activity
20242026
most citedSteering Large Language Models with Register Analysis for Arbitrary Style Transfer

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

collaborators

5 papers

cs.CL2026

Can You Make It Sound Like You? Post-Editing LLM-Generated Text for Personal Style

Connor Baumler, Calvin Bao, Huy Nghiem +3

Despite the growing use of large language models (LLMs) for writing tasks, users may hesitate to rely on LLMs when personal style is important. Post-editing LLM-generated drafts or…

cs.DS2025

An Exact Algorithm for the Unanimous Vote Problem

Feyza Duman Keles, Lisa Hellerstein, Kunal Marwaha +2

Consider independent, biased coins, each with a known probability of heads. Presented with an ordering of these coins, flip (i.e., toss) each coin once, in that order, until we…

cs.CL20251 cited

Steering Large Language Models with Register Analysis for Arbitrary Style Transfer

Xinchen Yang, Marine Carpuat

Large Language Models (LLMs) have demonstrated strong capabilities in rewriting text across various styles. However, effectively leveraging this ability for example-based arbitrary…

cs.CL2025

Token-level Ensembling of Models with Different Vocabularies

Rachel Wicks, Kartik Ravisankar, Xinchen Yang +2

Model ensembling is a technique to combine the predicted distributions of two or more models, often leading to improved robustness and performance. For ensembling in text generatio…

cs.AI2024

Syllabus: Portable Curricula for Reinforcement Learning Agents

Ryan Sullivan, Ryan Pégoud, Ameen Ur Rehman +5

Curriculum learning has been a quiet, yet crucial component of many high-profile successes of reinforcement learning. Despite this, it is still a niche topic that is not directly s…