Just links

@j_links

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Welcome to the informative world of the Telegram channel Just links, a dedicated space for those who seek a curated collection of engaging and thought-provoking links. With over 6,300 subscribers, this channel serves as an aggregator of content that the creator finds particularly interesting, especially in the realms of deep learning (DL) and topological condensed matter physics.

The channel’s description succinctly captures its essence: "That's just link aggregator of everything I consider interesting, especially DL and topological condensed matter physics." This simple yet effective statement sets the tone for what subscribers can expect. Each post brings forth valuable resources, research papers, and discussions that cater to enthusiasts in these specialized fields.

Recent messages in the channel showcase the type of content that is regularly shared. For instance, one of the latest messages highlighted a resource titled CombiBench: Benchmarking LLM Capability for Combinatorial Mathematics, which invites subscribers to explore benchmarking techniques in the context of large language models (LLMs). This topic is particularly relevant in today’s rapidly evolving AI landscape, where evaluating the capabilities of such models is crucial.

Another recent post featured SycEval: Evaluating LLM Sycophancy, a paper that dives deep into the evaluation of LLMs in social contexts. This kind of content not only keeps subscribers informed about the latest research but also encourages critical thinking about the implications of AI in society.

The channel also offers insights into advanced topics, such as Short remarks on shallow unitary circuits, which discusses theoretical aspects of quantum computing that are increasingly relevant in various technological advancements. Such discussions are indispensable for anyone looking to stay ahead in the field of physics and technology.

Moreover, the channel addresses practical applications of research with links like Science-T2I: Addressing Scientific Illusions in Image Synthesis. This entry reflects the interdisciplinary nature of modern scientific inquiry, bridging gaps between physics, computer science, and visualization techniques.

By aggregating links to research papers, articles, and discussions, Just links stands out as a valuable resource for both students and professionals interested in deep learning and condensed matter physics. The channel not only provides access to information but also fosters a community of like-minded individuals who share a passion for these topics.

In addition to the academic and technical content, the channel's format allows for a seamless experience in discovering new information. Each link is accompanied by a brief description, making it easier for subscribers to gauge the relevance and significance of the content before diving deeper.

For anyone looking to enrich their understanding of deep learning and topological condensed matter physics, subscribing to Just links is a step in the right direction. With its commitment to sharing only the most interesting and relevant links, this channel is a must-follow for anyone eager to stay updated on the latest developments in these dynamic fields.