3 citations · 5 across the 7 of their papers we have counts for
7 papers
RW-TTT: Batched Serving for Request-Owned Test-Time Training State
Jian Yang, Zhizhuo Kou, Yao Tian +4
Test-time training (TTT) adapts an LLM during generation by reading and updating request-owned state, such as fast weights, low-rank deltas, or streaming learner state. This breaks…
MMFCTUB: Multi-Modal Financial Credit Table Understanding Benchmark
Cui Yakun, Yanting Zhang, Zhu Lei +5
The advent of multi-modal language models (MLLMs) has spurred research into their application across various table understanding tasks. However, their performance in credit table u…
Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation
Junyu Luo, Yuhao Tang, Yiwei Fu +6
Unsupervised Graph Domain Adaptation (UGDA) leverages labeled source domain graphs to achieve effective performance in unlabeled target domains despite distribution shifts. However…
Surgery-R1: Advancing Surgical-VQLA with Reasoning Multimodal Large Language Model via Reinforcement Learning
Pengfei Hao, Shuaibo Li, Hongqiu Wang +4
In recent years, significant progress has been made in the field of surgical scene understanding, particularly in the task of Visual Question Localized-Answering in robotic surgery…
FinMME: Benchmark Dataset for Financial Multi-Modal Reasoning Evaluation
Junyu Luo, Zhizhuo Kou, Liming Yang +10
Multimodal Large Language Models (MLLMs) have experienced rapid development in recent years. However, in the financial domain, there is a notable lack of effective and specialized…
Automate Strategy Finding with LLM in Quant Investment
Zhizhuo Kou, Holam Yu, Junyu Luo +7
We present a novel three-stage framework leveraging Large Language Models (LLMs) within a risk-aware multi-agent system for automate strategy finding in quantitative finance. Our a…