activity
20232026
collaborators

5 papers

cs.LG2026

EMO: Frustratingly Easy Progressive Training of Extendable MoE

Linghao Jin, Chufan Shi, Huijuan Wang +4

Sparse Mixture-of-Experts (MoE) models offer a powerful way to scale model size without increasing compute, as per-token FLOPs depend only on k active experts rather than the total…

cs.CL2026

Modeling Community Attitude through Reaction Tone: A Human-AI Collaborative Framework for Evaluating LLM Alignment with Linguistic Behaviors in Online Communities

Nuan Wen, Xuezhe Ma

Large language models (LLMs) are increasingly utilized as proxies for computational social analysis; yet, their ability to faithfully represent the "thick descriptions" (Geertz, 19…

cs.CL2024

Secret Keepers: The Impact of LLMs on Linguistic Markers of Personal Traits

Zhivar Sourati, Meltem Ozcan, Colin McDaniel +5

Prior research has established associations between individuals' language usage and their personal traits; our linguistic patterns reveal information about our personalities, emoti…

cs.CL2023

Can Language Model Moderators Improve the Health of Online Discourse?

Hyundong Cho, Shuai Liu, Taiwei Shi +8

Conversational moderation of online communities is crucial to maintaining civility for a constructive environment, but it is challenging to scale and harmful to moderators. The inc…

cs.SI2023

MIDDAG: Where Does Our News Go? Investigating Information Diffusion via Community-Level Information Pathways

Mingyu Derek Ma, Alexander K. Taylor, Nuan Wen +9

We present MIDDAG, an intuitive, interactive system that visualizes the information propagation paths on social media triggered by COVID-19-related news articles accompanied by com…