Papers by Utkarsh Agarwal
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 . |
EGOILLUSION: Benchmarking Hallucinations in Egocentric Video Understanding (2025.emnlp-main)
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Ashish Seth, Utkarsh Tyagi, Ramaneswaran Selvakumar, Nishit Anand, Sonal Kumar, Sreyan Ghosh, Ramani Duraiswami, Chirag Agarwal, Dinesh Manocha
| Challenge: | Multimodal Large Language Models excel at visual perception and reasoning in third-person and egocentric videos, but are prone to hallucinations, generating coherent yet inaccurate responses. |
| Approach: | They propose to use a benchmark to evaluate MLLM hallucinations in egocentric videos. |
| Outcome: | EGOILLUSION comprises 1,400 videos paired with 8,000 human-annotated open and closed-ended questions designed to trigger hallucinations in both visual and auditory cues in egocentric videos. |
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. |
Nanda Family: Open-Weights Generative Large Language Models for Hindi (2026.eacl-long)
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Aaryamonvikram Singh, Debopriyo Banerjee, Dhruv Sahnan, Monojit Choudhury, Shivam Chauhan, Rocktim Jyoti Das, Xudong Han, Haonan Li, Alok Anil Jadhav, Utkarsh Agarwal, Mukund Choudhary, Fajri Koto, Junaid Hamid Bhat, Awantika Shukla, Samujjwal Ghosh, Samta Kamboj, Onkar Pandit, Lalit Pradhan, Rahul Pal, Sunil Kumar Sahu, Parvez Mullah, Ali El Filali, Zainul Abedien Ahmed Quraishi, Neha Sengupta, Gokulakrishnan Ramakrishnan, Rituraj Joshi, Gurpreet Gosal, Avraham Sheinin, Natalia Vassilieva, Preslav Nakov
| Challenge: | Large language models remain predominantly English-centric, which limits their utility for underrepresented languages. |
| Approach: | They propose to extend Llama’s vocabulary with 20% Hindi-specific tokens, thus halving Hindi tokenization fertility while preserving English efficiency. |
| Outcome: | The proposed models outperform open-weight models of comparable size on a 65B-token corpus and bilingual instruction and safety alignment on . a culturally grounded dataset. |