most citedFinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

cs.CL2026

Complementary Roles of Activation and Parametric Memory in Few-Shot Learning

Miaohe Niu, Runsong Zhao, Xinyu Liu +5

At test time, large language models (LLMs) can encode historical information in activation memory (i.e., KV caches) and parametric memory (i.e., updated parameters). While activati…

cs.AI2026

MemoSight: Unifying Context Compression and Multi Token Prediction for Reasoning Acceleration

Xinyu Liu, Xin Liu, Bo Jin +8

While chain-of-thought (CoT) reasoning enables LLMs to solve challenging reasoning tasks, the linear growth of the KV cache leads to substantial memory and inference overhead. Exis…

cs.LG2025★ 2 cited

FinLoRA: Finetuning Quantized Financial Large Language Models Using Low-Rank Adaptation

Dannong Wang, Daniel Kim, Bo Jin +4

Finetuned large language models (LLMs) have shown remarkable performance in financial tasks, such as sentiment analysis and information retrieval. Due to privacy concerns, finetuni…