1 citations · 1 across the 12 of their papers we have counts for
14 papers
CRC-Router: Risk-Constrained Routing for Medical Agentic AI Systems
Xueyang Li, Mingze Jiang, Gelei Xu +5
Agentic AI systems are increasingly being explored in medical imaging to improve throughput and reduce clinician workload; however, safe deployment remains challenging because auto…
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…
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
Nobin Sarwar, Shubhashis Roy Dipta, Zheyuan Liu +1
With the growing adoption of VLMs, DMs, LLMs, and AFMs, these multimodal foundation models can inadvertently encode sensitive, copyrighted, biased, or unsafe cross-modal associatio…
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…
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…
Leopard: A Vision Language Model For Text-Rich Multi-Image Tasks
Mengzhao Jia, Wenhao Yu, Kaixin Ma +6
Text-rich images, where text serves as the central visual element guiding the overall understanding, are prevalent in real-world applications, such as presentation slides, scanned…
Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning
Zhihan Zhang, Tao Ge, Zhenwen Liang +5
Supervised fine-tuning enhances the problem-solving abilities of language models across various mathematical reasoning tasks. To maximize such benefits, existing research focuses o…
Describe-then-Reason: Improving Multimodal Mathematical Reasoning through Visual Comprehension Training
Mengzhao Jia, Zhihan Zhang, Wenhao Yu +2
Open-source multimodal large language models (MLLMs) excel in various tasks involving textual and visual inputs but still struggle with complex multimodal mathematical reasoning, l…
PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning
Zhihan Zhang, Dong-Ho Lee, Yuwei Fang +4
Instruction tuning has remarkably advanced large language models (LLMs) in understanding and responding to diverse human instructions. Despite the success in high-resource language…