Papers by Sanjana Gautam
Improving the Distributional Alignment of LLMs using Supervision (2026.acl-long)
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Gauri Kambhatla, Sanjana Gautam, Angela Zhang, Alexander Liu, Ravi Srinivasan, Junyi Jessy Li, Matthew Lease
| Challenge: | Existing work to evaluate LLMs' alignment with human values and opinions has a key shortcoming. |
| Approach: | They propose to add supervision to LLMs to improve alignment with diverse populations . they find that supervision improves alignment across public health, public opinion, values and beliefs . |
| Outcome: | The proposed method improves the alignment of LLMs with diverse populations on subjective questions. |
Nationality Bias in Text Generation (2023.eacl-main)
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| Challenge: | Existing studies have shown that nationality biases in language models can be a factor in improving the performance of social NLP models. |
| Approach: | They propose to use a text generation model, GPT-2, to analyze how the number of internet users and the country’s economic status affects the sentiment of stories. |
| Outcome: | The proposed model accentuates biases about country-based demonyms and reduces them with the use of adversarial triggering. |
The Sentiment Problem: A Critical Survey towards Deconstructing Sentiment Analysis (2023.emnlp-main)
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Pranav Venkit, Mukund Srinath, Sanjana Gautam, Saranya Venkatraman, Vipul Gupta, Rebecca Passonneau, Shomir Wilson
| Challenge: | Existing research reveals a notable absence of interdisciplinary endeavors to comprehend the social dimensions of sentiment analysis, encompassing aspects like emotion and fairness. |
| Approach: | They propose an ethics sheet encompassing critical inquiries to guide practitioners in ensuring equitable utilization of SA. |
| Outcome: | The proposed ethics sheet outlines the importance of adopting an interdisciplinary approach to defining sentiment in SA and offers a pragmatic solution for its implementation. |