20 citations · 30 across the 22 of their papers we have counts for
5 papers · 1 filter
MM-ReCoder: Advancing Chart-to-Code Generation with Reinforcement Learning and Self-Correction
Zitian Tang, Xu Zhang, Jianbo Yuan +4
Multimodal Large Language Models (MLLMs) have recently demonstrated promising capabilities in multimodal coding tasks such as chart-to-code generation. However, existing methods pr…
Model Merging Scaling Laws in Large Language Models
Yuanyi Wang, Yanggan Gu, Yiming Zhang +6
We study empirical scaling laws for language model merging measured by cross-entropy. Despite its wide practical use, merging lacks a quantitative rule that predicts returns as we…
InfiGUI-G1: Advancing GUI Grounding with Adaptive Exploration Policy Optimization
Yuhang Liu, Zeyu Liu, Shuanghe Zhu +10
The emergence of Multimodal Large Language Models (MLLMs) has propelled the development of autonomous agents that operate on Graphical User Interfaces (GUIs) using pure visual inpu…
Infi-MMR: Curriculum-based Unlocking Multimodal Reasoning via Phased Reinforcement Learning in Multimodal Small Language Models
Zeyu Liu, Yuhang Liu, Guanghao Zhu +9
Recent advancements in large language models (LLMs) have demonstrated substantial progress in reasoning capabilities, such as DeepSeek-R1, which leverages rule-based reinforcement…
BabelBench: An Omni Benchmark for Code-Driven Analysis of Multimodal and Multistructured Data
Xuwu Wang, Qiwen Cui, Yunzhe Tao +16
Large language models (LLMs) have become increasingly pivotal across various domains, especially in handling complex data types. This includes structured data processing, as exempl…