WebRISE: Requirement-Induced State Evaluation for MLLM-Generated Web Artifacts
Tsinghua University（清华大学）；Huawei Noah’s Ark Lab（华为诺亚实验室）；East China Normal University（华东师范大学）；Tongji University（同济大学）；Institute of Artificial Intelligence, Beihang University（北京航空航天大学人工智能研究院）
Existing benchmarks for MLLM-generated web artifacts assess interaction through local evidence and miss the requirement-induced states and transitions that determine whether a page works. We introduce WebRISE, which compiles task requirements into Interaction Contract Graphs (ICGs) of observable states, user-intent transitions, and DOM/visual assertions for implementation-agnostic browser execution. WebRISE spans 442 tasks across five input modalities (Text, Markdown, Sketch, Image, Video), with 5,495 transitions and 5,271 requirement checks that separate user-stated functions from implicit product-level constraints. Across 14 MLLMs, even the strongest model reaches only 65.6% transition validity and 66.3% requirement coverage, and visual quality is no proxy for behavior (Qwen3.6-35B-A3B on Markdown: V=80.8 yet T=15.5). Video gives the strongest interaction signal (+10.6 pp implicit coverage over Text), while implicit constraints persist; defect injection shows ICG-based scoring detects state errors at 2-16x the rate of checkpoint-style evaluation.
Deep Residual Injection for Full-Spectrum Forensic Signal Perception in Multimodal Large Language Models
National University of Singapore（新加坡国立大学）；Tsinghua University（清华大学）；University of Science and Technology of China（中国科学技术大学）；University of Electronic Science and Technology of China（电子科技大学）；University of California, Berkeley（加州大学伯克利分校）
Jury Duty: Calibration and Orientation Failures in MLLM-as-a-Judge Under Cultural Ambiguity
Salesforce AI Research（Salesforce AI 研究院）；University of Cambridge（剑桥大学）；University of Colorado Boulder（科罗拉多大学博尔德分校）；Carnegie Mellon University（卡内基梅隆大学）；UIUC（伊利诺伊大学厄巴纳-香槟分校）
Tsinghua University（清华大学）；BNRist；OPPO AI Center（OPPO人工智能中心）；Peking University（北京大学）；Hangzhou Zhuoxi Institute of Brain and Intelligence（杭州智行脑科学与人工智能研究所）
When Modalities Conflict: How Unimodal Reasoning Uncertainty Governs Preference Dynamics in MLLMs
Peking University（北京大学）；Provable Responsible AI and Data Analytics (PRADA) Lab（可证明负责任的人工智能和数据分析实验室）；King Abdullah University of Science and Technology（卡布斯大学）；South China University of Technology（华南理工大学）；Tsinghua University（清华大学）；University of Georgia（佐治亚大学）；MBZUAI（马克斯·普朗克人工智能研究所）
SpaceDG: Benchmarking Spatial Intelligence under Visual Degradation
Shanghai Jiao Tong University（上海交通大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；University of Electronic Science and Technology of China（电子科技大学）；Chongqing University（重庆大学）；The University of Tokyo（东京大学）；Beihang University（北航）；Northwestern Polytechnical University（西北工业大学）
From Mirage to Grounding: Towards Reliable Multimodal Circuit-to-Verilog Code Generation
State Key Laboratory of Blockchain and Data Security, Zhejiang University（区块链与数据安全国家重点实验室，浙江大学）；Hangzhou High-Tech Zone (Binjiang) Institute of Blockchain and Data Security, Hangzhou（杭州高新技术区（滨江）区块链与数据安全研究院，杭州）；School of Artificial Intelligence and Computer Science, Nantong University（人工智能与计算机科学学院，南通大学）
Reinforcing Multimodal Reasoning Against Visual Degradation
Tencent Hunyuan（腾讯文言）；University of Maryland, College Park（马里兰大学 College Park 分校）；University of Virginia（弗吉尼亚大学）；University of North Carolina, Chapel Hill（北卡罗来纳大学 Chapel Hill 分校）
