4 papers
Weightless Fine-Tuning: Personalizing LLMs via Logit-Space Transport
Bohan Zhang, Anqi Ni, Yixin Wang +1
Supervised fine-tuning (SFT) is a standard approach for adapting LLMs to a target distribution, but in settings such as personalization, where each author requires separate weight…
Who Owns the Text? Design Patterns for Preserving Authorship in AI-Assisted Writing
Bohan Zhang, Chengke Bu, Paramveer S. Dhillon
AI writing assistants can reduce effort and improve fluency, but they may also weaken writers' sense of authorship. We study this tension with an ownership-aware co-writing editor…
ExAnte: A Benchmark for Ex-Ante Inference in Large Language Models
Yachuan Liu, Xiaochun Wei, Lin Shi +4
Large language models (LLMs) face significant challenges in ex-ante reasoning, where analysis, inference, or predictions must be made without access to information from future even…
Policy Learning with a Natural Language Action Space: A Causal Approach
Bohan Zhang, Yixin Wang, Paramveer S. Dhillon
This paper introduces a novel causal framework for multi-stage decision-making in natural language action spaces where outcomes are only observed after a sequence of actions. While…