Parents need to know that Transformers: Revenge of the Fallen is the sequel to 2007's Transformers. It's edgier and less kid-friendly than the first. Kids will want to see it because they're the ones who play with the toys the movie was inspired by, but it's packed with metal-on-metal mayhem and brutally violent action scenes that are too much for them. While most of the combatants are giant robots, the film's human characters are in constant peril, and the explosions never seem to stop. There are also eyebrow-raising amounts of sexualized and even racially insensitive material, as well as strong language (including one use of "f--k" and frequent uses of words like "bitch" and "p---y"). Plus, it's essentially a long commercial for both cars and toys.
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The faults of the first Transformers movie are even worse here. Director Michael Bay brings in robot after robot after robot, making it impossible to tell the metal mega-warriors apart and resulting in action scenes where who's doing what to who is conveyed more by screaming bystanders than clear, comprehensible filmmaking. Whether you loved or hated the original Transformers, it made so much money that a sequel was inevitable. It was not, however, necessarily inevitable that said sequel would be good.
The human characters aren't much better -- the film bogs down in scenes where Sam's parents are concerned about him heading off to school, only to jettison all that in the name of globe-trotting action. The relationship between Sam and girlfriend Mikaela (Megan Fox) is laughably thin, and the film's need to overdo everything results in either misshapen comic relief scenes or action scenes so loud and large and quickly cut that they're simply empty blurs. Transformers: Revenge of the Fallen is, at heart, the worst of everything that modern big-money moviemaking has to offer -- spectacle, sex, special effects, and sanitized violence -- without a single redeeming feature.
You can also bring up the movie's stereotyping -- including the robot "Twins," one of whom has a gold tooth and later explains that he can't decipher hieroglyphics because "We don't do much readin'." Are those kinds of caricatures funny or offensive? Why?
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A deep learning model called Transformer uses the self-attention process. This framework is utilized by numerous researchers for extractive summarization jobs. The researchers of [35] focused on the structured transformers HiBERT presented by [36] and Extended Transformers presented by [37], which offer an extractive encoder-centric stepwise strategy for summarizing documents. This model enabled stepwise summarization by inserting the previously created summary as an additional substructure into the structured Transformer. The authors in [38] presented an extractive summarization model based on layered trees, where the given document's discourse and syntactic trees are combined to form nested tree structures. The authors primarily focused on the existing model RoBERTa presented by [39] for constructing this model. By lowering the size of the attention module, the authors in [40] presented an extractive summarization technique for discourse-based attention at the document level; this constitutes the core of the transformer architecture, utilizing a unique discourse-inspired approach. Two different transformer-based techniques for sentiment analysis were provided by the authors in [41] while fetching the words that are crucial to the model's decision-making to produce a summary as the output explanation. To generate unsupervised extractive summaries, the researchers of [42] used a transformer attention mechanism to prioritize sentences. For extractive summarization of long text, the authors of [43] used the transformer model and introduced a type of heterogeneous framework called HETFORMER framework. BERT is a pretrained model used by many researchers for extractive summarization. The summarized literature review is depicted in Table 1. 2ff7e9595c
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