2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.CL2025
FinLMM-R1: Enhancing Financial Reasoning in LMM through Scalable Data and Reward Design
Kai Lan, Jiayong Zhu, Jiangtong Li +3
Large Multimodal Models (LMMs) demonstrate significant cross-modal reasoning capabilities. However, financial applications face challenges due to the lack of high-quality multimoda…
cs.CV2024★ 2 cited
Pensieve: Retrospect-then-Compare Mitigates Visual Hallucination
Dingchen Yang, Bowen Cao, Guang Chen +1
Multi-modal Large Language Models (MLLMs) demonstrate remarkable success across various vision-language tasks. However, they suffer from visual hallucination, where the generated r…
cs.LG2023
Spreeze: High-Throughput Parallel Reinforcement Learning Framework
Jing Hou, Guang Chen, Ruiqi Zhang +3
The promotion of large-scale applications of reinforcement learning (RL) requires efficient training computation. While existing parallel RL frameworks encompass a variety of RL al…