Papers by Tanmay Sinha
Automatic Generation of Socratic Subquestions for Teaching Math Word Problems (2022.emnlp-main)
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| Challenge: | We hypothesize that questioning can enhance human performance and assist solvers . |
| Approach: | They propose to use large language models to generate sequential questions for math word problem-solving . they propose to apply these models to a variety of math word problems . |
| Outcome: | The proposed model improves the performance of a math word problem solver by generating more questions than other models. |
MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems (2023.findings-emnlp)
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Jakub Macina, Nico Daheim, Sankalan Chowdhury, Tanmay Sinha, Manu Kapur, Iryna Gurevych, Mrinmaya Sachan
| Challenge: | Existing models for automatic dialogue tutoring fail to provide accurate feedback or reveal solutions to students too early. |
| Approach: | They propose a framework to generate one-to-one teacher-student tutoring dialogues by pairing human teachers with a Large Language Model (LLM) they use scaffolding questions and annotations to fine-tune models to be more effective tutors . |
| Outcome: | The proposed framework can generate 3k one-to-one teacher-student tutoring dialogues grounded in multi-step math reasoning problems. |
Opportunities and Challenges in Neural Dialog Tutoring (2023.eacl-main)
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| Challenge: | Existing approaches to designing dialog tutors have been challenging . current approaches perform poorly in constrained learning scenarios, authors find . |
| Approach: | They analyze dialog tutoring models using automatic and human evaluations to understand the new opportunities brought by dialog tutors. |
| Outcome: | The proposed models perform poorly in less constrained learning scenarios, the authors show . they find large number of model reasoning errors in 45% of conversations . |