7 citations · 16 across the 17 of their papers we have counts for
17 papers
AITutor-EvalKit: Exploring the Capabilities of AI Tutors
Numaan Naeem, Kaushal Kumar Maurya, Kseniia Petukhova +1
We present AITutor-EvalKit, an application that uses language technology to evaluate the pedagogical quality of AI tutors, provides software for demonstration and evaluation, as we…
Pedagogy-driven Evaluation of Generative AI-powered Intelligent Tutoring Systems
Kaushal Kumar Maurya, Ekaterina Kochmar
The interdisciplinary research domain of Artificial Intelligence in Education (AIED) has a long history of developing Intelligent Tutoring Systems (ITSs) by integrating insights fr…
LLMs cannot spot math errors, even when allowed to peek into the solution
KV Aditya Srivatsa, Kaushal Kumar Maurya, Ekaterina Kochmar
Large language models (LLMs) demonstrate remarkable performance on math word problems, yet they have been shown to struggle with meta-reasoning tasks such as identifying errors in…
Findings of the BEA 2025 Shared Task on Pedagogical Ability Assessment of AI-powered Tutors
Ekaterina Kochmar, Kaushal Kumar Maurya, Kseniia Petukhova +3
This shared task has aimed to assess pedagogical abilities of AI tutors powered by large language models (LLMs), focusing on evaluating the quality of tutor responses aimed at stud…
Can LLMs Reliably Simulate Real Students' Abilities in Mathematics and Reading Comprehension?
KV Aditya Srivatsa, Kaushal Kumar Maurya, Ekaterina Kochmar
Large Language Models (LLMs) are increasingly used as proxy students in the development of Intelligent Tutoring Systems (ITSs) and in piloting test questions. However, to what exte…
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,…
Simulating Student-Tutor Interactions with LLMs for Multilingual Math Feedback
Junior Cedric Tonga, KV Aditya Srivatsa, Kaushal Kumar Maurya +2
Large language models (LLMs) have demonstrated the ability to generate formative feedback and instructional hints in English, making them increasingly relevant for AI-assisted educ…
Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors
Kaushal Kumar Maurya, KV Aditya Srivatsa, Kseniia Petukhova +1
In this paper, we investigate whether current state-of-the-art large language models (LLMs) are effective as AI tutors and whether they demonstrate pedagogical abilities necessary…
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.…
SelectLLM: Query-Aware Efficient Selection Algorithm for Large Language Models
Kaushal Kumar Maurya, KV Aditya Srivatsa, Ekaterina Kochmar
Large language models (LLMs) have been widely adopted due to their remarkable performance across various applications, driving the accelerated development of a large number of dive…
Harnessing the Power of Multiple Minds: Lessons Learned from LLM Routing
KV Aditya Srivatsa, Kaushal Kumar Maurya, Ekaterina Kochmar
With the rapid development of LLMs, it is natural to ask how to harness their capabilities efficiently. In this paper, we explore whether it is feasible to direct each input query…
Trie-NLG: Trie Context Augmentation to Improve Personalized Query Auto-Completion for Short and Unseen Prefixes
Kaushal Kumar Maurya, Maunendra Sankar Desarkar, Manish Gupta +1
Query auto-completion (QAC) aims to suggest plausible completions for a given query prefix. Traditionally, QAC systems have leveraged tries curated from historical query logs to su…
CharSpan: Utilizing Lexical Similarity to Enable Zero-Shot Machine Translation for Extremely Low-resource Languages
Kaushal Kumar Maurya, Rahul Kejriwal, Maunendra Sankar Desarkar +1
We address the task of machine translation (MT) from extremely low-resource language (ELRL) to English by leveraging cross-lingual transfer from 'closely-related' high-resource lan…
Meta-X: A Meta-Learning Approach Based on Language Clustering for Zero-Shot Cross-Lingual Transfer and Generation
Kaushal Kumar Maurya, Maunendra Sankar Desarkar
Recently, the NLP community has witnessed a rapid advancement in multilingual and cross-lingual transfer research where the supervision is transferred from high-resource languages…
ZmBART: An Unsupervised Cross-lingual Transfer Framework for Language Generation
Kaushal Kumar Maurya, Maunendra Sankar Desarkar, Yoshinobu Kano +1
Despite the recent advancement in NLP research, cross-lingual transfer for natural language generation is relatively understudied. In this work, we transfer supervision from high r…
Walk in Wild: An Ensemble Approach for Hostility Detection in Hindi Posts
Chander Shekhar, Bhavya Bagla, Kaushal Kumar Maurya +1
As the reach of the internet increases, pejorative terms started flooding over social media platforms. This leads to the necessity of identifying hostile content on social media pl…
Coarse and Fine-Grained Hostility Detection in Hindi Posts using Fine Tuned Multilingual Embeddings
Arkadipta De, Venkatesh E, Kaushal Kumar Maurya +1
Due to the wide adoption of social media platforms like Facebook, Twitter, etc., there is an emerging need of detecting online posts that can go against the community acceptance st…