM Era -- Where do we stand?

Sowmya Vajjala, Shwetali Shimangaud

Large Language Models revolutionized NLP and showed dramatic performance improvements across several tasks. In this paper, we investigated the role of such language models in text…

cs.CL2024★ 1 cited

LLMs in Education: Novel Perspectives, Challenges, and Opportunities

Bashar Alhafni, Sowmya Vajjala, Stefano Bannò +2

The role of large language models (LLMs) in education is an increasing area of interest today, considering the new opportunities they offer for teaching, learning, and assessment.…

cs.CL2024★ 1 cited

Annotation Errors and NER: A Study with OntoNotes 5.0

Gabriel Bernier-Colborne, Sowmya Vajjala

Named Entity Recognition (NER) is a well-studied problem in NLP. However, there is much less focus on studying NER datasets, compared to developing new NER models. In this paper, w…

cs.CL2024

Dravidian language family through Universal Dependencies lens

Taraka Rama, Sowmya Vajjala

The Universal Dependencies (UD) project aims to create a cross-linguistically consistent dependency annotation for multiple languages, to facilitate multilingual NLP. It currently…

cs.CL2024★ 22 cited

Scope Ambiguities in Large Language Models

Gaurav Kamath, Sebastian Schuster, Sowmya Vajjala +1

Sentences containing multiple semantic operators with overlapping scope often create ambiguities in interpretation, known as scope ambiguities. These ambiguities offer rich insight…

cs.CL2023★ 1 cited

A Multilingual Evaluation of NER Robustness to Adversarial Inputs

Akshay Srinivasan, Sowmya Vajjala

Adversarial evaluations of language models typically focus on English alone. In this paper, we performed a multilingual evaluation of Named Entity Recognition (NER) in terms of its…

cs.CL2022

Automatic Text Simplification of News Articles in the Context of Public Broadcasting

Diego Maupomé, Fanny Rancourt, Thomas Soulas +8

This report summarizes the work carried out by the authors during the Twelfth Montreal Industrial Problem Solving Workshop, held at Université de Montréal in August 2022. The team…

cs.CL2022

What do we Really Know about State of the Art NER?

Sowmya Vajjala, Ramya Balasubramaniam

Named Entity Recognition (NER) is a well researched NLP task and is widely used in real world NLP scenarios. NER research typically focuses on the creation of new ways of training…

cs.CL2022

A Neural Pairwise Ranking Model for Readability Assessment

Justin Lee, Sowmya Vajjala

Automatic Readability Assessment (ARA), the task of assigning a reading level to a text, is traditionally treated as a classification problem in NLP research. In this paper, we pro…

cs.CL2021

Teaching NLP outside Linguistics and Computer Science classrooms: Some challenges and some opportunities

Sowmya Vajjala

NLP's sphere of influence went much beyond computer science research and the development of software applications in the past decade. We see people using NLP methods in a range of…