Update Tracking Figure

Author: NipElement

index.html

@@ -49,6 +49,9 @@
               <a class="navbar-item" href="https://huggingface.co/datasets/MMMU/MMMU_Pro">
                 <b>MMMU-Pro</b> <span style="font-size:18px; display: inline; margin-left: 5px;">🔥</span>
               </a>
+              <a class="navbar-item" href="https://videommmu.github.io/">
+                <b>Video-MMMU</b> <span style="font-size:18px; display: inline; margin-left: 5px;">🔥</span>
+              </a>
               <a class="navbar-item" href="https://tiger-ai-lab.github.io/MAmmoTH/">
                 MAmmoTH
               </a>
@@ -238,6 +241,8 @@ <h2 class="title is-3">Introduction</h2>
               <p>
                 We introduce MMMU: a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning. MMMU includes <b>11.5K</b> meticulously collected multimodal questions from college exams, quizzes, and textbooks, covering six core disciplines: Art & Design, Business, Science, Health & Medicine, Humanities & Social Science, and Tech & Engineering. These questions span <b>30</b> subjects and <b>183</b> subfields, comprising 30 highly heterogeneous image types, such as charts, diagrams, maps, tables, music sheets, and chemical structures. Unlike existing benchmarks, MMMU focuses on advanced perception and reasoning with domain-specific knowledge, challenging models to perform tasks akin to those faced by experts. Our evaluation of 14 open-source LMMs and the proprietary GPT-4V(ision) highlights the substantial challenges posed by MMMU. Even the advanced GPT-4V only achieves a 56% accuracy, indicating significant room for improvement. We believe MMMU will stimulate the community to build next-generation multimodal foundation models towards expert artificial general intelligence.
               </p>
+              <img src="static/images/MMMU_Tracking_Figure.png" alt="algebraic reasoning" width="100%">
+              <br>
             </div>
           </div>
         </div>