7 papers
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…
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…
AT-CXR: Uncertainty-Aware Agentic Triage for Chest X-rays
Xueyang Li, Mingze Jiang, Gelei Xu +4
Agentic AI is advancing rapidly, yet truly autonomous medical-imaging triage, where a system decides when to stop, escalate, or defer under real constraints, remains relatively und…
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…
RepoGraph: Enhancing AI Software Engineering with Repository-level Code Graph
Siru Ouyang, Wenhao Yu, Kaixin Ma +6
Large Language Models (LLMs) excel in code generation yet struggle with modern AI software engineering tasks. Unlike traditional function-level or file-level coding tasks, AI softw…
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…