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<rdf:RDF xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:taxo="http://purl.org/rss/1.0/modules/taxonomy/" xmlns="http://purl.org/rss/1.0/" xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#"><channel rdf:about="https://www.bibsonomy.org/tag/model"><title>BibSonomy bookmarks for /tag/model</title><link>https://www.bibsonomy.org/tag/model</link><description>BibSonomy RSS Feed for /tag/model</description><items><rdf:Seq><rdf:li rdf:resource="https://dinosaurpictures.org/ancient-earth#750"/><rdf:li rdf:resource="https://easysubscription.io/glossary/subscription-business-model/?utm_source=blogsubmission&amp;utm_medium=ss&amp;utm_campaign=organic"/><rdf:li rdf:resource="https://aws.amazon.com/de/blogs/machine-learning/an-introduction-to-preparing-your-own-dataset-for-llm-training/"/><rdf:li rdf:resource="https://tensorwave.com/blog/how-to-train-an-llm-on-your-own-data"/><rdf:li rdf:resource="https://github.com/assafelovic/gpt-researcher"/><rdf:li rdf:resource="https://link.springer.com/chapter/10.1007/978-3-032-02003-1_3"/><rdf:li rdf:resource="https://www.sciencedirect.com/science/article/pii/S0952197624000587"/><rdf:li rdf:resource="https://gist.github.com/mgbckr/13fe59473a9135dd11d03cc5650932e0"/><rdf:li rdf:resource="https://bitnine.net/relational-database/data-modeling-rdb/"/><rdf:li rdf:resource="https://vertabelo.com/blog/data-modeling-techniques/"/><rdf:li rdf:resource="https://riseandbliss.com/personality-perspectives-shaping-identity-in-a-complex-world/"/><rdf:li rdf:resource="https://ollama.com/library"/><rdf:li rdf:resource="https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard"/><rdf:li rdf:resource="https://www.phind.com/blog/code-llama-beats-gpt4"/><rdf:li rdf:resource="https://www.cell.com/patterns/fulltext/S2666-3899(23)00239-8"/><rdf:li rdf:resource="https://acl2023-retrieval-lm.github.io/"/><rdf:li rdf:resource="https://news.ycombinator.com/item?id=37386397"/><rdf:li rdf:resource="https://platform.openai.com/docs/guides/embeddings/use-cases"/><rdf:li rdf:resource="https://8530121.fs1.hubspotusercontent-na1.net/hubfs/8530121/Website%20Relaunch%202022/Blogbeitr%C3%A4ge/DASC-PM_v1.1.pdf"/></rdf:Seq></items></channel><item rdf:about="https://dinosaurpictures.org/ancient-earth#750"><title>Ancient Earth globe. What did Earth look like MANY years ago?</title><description>visualization is created and maintained by Ian Webster. Plate tectonic and paleogeographic maps by C.R. Scotese, PALEOMAP Project. For more information visit: https://www.earthbyte.org/paleomap-paleoatlas-for-gplates &amp; www.globalgeology.com. Read more about the methods used here.

Some elements of this visualization are not adjusted for time (eg. cloud and star positions). The locations are accurate to ~100 km. The coloring of the maps is based on elevation and bathymetry: dark blue = deep water, light blue = shallow water; dark green, green, tan, brown, white = ground in increasing order of elevation. </description><link>https://dinosaurpictures.org/ancient-earth#750</link><dc:creator>panic</dc:creator><dc:date>2026-10-05T23:31:39+02:00</dc:date><dc:subject>Earth Information Map Model WEB tool(s) </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;visualization is created and maintained by Ian Webster. Plate tectonic and paleogeographic maps by C.R. Scotese, PALEOMAP Project. For more information visit: https://www.earthbyte.org/paleomap-paleoatlas-for-gplates &amp;amp; www.globalgeology.com. Read more about the methods used here.

