activity
20232026
most citedLarge Human Language Models: A Need and the Challenges

5 citations · 7 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Addressing the Ecological Fallacy in Larger LMs with Human Context

Nikita Soni, Dhruv Vijay Kunjadiya, Pratham Piyush Shah +3

Language model training and inference ignore a fundamental linguistic fact -- there is a dependence between multiple sequences of text written by the same person. Prior work has sh…

cs.CL2025

Residualized Similarity for Faithfully Explainable Authorship Verification

Peter Zeng, Pegah Alipoormolabashi, Jihu Mun +5

Responsible use of Authorship Verification (AV) systems not only requires high accuracy but also interpretable solutions. More importantly, for systems to be used to make decisions…

cs.CL2025★ 1 cited

Evaluation of LLMs-based Hidden States as Author Representations for Psychological Human-Centered NLP Tasks

Nikita Soni, Pranav Chitale, Khushboo Singh +2

Like most of NLP, models for human-centered NLP tasks -- tasks attempting to assess author-level information -- predominantly use representations derived from hidden states of Tran…

cs.CL2024★ 1 cited

Comparing Pre-trained Human Language Models: Is it Better with Human Context as Groups, Individual Traits, or Both?

Nikita Soni, Niranjan Balasubramanian, H. Andrew Schwartz +1

Pre-trained language models consider the context of neighboring words and documents but lack any author context of the human generating the text. However, language depends on the a…

cs.CL2023★ 5 cited

Large Human Language Models: A Need and the Challenges

Nikita Soni, H. Andrew Schwartz, João Sedoc +1

As research in human-centered NLP advances, there is a growing recognition of the importance of incorporating human and social factors into NLP models. At the same time, our NLP sy…