[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"article-2026-llm-paper-lists-better-than-feeds-en":3,"article-related-2026-llm-paper-lists-better-than-feeds-en":31,"series-research-cb48de54-dfdc-4fe0-adde-e5e3465c57bd":84},{"id":4,"slug":5,"title":6,"content":7,"summary":8,"source":9,"source_url":10,"author":11,"image_url":12,"cover_image":12,"category":13,"language":14,"translated_content":11,"related_article_id":15,"keywords":16,"key_takeaways":23,"views":27,"created_at":28,"published_at":29,"topic_cluster_id":30},"cb48de54-dfdc-4fe0-adde-e5e3465c57bd","2026-llm-paper-lists-better-than-feeds-en","2026 LLM paper lists are a better research tool than feeds","\u003Cp data-speakable=\"summary\">Curated \u003Ca href=\"\u002Ftag\u002Fllm\">LLM\u003C\u002Fa> paper lists beat raw feeds because they turn scattered research into usable context.\u003C\u002Fp>\u003Cp>Curated paper lists are more valuable than endless arXiv feeds for LLM work, and Sebastian Raschka’s January-to-May 2026 roundup proves it.\u003C\u002Fp>\u003Ch2>First argument: curation beats volume\u003C\u002Fh2>\u003Cp>The strongest reason to keep a curated list is simple: it reduces search friction. Raschka says he built the list because he often remembers that a relevant paper exists, but finding it again is annoyingly hard. That is not a niche complaint; it is the daily cost of working in a field that publishes at machine speed.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781258572644-me3b.png\" alt=\"2026 LLM paper lists are a better research tool than feeds\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>The list also makes the signal visible. In just the opening sections, the recurring themes are hybrid architectures, efficient \u003Ca href=\"\u002Ftag\u002Finference\">inference\u003C\u002Fa>, \u003Ca href=\"\u002Ftag\u002Flong-context\">long context\u003C\u002Fa>, reasoning, and \u003Ca href=\"\u002Ftag\u002Fagent\">agent\u003C\u002Fa> systems. That clustering matters more than completeness. A reader scanning the list can see where the field is moving without sorting through thousands of titles that only look different at the surface.\u003C\u002Fp>\u003Ch2>Second argument: the best list is opinionated\u003C\u002Fh2>\u003Cp>Raschka does not pretend to be exhaustive, and that is the point. He explicitly says this is a curated reference list based on papers he found interesting or relevant for his own work. That admission gives the list more value, not less, because it tells the reader what deserves attention from someone who is actively building and writing in the space.\u003C\u002Fp>\u003Cp>The evidence is in the selections. Papers like Nemotron 3 Super, Mamba-3, Gated DeltaNet-2, and Step 3.5 Flash are not random inclusions. They reflect a real thesis about 2026: long-context efficiency, hybrid architectures, and practical serving now matter as much as raw scale. A good research list should reveal that thesis instead of hiding behind neutrality.\u003C\u002Fp>\u003Ch2>The counter-argument\u003C\u002Fh2>\u003Cp>The obvious objection is that lists age fast. In a fast-moving field, a January-to-May roundup can look outdated by June, and a curated set can miss important work outside the curator’s interests. A raw feed, by contrast, is broader and less dependent on one person’s taste.\u003C\u002Fp>\n\u003Cfigure class=\"my-6\">\u003Cimg src=\"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781258579138-uogn.png\" alt=\"2026 LLM paper lists are a better research tool than feeds\" class=\"rounded-xl w-full\" loading=\"lazy\" \u002F>\u003C\u002Ffigure>\n\u003Cp>That criticism is fair, but it misses the real job of a research list. The goal is not to archive everything. The goal is to create a navigable map of the papers that matter for a given workflow. Raschka’s list does that with honest scope, category structure, and enough topical breadth to support real work. Exhaustiveness is a trap; usefulness is the standard.\u003C\u002Fp>\u003Cp>The best response is not to demand a perfect index. It is to accept that a strong list is a working artifact, not a census. For engineers, researchers, and technical writers, a curated shortlist is faster to reuse, easier to cite, and more likely to shape actual decisions than a firehose of links ever will.\u003C\u002Fp>\u003Ch2>What to do with this\u003C\u002Fh2>\u003Cp>If you are an engineer, PM, or founder, stop treating research discovery as passive browsing. Build a living shortlist by theme, keep one note for model architecture, one for training, one for serving, and one for agents, then update each with your own verdict on relevance. The value is not in collecting papers. The value is in making the next decision faster.\u003C\u002Fp>","Curated LLM paper lists beat raw feeds because they turn scattered research into usable context.","magazine.sebastianraschka.com","https:\u002F\u002Fmagazine.sebastianraschka.com\u002Fp\u002Fllm-research-papers-2026-part1",null,"https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781258572644-me3b.png","research","en","34681ebb-0d9d-4988-822a-45b6e5ad46d6",[17,18,19,20,21,22],"Sebastian Raschka","LLM research papers","hybrid architectures","agent systems","long context","efficient inference",[24,25,26],"Curated LLM paper lists reduce search friction and improve reuse.","Opinionated selection is more useful than exhaustive coverage.","Working research lists help teams make faster technical 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pixels","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781266683694-z93k.png","2026-06-12T12:17:32.187899+00:00",{"id":55,"slug":56,"title":57,"cover_image":58,"image_url":58,"created_at":59,"category":13},"763f2b17-41e2-4685-a9eb-9eb285383747","taxonomy-rwa-tokenization-blockchain-infrastructure-en","A Practical Taxonomy for RWA Tokenization","https:\u002F\u002Fxxdpdyhzhpamafnrdkyq.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Fcovers\u002Finline-1781259482218-p7ji.png","2026-06-12T10:17:30.894151+00:00",{"id":61,"slug":62,"title":63,"cover_image":64,"image_url":64,"created_at":65,"category":13},"d389cb06-cef8-48a6-abfc-0c5f5bcb6a26","anthropic-ai-building-ai-recursive-self-improvement-en","Anthropic’s own data says AI is already building 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Papers of the Week Turns GitHub Into a Research Desk","2026-03-27T01:11:39.480259+00:00",{"id":96,"slug":97,"title":98,"created_at":99},"87897a94-8065-4464-a016-1f23e89e17cc","ai-ml-conferences-to-watch-in-2026-en","AI\u002FML Conferences to Watch in 2026","2026-03-27T01:51:54.184108+00:00",{"id":101,"slug":102,"title":103,"created_at":104},"6f1987cf-25f3-47a4-b3e6-db0997695be8","openclaw-agents-manipulated-self-sabotage-en","OpenClaw Agents Can Be Manipulated Into Failure","2026-03-28T03:03:18.899465+00:00",{"id":106,"slug":107,"title":108,"created_at":109},"a53571ad-735a-4178-9f93-cb09b699d99c","vega-driving-language-instructions-en","Vega: Driving with Natural Language Instructions","2026-03-28T14:54:04.698882+00:00",{"id":111,"slug":112,"title":113,"created_at":114},"a34581d6-f36e-46da-88bb-582fb3e7425c","personalizing-autonomous-driving-styles-en","Drive My Way: Personalizing Autonomous Driving 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