most citedHow the cascade inference problem distorts information diffusion

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.IR2026

IntentTune: Using user demand and personalization to resolve "unknown" query intents for e-commerce search

Rachith Aiyappa, Ishita Khan, Chester Palen-Michel +4

Understanding user intent is fundamental to delivering relevant search results in e-commerce. However, substantial fraction of real-world queries are under-specified (e.g., "watch"…

cs.SI20261 cited

How the cascade inference problem distorts information diffusion

Matthew R. DeVerna, Francesco Pierri, Rachith Aiyappa +3

To analyze the flow of information online, experts often rely on platform-provided data from social media companies, which typically attribute all resharing actions to an original…

cs.SI2026

Emergence of Stereotypes and Affective Polarization from Belief Network Dynamics

Ozgur Can Seckin, Rachith Aiyappa, Madalina Vlasceanu +3

Our belief systems are shaped by social processes, such as observations and influence, and by cognitive processes, such as the drive for internal coherence. These processes steer h…

cs.CL2026

What Helps Language Models Predict Human Beliefs: Demographics or Prior Stances?

Joseph Malone, Rachith Aiyappa, Byunghwee Lee +3

Beliefs shape how people reason, communicate, and behave. Rather than existing in isolation, they exhibit a rich correlational structure--some connected through logical dependencie…

cs.CL2025

A semantic embedding space based on large language models for modelling human beliefs

Byunghwee Lee, Rachith Aiyappa, Yong-Yeol Ahn +2

Beliefs form the foundation of human cognition and decision-making, guiding our actions and social connections. A model encapsulating beliefs and their interrelationships is crucia…