Papers by Neel Bhandari
Imperfectly Cooperative Human-AI Interactions: Comparing the Impacts of Human and AI Attributes in Simulated and User Studies (2026.findings-acl)
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Myke C. Cohen, Mingqian Zheng, Neel Bhandari, Hsien-Te Kao, Xuhui Zhou, Daniel Nguyen, Laura Cassani, Maarten Sap, Svitlana Volkova
| Challenge: | In simulations, personality traits and AI attributes were comparatively influential, but with actual human subjects, AI attributes – particularly transparency – were much more impactful. |
| Approach: | They compare a purely simulated dataset and a parallel human subjects experiment to examine how human personality traits and AI design characteristics jointly shape interaction outcomes in imperfectly cooperative scenarios. |
| Outcome: | The results show that personality traits and AI attributes are comparatively influential in simulations, but with actual human subjects, they are much more impactful. |
Out of Style: RAG’s Fragility to Linguistic Variation (2026.eacl-long)
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| Challenge: | linguistic reformulations impact both retrieval and generation stages, leading to a relative performance drop of up to 40.41% for less formal queries and 38.86% for queries containing grammatical errors. |
| Approach: | They evaluate two retrieval models and nine LLMs across four QA datasets and examine how linguistic reformulations impact RAG performance. |
| Outcome: | The proposed models show that linguistic reformulations significantly impact both retrieval and generation stages, leading to a performance drop of up to 40.41% for less formal queries and 38.86% for queries containing grammatical errors. |