most citedNumerical Pruning for Efficient Autoregressive Models

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

collaborators

5 papers

cs.AI2025

Skill Discovery for Software Scripting Automation via Offline Simulations with LLMs

Paiheng Xu, Gang Wu, Xiang Chen +6

Scripting interfaces enable users to automate tasks and customize software workflows, but creating scripts traditionally requires programming expertise and familiarity with specifi…

cs.CL2025

Exploring Rewriting Approaches for Different Conversational Tasks

Md Mehrab Tanjim, Ryan A. Rossi, Mike Rimer +9

Conversational assistants often require a question rewriting algorithm that leverages a subset of past interactions to provide a more meaningful (accurate) answer to the user's que…

cs.LG20241 cited

Numerical Pruning for Efficient Autoregressive Models

Xuan Shen, Zhao Song, Yufa Zhou +12

Transformers have emerged as the leading architecture in deep learning, proving to be versatile and highly effective across diverse domains beyond language and image processing. Ho…

cs.HC2024

Optimizing Data Delivery: Insights from User Preferences on Visuals, Tables, and Text

Reuben Luera, Ryan Rossi, Franck Dernoncourt +9

In this work, we research user preferences to see a chart, table, or text given a question asked by the user. This enables us to understand when it is best to show a chart, table,…

cs.CL2024

A Multi-LLM Debiasing Framework

Deonna M. Owens, Ryan A. Rossi, Sungchul Kim +7

Large Language Models (LLMs) are powerful tools with the potential to benefit society immensely, yet, they have demonstrated biases that perpetuate societal inequalities. Despite s…