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cs.LG2026
ReGRA: Residual-Gradient Adaptation for Complementary Low-Rank Fine-Tuning
Fanyao Li, Yuxi Liu, Xiaohao Liu +3
Low-rank adaptation (LoRA) enables parameter-efficient fine-tuning by learning low-rank weight updates. Increasing rank expands adaptation capacity, but does not guarantee that all…
cs.IR2026
Scattered Hypothesis Generation for Open-Ended Event Forecasting
He Chang, Zhulin Tao, Lifang Yang +2
Despite the importance of open-ended event forecasting for risk management, current LLM-based methods predominantly target only the most probable outcomes, neglecting the intrinsic…