Some elements of this visualization are not adjusted for time (eg. cloud and star positions). The locations are accurate to ~100 km. The coloring of the maps is based on elevation and bathymetry: dark blue = deep water, light blue = shallow water; dark green, green, tan, brown, white = ground in increasing order of elevation. &lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Earth"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Information"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Map"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/WEB"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tool(s)"/></rdf:Bag></taxo:topics></item><item rdf:about="https://easysubscription.io/glossary/subscription-business-model/?utm_source=blogsubmission&amp;utm_medium=ss&amp;utm_campaign=organic"><title>Subscription Model: The Smart Growth Strategy Every Modern Ecommerce Brand Needs</title><description>Discover how the subscription model helps businesses generate recurring revenue, improve customer loyalty, and scale faster with the right strategies and subscription solutions.</description><link>https://easysubscription.io/glossary/subscription-business-model/?utm_source=blogsubmission&amp;utm_medium=ss&amp;utm_campaign=organic</link><dc:creator>easyapp</dc:creator><dc:date>2026-08-06T13:02:02+02:00</dc:date><dc:subject>model subscription </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Discover how the subscription model helps businesses generate recurring revenue, improve customer loyalty, and scale faster with the right strategies and subscription solutions.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/subscription"/></rdf:Bag></taxo:topics></item><item rdf:about="https://aws.amazon.com/de/blogs/machine-learning/an-introduction-to-preparing-your-own-dataset-for-llm-training/"><title>An introduction to preparing your own dataset for LLM training | Artificial Intelligence</title><description></description><link>https://aws.amazon.com/de/blogs/machine-learning/an-introduction-to-preparing-your-own-dataset-for-llm-training/</link><dc:creator>brightbyte</dc:creator><dc:date>2026-05-11T15:39:53+02:00</dc:date><dc:subject>AI LL amazon model training </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2026-05-11T15:39:53+02:00&#034; href=&#034;https://aws.amazon.com/de/blogs/machine-learning/an-introduction-to-preparing-your-own-dataset-for-llm-training/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://aws.amazon.com/de/blogs/machine-learning/an-introduction-to-preparing-your-own-dataset-for-llm-training/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/AI"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/LL"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/amazon"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/training"/></rdf:Bag></taxo:topics></item><item rdf:about="https://tensorwave.com/blog/how-to-train-an-llm-on-your-own-data"><title>How to Train an LLM on Your Own Data for Personalized Models</title><description></description><link>https://tensorwave.com/blog/how-to-train-an-llm-on-your-own-data</link><dc:creator>brightbyte</dc:creator><dc:date>2026-05-11T15:38:59+02:00</dc:date><dc:subject>AI LLM blog model post train </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2026-05-11T15:38:59+02:00&#034; href=&#034;https://tensorwave.com/blog/how-to-train-an-llm-on-your-own-data&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://tensorwave.com/blog/how-to-train-an-llm-on-your-own-data&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/AI"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/LLM"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/blog"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/post"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/train"/></rdf:Bag></taxo:topics></item><item rdf:about="https://github.com/assafelovic/gpt-researcher"><title>GitHub - assafelovic/gpt-researcher: An autonomous agent that conducts deep research on any data using any LLM providers.</title><description>An autonomous agent that conducts deep research on any data using any LLM providers. - assafelovic/gpt-researcher</description><link>https://github.com/assafelovic/gpt-researcher</link><dc:creator>hotho</dc:creator><dc:date>2026-01-29T15:55:07+01:00</dc:date><dc:subject>deep gpt model open research source </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;An autonomous agent that conducts deep research on any data using any LLM providers. - assafelovic/gpt-researcher&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/deep"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/gpt"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/open"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/research"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/source"/></rdf:Bag></taxo:topics></item><item rdf:about="https://link.springer.com/chapter/10.1007/978-3-032-02003-1_3"><title>Collaborative Trustworthy Foundation Model Framework: An Environmental Sustainability Use-Case to Detect Contamination Objects in Organic Waste Streams</title><description></description><link>https://link.springer.com/chapter/10.1007/978-3-032-02003-1_3</link><dc:creator>scch</dc:creator><dc:date>2025-12-03T11:08:50+01:00</dc:date><dc:subject>Collaborative Foundation Framework Model Trustworthy </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2025-12-03T11:08:50+01:00&#034; href=&#034;https://link.springer.com/chapter/10.1007/978-3-032-02003-1_3&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://link.springer.com/chapter/10.1007/978-3-032-02003-1_3&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Collaborative"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Foundation"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Framework"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Trustworthy"/></rdf:Bag></taxo:topics></item><item rdf:about="https://www.sciencedirect.com/science/article/pii/S0952197624000587"><title>Variational Bayesian deep fuzzy models for interpretable classification</title><description></description><link>https://www.sciencedirect.com/science/article/pii/S0952197624000587</link><dc:creator>scch</dc:creator><dc:date>2024-12-17T09:44:22+01:00</dc:date><dc:subject>bayesian classification deep deep-learning fuzzy model variational </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2024-12-17T09:44:22+01:00&#034; href=&#034;https://www.sciencedirect.com/science/article/pii/S0952197624000587&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://www.sciencedirect.com/science/article/pii/S0952197624000587&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bayesian"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/classification"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/deep"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/deep-learning"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/fuzzy"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/variational"/></rdf:Bag></taxo:topics></item><item rdf:about="https://gist.github.com/mgbckr/13fe59473a9135dd11d03cc5650932e0"><title>Custom `cross_val` function for Pythons scikit-learn library. As opposed to scikit-learn&#039;s implementations, it returns predictions, split information, estimators.</title><description></description><link>https://gist.github.com/mgbckr/13fe59473a9135dd11d03cc5650932e0</link><dc:creator>becker</dc:creator><dc:date>2024-10-03T16:33:40+02:00</dc:date><dc:subject>cross_val cross_validate model python scikit-learn selection sklearn </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2024-10-03T16:33:40+02:00&#034; href=&#034;https://gist.github.com/mgbckr/13fe59473a9135dd11d03cc5650932e0&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://gist.github.com/mgbckr/13fe59473a9135dd11d03cc5650932e0&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cross_val"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cross_validate"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/python"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/scikit-learn"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/selection"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sklearn"/></rdf:Bag></taxo:topics></item><item rdf:about="https://bitnine.net/relational-database/data-modeling-rdb/"><title>What is Data Modeling? (Relational DB) | 비트나인</title><description></description><link>https://bitnine.net/relational-database/data-modeling-rdb/</link><dc:creator>bshanks</dc:creator><dc:date>2024-06-02T01:16:17+02:00</dc:date><dc:subject>data model relational </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2024-06-02T01:16:17+02:00&#034; href=&#034;https://bitnine.net/relational-database/data-modeling-rdb/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://bitnine.net/relational-database/data-modeling-rdb/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/data"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/relational"/></rdf:Bag></taxo:topics></item><item rdf:about="https://vertabelo.com/blog/data-modeling-techniques/"><title>5 Data Modeling Techniques | Vertabelo Database Modeler</title><description></description><link>https://vertabelo.com/blog/data-modeling-techniques/</link><dc:creator>bshanks</dc:creator><dc:date>2024-06-02T01:10:59+02:00</dc:date><dc:subject>data db dimensional entityrelationship er model relational schema sql star </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2024-06-02T01:10:59+02:00&#034; href=&#034;https://vertabelo.com/blog/data-modeling-techniques/&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://vertabelo.com/blog/data-modeling-techniques/&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/data"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/db"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dimensional"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/entityrelationship"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/er"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/relational"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/schema"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/sql"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/star"/></rdf:Bag></taxo:topics></item><item rdf:about="https://riseandbliss.com/personality-perspectives-shaping-identity-in-a-complex-world/"><title>Personality Perspectives: Shaping Identity in a Complex World</title><description>It is absolutely true to state that the role of an individual personality traits makes them more adaptable and comfortable to certain jobs. Selecting a career on the basis of your personality feature can result in a pleasant outcome. For example, if an individual is introvert, and if he chooses to become an anchor, just because it has a greater scope, tell me, can he thrive in this profession for a longer period of time?
