Obedient Videos with Ai Need a sequence of photos correctly. The biggest challenge in AI models are based on video to process videos such as continuous flow, important information and distracting proceeding. This shortage of temporary smile prevents reform changes; Therefore, events and collaboration is not partially known. Tall videos that are also making a process difficult, at high cost of integration and requires strategies such as framework, losing important information and reduces accuracy. Through the data within the frames also do not oppress well, resulting in reducing and reducing resources.
Currently, video language models carry videos such as a sequence of frameworks The Encaders of Pictures including Language view projectshard to represent movement and continuity. Language models have temporary problems independently, resulting in partial understanding. The SuchMost of independent reduces the Computational burden on the cost of deleting useful information, which affects accuracy. Ways to reduce tokens as a Recension KV Cache Copression and Selection Advanced Video Acciders and Making Helps, are always unemployment, processing the longest video processing.
Dealing with these challenges, researchers from The envid, Rutger University, C Berkeley, Conceive, Nanjing Universitybeside Kind decreased Storm (SpatoryManding Token Reduction of Multimodal LLTIMONDAL), The construction of the project-based project Maqa through effective long-video videos. Unlike traditional ways, where temporary relationship is separated separately from each of the video structure, language models used by entering temporary relations. Storm Addsitional temporary information at the levels of video Tokens to complete the development and improve efficiency. The model is upgrading video submissions with a biitirection of a barning mechanism while promoting a temporary consultation load from the LLM.
Framework is used Mbamba's layers Developing temporary models, including a biitirectional scanning module depending on all local and provocative forms. This page Temporary Agreement Implementation and unique installation, acting as a local photographer to integrate local context and the SPIATOTMATIONAL DYNAMSCS TIME. During training, strategies to optimize tokens develop computational efficiency while storing important information, which allows for one toe Kind. Token SuctionThe-Free Training-Free Sucker Closed the test time to reduce the computitional loads according to the maintenance of important temporary information. This method has worked well to process long videos without requiring special equipment or intimacy.
Tests are made to check Storm a video of video understanding. Training is done using the previous use Hack Models, with temporary profusktha presented with random initialization. The process involved two Categories: Alignment classwhere the image Ecoder was named Ecoder and the LLM while temporary project trained using pairs of text, and a The best member of goodness (Soup) A variety of 12.5 million dataset, including text, text-text and video text data. Methods of Press tokens, including temporary and local Pooling, reduced computational load. The last model was examined in the tall benches of video EgoSchema, MVBANCH, Mlvu, LongVideoobinchbeside VideileMeby working as compared to other video llms.
At the test, expiry models are successful, reaching the results of the benches of the benches. Mondlon of Mambulon has developed efficiency by oppressing visual tokens while keeping important information, reducing the meeting time until the 65.5%. The temporary pooling is used in the tall videos, doing good working with a few tokens. The storm is also made more better than found Kind The model, especially in activities involved in understanding the context of the world. The results confirmed the importance of the Token Comtresses, with the increased operation and video length from 8 above 128 frames.
In short, the proposed storm model promoted a remote video understanding using a temporary encoder based on Mbaba and efficient token. Enabled a strong stress without losing the official temporary information, recording weather performance from the long-distance bakes while keeping integrated is low. The path may serve as a basis for future research, simplify the establishment of the Token Commental, MultiModal alignment, and the actual land shipping to enhance video language and efficiency.
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