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Compositional Learning Journal Club at RIML Lab 🔥

We are pleased to announce the establishment of a new research group within RIML Lab, dedicated to the study and advancement of Compositional Learning.

Compositional learning is inspired by the inherent human ability to comprehend and generate complex ideas from simpler concepts. By enabling the recombination of learned components, compositional learning enhances a machine's ability to generalize to out-of-distribution samples encountered in real-world scenarios. This characteristic has spurred vibrant research in areas such as object-centric learning, compositional generalization, and compositional reasoning, with wide-ranging applications across various tasks, including controllable text generation, factual knowledge reasoning, image captioning, text-to-image generation, visual reasoning, speech processing, and reinforcement learning.

To promote collaboration and the exchange of knowledge, we are launching a weekly Journal Club. These sessions will be held every Sunday from 3:30 PM to 5:00 PM, where we will engage in discussions on the latest research papers and significant advancements in Compositional Learning.

For updates and additional information, please visit our blog: complearnjc.github.io.

For in-person communication, you may contact us via Telegram at @amirkasaei and @arashmarioriyad.

We look forward to your participation.



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Compositional Learning Journal Club at RIML Lab 🔥

We are pleased to announce the establishment of a new research group within RIML Lab, dedicated to the study and advancement of Compositional Learning.

Compositional learning is inspired by the inherent human ability to comprehend and generate complex ideas from simpler concepts. By enabling the recombination of learned components, compositional learning enhances a machine's ability to generalize to out-of-distribution samples encountered in real-world scenarios. This characteristic has spurred vibrant research in areas such as object-centric learning, compositional generalization, and compositional reasoning, with wide-ranging applications across various tasks, including controllable text generation, factual knowledge reasoning, image captioning, text-to-image generation, visual reasoning, speech processing, and reinforcement learning.

To promote collaboration and the exchange of knowledge, we are launching a weekly Journal Club. These sessions will be held every Sunday from 3:30 PM to 5:00 PM, where we will engage in discussions on the latest research papers and significant advancements in Compositional Learning.

For updates and additional information, please visit our blog: complearnjc.github.io.

For in-person communication, you may contact us via Telegram at @amirkasaei and @arashmarioriyad.

We look forward to your participation.

BY RIML Lab


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Telegram and Signal Havens for Right-Wing Extremists

Since the violent storming of Capitol Hill and subsequent ban of former U.S. President Donald Trump from Facebook and Twitter, the removal of Parler from Amazon’s servers, and the de-platforming of incendiary right-wing content, messaging services Telegram and Signal have seen a deluge of new users. In January alone, Telegram reported 90 million new accounts. Its founder, Pavel Durov, described this as “the largest digital migration in human history.” Signal reportedly doubled its user base to 40 million people and became the most downloaded app in 70 countries. The two services rely on encryption to protect the privacy of user communication, which has made them popular with protesters seeking to conceal their identities against repressive governments in places like Belarus, Hong Kong, and Iran. But the same encryption technology has also made them a favored communication tool for criminals and terrorist groups, including al Qaeda and the Islamic State.

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