Whenever, we hear such term in our day-to-day life, the first things that comes to our mind is of famous personalities, like Virat Kohli; Sachin Tendulker or Narendra Modi, etc. Not only this, we inspire from them and try to become like them, and in this process, we might lose our uniqueness. However, we never try to understand that what does personality actually mean?</description><link>https://riseandbliss.com/personality-perspectives-shaping-identity-in-a-complex-world/</link><dc:creator>surbhi1994</dc:creator><dc:date>2024-03-17T17:17:23+01:00</dc:date><dc:subject>Eysenck Indicator Model Myers-Briggs Personality The Type big five model </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;It is absolutely true to state that the role of an individual personality traits makes them more adaptable and comfortable to certain jobs. Selecting a career on the basis of your personality feature can result in a pleasant outcome. For example, if an individual is introvert, and if he chooses to become an anchor, just because it has a greater scope, tell me, can he thrive in this profession for a longer period of time?
Whenever, we hear such term in our day-to-day life, the first things that comes to our mind is of famous personalities, like Virat Kohli; Sachin Tendulker or Narendra Modi, etc. Not only this, we inspire from them and try to become like them, and in this process, we might lose our uniqueness. However, we never try to understand that what does personality actually mean?&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Eysenck"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Indicator"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Myers-Briggs"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Personality"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/The"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Type"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/big"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/five"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/></rdf:Bag></taxo:topics></item><item rdf:about="https://ollama.com/library"><title>library</title><description></description><link>https://ollama.com/library</link><dc:creator>hotho</dc:creator><dc:date>2024-02-18T11:55:21+01:00</dc:date><dc:subject>llama llm mac model ollama tools </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2024-02-18T11:55:21+01:00&#034; href=&#034;https://ollama.com/library&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://ollama.com/library&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/llama"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/llm"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/mac"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/ollama"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tools"/></rdf:Bag></taxo:topics></item><item rdf:about="https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard"><title>LMSys Chatbot Arena Leaderboard - a Hugging Face Space by lmsys</title><description></description><link>https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard</link><dc:creator>hotho</dc:creator><dc:date>2024-01-31T22:39:12+01:00</dc:date><dc:subject>board bot chat language large leader llm model modell </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2024-01-31T22:39:12+01:00&#034; href=&#034;https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://huggingface.co/spaces/lmsys/chatbot-arena-leaderboard&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/board"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/bot"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/chat"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/language"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/large"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/leader"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/llm"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/modell"/></rdf:Bag></taxo:topics></item><item rdf:about="https://www.phind.com/blog/code-llama-beats-gpt4"><title>Phind - AI Search Engine and Pair Programmer</title><description>We&#039;ve trained a new model, Phind-CodeLlama-34B-v2, that achieves 73.8% pass@1 on HumanEval.</description><link>https://www.phind.com/blog/code-llama-beats-gpt4</link><dc:creator>jil</dc:creator><dc:date>2023-10-10T14:10:45+02:00</dc:date><dc:subject>code fine llama2 llm model tuned </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;We&amp;#039;ve trained a new model, Phind-CodeLlama-34B-v2, that achieves 73.8% pass@1 on HumanEval.