9 papers · 1 filter
Agent as Policy for Robotic Manipulation
Mengzhao Jia, Yang Lin, Xixin Zhang +3
We demonstrate that a general-purpose agent can directly drive a physical robot throughout task execution without any task-specific or environment-specific training. We introduce A…
Prioritizing the Best: Incentivizing Reliable Multimodal Reasoning by Rewarding Beyond Answer Correctness
Mengzhao Jia, Zhihan Zhang, Meng Jiang
Reinforcement Learning with Verifiable Rewards (RLVR) improves multimodal reasoning by rewarding verifiable final answers. Yet answer-correct trajectories may still rely on incompl…
MMTutorBench: The First Multimodal Benchmark for AI Math Tutoring
Tengchao Yang, Sichen Guo, Mengzhao Jia +4
Effective math tutoring requires not only solving problems but also diagnosing students' difficulties and guiding them step by step. While multimodal large language models (MLLMs)…
AutoRubric: Rubric-Based Generative Rewards for Faithful Multimodal Reasoning
Mengzhao Jia, Zhihan Zhang, Ignacio Cases +3
Multimodal large language models (MLLMs) have rapidly advanced from perception tasks to complex multi-step reasoning, yet reinforcement learning with verifiable rewards (RLVR) ofte…
Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench
Zheyuan Liu, Guangyao Dou, Mengzhao Jia +4
Generative models such as Large Language Models (LLM) and Multimodal Large Language models (MLLMs) trained on massive web corpora can memorize and disclose individuals' confidentia…
MultiChartQA: Benchmarking Vision-Language Models on Multi-Chart Problems
Zifeng Zhu, Mengzhao Jia, Zhihan Zhang +2
Multimodal Large Language Models (MLLMs) have demonstrated impressive abilities across various tasks, including visual question answering and chart comprehension, yet existing benc…