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cs.LG2026
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…
cs.LG2025
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…