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/code"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/fine"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/llama2"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/llm"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tuned"/></rdf:Bag></taxo:topics></item><item rdf:about="https://www.cell.com/patterns/fulltext/S2666-3899(23)00239-8"><title>A universal workflow for creation, validation, and generalization of detailed neuronal models: Patterns</title><description></description><link>https://www.cell.com/patterns/fulltext/S2666-3899(23)00239-8</link><dc:creator>bshanks</dc:creator><dc:date>2023-10-09T05:50:29+02:00</dc:date><dc:subject>model neuro </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2023-10-09T05:50:29+02:00&#034; href=&#034;https://www.cell.com/patterns/fulltext/S2666-3899(23)00239-8&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://www.cell.com/patterns/fulltext/S2666-3899(23)00239-8&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/neuro"/></rdf:Bag></taxo:topics></item><item rdf:about="https://acl2023-retrieval-lm.github.io/"><title>ACL 2023 Tutorial: Retrieval-based LMs and Applications</title><description>Deformable Neural Radiance Fields creates free-viewpoint portraits (nerfies) from casually captured videos.</description><link>https://acl2023-retrieval-lm.github.io/</link><dc:creator>jaeschke</dc:creator><dc:date>2023-09-07T10:10:57+02:00</dc:date><dc:subject>information ir language llm model retrieval tutorial </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;Deformable Neural Radiance Fields creates free-viewpoint portraits (nerfies) from casually captured videos.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/information"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/ir"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/language"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/llm"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/retrieval"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/tutorial"/></rdf:Bag></taxo:topics></item><item rdf:about="https://news.ycombinator.com/item?id=37386397"><title>Get a cable modem, go to jail (1999) | Hacker News</title><description></description><link>https://news.ycombinator.com/item?id=37386397</link><dc:creator>bshanks</dc:creator><dc:date>2023-09-05T19:15:27+02:00</dc:date><dc:subject>cable isp model </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2023-09-05T19:15:27+02:00&#034; href=&#034;https://news.ycombinator.com/item?id=37386397&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://news.ycombinator.com/item?id=37386397&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/cable"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/isp"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/></rdf:Bag></taxo:topics></item><item rdf:about="https://platform.openai.com/docs/guides/embeddings/use-cases"><title>Embeddings - OpenAI API</title><description>We observed that generally the embedding representation is very rich and information dense. For example, reducing the dimensionality of the inputs using SVD or PCA, even by 10%, generally results in worse downstream performance on specific tasks.</description><link>https://platform.openai.com/docs/guides/embeddings/use-cases</link><dc:creator>jil</dc:creator><dc:date>2023-06-28T23:05:59+02:00</dc:date><dc:subject>dense embedding model pca store svd vector </dc:subject><content:encoded>&lt;span itemprop=&#034;description&#034;&gt;We observed that generally the embedding representation is very rich and information dense. For example, reducing the dimensionality of the inputs using SVD or PCA, even by 10%, generally results in worse downstream performance on specific tasks.&lt;/span&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/dense"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/embedding"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/pca"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/store"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/svd"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/vector"/></rdf:Bag></taxo:topics></item><item rdf:about="https://8530121.fs1.hubspotusercontent-na1.net/hubfs/8530121/Website%20Relaunch%202022/Blogbeitr%C3%A4ge/DASC-PM_v1.1.pdf"><title>https://8530121.fs1.hubspotusercontent-na1.net/hubfs/8530121/Website%20Relaunch%202022/Blogbeiträge/DASC-PM_v1.1.pdf</title><description></description><link>https://8530121.fs1.hubspotusercontent-na1.net/hubfs/8530121/Website%20Relaunch%202022/Blogbeitr%C3%A4ge/DASC-PM_v1.1.pdf</link><dc:creator>hotho</dc:creator><dc:date>2023-06-05T10:37:16+02:00</dc:date><dc:subject>Modell data model process science </dc:subject><content:encoded>&lt;a itemprop=&#034;url&#034; data-versiondate=&#034;2023-06-05T10:37:16+02:00&#034; href=&#034;https://8530121.fs1.hubspotusercontent-na1.net/hubfs/8530121/Website%20Relaunch%202022/Blogbeitr%C3%A4ge/DASC-PM_v1.1.pdf&#034; rel=&#034;nofollow&#034; class=&#034;description-link&#034;&gt;https://8530121.fs1.hubspotusercontent-na1.net/hubfs/8530121/Website%20Relaunch%202022/Blogbeitr%C3%A4ge/DASC-PM_v1.1.pdf&lt;/a&gt;</content:encoded><taxo:topics><rdf:Bag><rdf:li rdf:resource="https://www.bibsonomy.org/tag/Modell"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/data"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/model"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/process"/><rdf:li rdf:resource="https://www.bibsonomy.org/tag/science"/></rdf:Bag></taxo:topics></item></rdf:RDF>