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     <!-- <ol class="bibliography"><li> <div class="row"> <div class="col-sm-2 abbr"><abbr class="badge"><a href="https://journals.aps.org/" rel="external nofollow noopener" target="_blank">PhysRev</a></abbr></div> <div id="PhysRev.47.777" class="col-sm-8"> <div class="title">Can Quantum-Mechanical Description of Physical Reality Be Considered Complete?</div> <div class="author"> <em>A. Einstein</em>, <a href="https://en.wikipedia.org/wiki/Boris_Podolsky" rel="external nofollow noopener" target="_blank">B. Podolsky</a>, and <a href="https://en.wikipedia.org/wiki/Nathan_Rosen" rel="external nofollow noopener" target="_blank">N. Rosen</a> </div> <div class="periodical"> <em>Phys. Rev.</em>, May 1935 </div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> <a href="https://journals.aps.org/pr/abstract/10.1103/PhysRev.47.777" class="btn btn-sm z-depth-0" role="button" rel="external nofollow noopener" target="_blank">HTML</a> <a href="/assets/pdf/example_pdf.pdf" class="btn btn-sm z-depth-0" role="button">PDF</a> </div> <div class="badges"> <span class="altmetric-embed" data-hide-no-mentions="true" data-hide-less-than="15" data-badge-type="2" data-badge-popover="right" data-doi="10.1103/PhysRev.47.777"></span> <span class="__dimensions_badge_embed__" data-doi="10.1103/PhysRev.47.777" data-hide-zero-citations="true" data-style="small_rectangle" data-legend="hover-right" style="margin-bottom: 3px;"></span> </div> <div class="abstract hidden"> <p>In a complete theory there is an element corresponding to each element of reality. A sufficient condition for the reality of a physical quantity is the possibility of predicting it with certainty, without disturbing the system. In quantum mechanics in the case of two physical quantities described by non-commuting operators, the knowledge of one precludes the knowledge of the other. Then either (1) the description of reality given by the wave function in quantum mechanics is not complete or (2) these two quantities cannot have simultaneous reality. Consideration of the problem of making predictions concerning a system on the basis of measurements made on another system that had previously interacted with it leads to the result that if (1) is false then (2) is also false. One is thus led to conclude that the description of reality as given by a wave function is not complete.</p> </div> </div> </div> </li></ol> -->
 
 
-Junlin Fang, Wenya Wang, Tianze Luo, Yanyong Huang, Fengmao Lv. In ACM International Conference on Information and Knowledge Management (CIKM-24). Boise, Idaho, USA. October 21-25, 2024
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     <ol class="bibliography"><li> <div class="row"> <div class="col-sm-2 abbr"><abbr class="badge"><a href="" rel="external nofollow noopener" target="_blank">arXiv</a></abbr></div> <div id="PhysRev.47.777" class="col-sm-8"> <div class="title">From Seconds to Hours: Reviewing MultiModal Large Language Models on Comprehensive Long Video Understanding</div> <div class="author"> Heqing Zou*, <em>Tianze Luo*</em>, Guiyang Xie, Victor (Xiao Jie)Zhang, Fengmao Lv, Guangcong Wang, Juanyang Chen, Zhuochen Wang, Hansheng Zhang, Huaijian Zhang  </div> <div class="periodical"> <em> arXiv preprint </em>, 2024</div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> <a href="https://arxiv.org/abs/2409.18938" class="btn btn-sm z-depth-0" role="button">PDF</a> </div> <div class="badges">  </div> <div class="abstract hidden"> <p>The integration of Large Language Models (LLMs) with visual encoders has recently shown promising performance in visual understanding tasks, leveraging their inherent capability to comprehend and generate human-like text for visual reasoning. Given the diverse nature of visual data, MultiModal Large Language Models (MM-LLMs) exhibit variations in model designing and training for understanding images, short videos, and long videos. Our paper focuses on the substantial differences and unique challenges posed by long video understanding compared to static image and short video understanding. Unlike static images, short videos encompass sequential frames with both spatial and within-event temporal information, while long videos consist of multiple events with between-event and long-term temporal information. In this survey, we aim to trace and summarize the advancements of MM-LLMs from image understanding to long video understanding. We review the differences among various visual understanding tasks and highlight the challenges in long video understanding, including more fine-grained spatiotemporal details, dynamic events, and long-term dependencies. We then provide a detailed summary of the advancements in MM-LLMs in terms of model design and training methodologies for understanding long videos. Finally, we compare the performance of existing MM-LLMs on video understanding benchmarks of various lengths and discuss potential future directions for MM-LLMs in long video understanding.</p> </div> </div> </div> </li></ol>
 
         <ol class="bibliography"><li> <div class="row"> <div class="col-sm-2 abbr"><abbr class="badge"><a href="" rel="external nofollow noopener" target="_blank">CIKM</a></abbr></div> <div id="PhysRev.47.777" class="col-sm-8"> <div class="title">Progressive multimodal pivot learning: towards semantic discordance understanding as humans</div> <div class="author"> Junlin Fang, Wenya Wang, <em>Tianze Luo</em>, Yanyong Huang, Fengmao Lv  </div> <div class="periodical"> <em>In ACM International Conference on Information and Knowledge Management (CIKM-24) </em>, 2024</div> <div class="periodical"> </div> <div class="links"> <a class="abstract btn btn-sm z-depth-0" role="button">Abs</a> <a href="" class="btn btn-sm z-depth-0" role="button">PDF</a> </div> <div class="badges">  </div> <div class="abstract hidden"> <p></p> </div> </div> </div> </li></ol>