Papers by Kumar Tanmay
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. |
Ethical Reasoning and Moral Value Alignment of LLMs Depend on the Language We Prompt Them in (2024.lrec-main)
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| Challenge: | Ethical reasoning is a crucial skill for Large Language Models (LLMs). However, moral values are not universal, but rather influenced by language and culture. |
| Approach: | They extend the study of ethical reasoning of LLMs by (CITATION) to a multilingual setup using six languages: English, Spanish, Russian, Chinese, Hindi, and Swahili. |
| Outcome: | The proposed model is based on a multilingual setup in English, Spanish, Russian, Chinese, Hindi, and Swahili. |
Ethical Reasoning over Moral Alignment: A Case and Framework for In-Context Ethical Policies in LLMs (2023.findings-emnlp)
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| Challenge: | a paper by a team of researchers proposes that large language models should be morally aligned to ethical principles . a moral compass is a model that integrates moral dilemmas with moral principles pertaining to different foramlisms of normative ethics . |
| Approach: | They propose to infuse generic ethical reasoning capabilities into large-scale models . they argue that LLMs should take a moral stance on value pluralism . |
| Outcome: | a new ethical reasoning framework integrates moral dilemmas with moral principles . the framework is based on the results of a hypothetical case study on a large-scale model . |
DUBLIN: Visual Document Understanding By Language-Image Network (2023.emnlp-industry)
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Kriti Aggarwal, Aditi Khandelwal, Kumar Tanmay, Owais Khan Mohammed, Qiang Liu, Monojit Choudhury, Hardik Chauhan, Subhojit Som, Vishrav Chaudhary, Saurabh Tiwary
| Challenge: | DUBLIN is a pixel-based visual document understanding model that does not rely on OCR. |
| Approach: | They propose a pixel-based visual document understanding model that does not rely on OCR. |
| Outcome: | The proposed model performs on extractive tasks such as DocVQA, InfoVQA and AI2D, and strong performance on abstraction datasets such as VisualMRC and text captioning. |
Do Moral Judgment and Reasoning Capability of LLMs Change with Language? A Study using the Multilingual Defining Issues Test (2024.eacl-long)
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| Challenge: | Existing studies have shown that moral judgment depends on the language in which the dilemma is presented. |
| Approach: | They extend the work of beyond English, to 5 new languages (Chinese, Hindi, Russian, Spanish and Swahili) and probe three LLMs that show substantial multilingual text processing and generation abilities. |
| Outcome: | The models show substantial multilingual text processing and generation abilities. |
ReviewEval: An Evaluation Framework for AI-Generated Reviews (2025.findings-emnlp)
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| Challenge: | escalating volume of academic research necessitates innovative approaches to peer review . authors propose reviewEval, ReviewAgent and ReviewEval to improve on existing reviews . |
| Approach: | They propose a framework for AI-generated reviews that measures alignment with human assessments . they propose 'reviewAgent' that iteratively optimizes its intermediate outputs and external improvement loops . |
| Outcome: | The proposed framework improves actionable insights and analytical depth by 6.78% and 47.62% over baselines and expert reviews. |