ValiantLabs/gpt-oss-20b-ShiningValiant3
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ValiantLabs/Qwen3-1.7B-ShiningValiant3
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sequelbox/Qwen3-14B-UML-Generator
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Two new releases today!
Firstly, our new Raiden-Mini dataset, powered by DeepSeek's newest deepseek-ai/DeepSeek-V3.2-Speciale model!
- A V3.2-Speciale reasoning showcase: the Raiden prompts test the model's creative, analytic, and general reasoning skills!
- HEAD TO HEAD: a comparison subset pits V3.2-Speciale against V3.2 with the same prompts, providing a direct look at each model's advantages!
Get the new Raiden-Mini dataset: sequelbox/Raiden-Mini-DeepSeek-V3.2-Speciale
On the model side, we've also brought Shining Valiant 3 to Ministral 3!
- Science-reasoning: sequelbox/Celestia3-DeepSeek-R1-0528 for physics, biology, chemistry, compsci, astronomy, Earth science, and information theory.
- AI to build AI: the sequelbox/Mitakihara-DeepSeek-R1-0528 dataset for high-quality reasoning performance on AI, MLOps, math and CUDA, complex adaptive and agentic systems, cognition, logic, linguistics, simulation, knowledge management, and more!
- Creative reasoning and general chat performance supplemented with sequelbox/Raiden-DeepSeek-R1
Get the newest SV3: ValiantLabs/Ministral-3-14B-Reasoning-2512-ShiningValiant3
Esper 3.1 is available for Ministral 3 as well: ValiantLabs/Ministral-3-14B-Reasoning-2512-Esper3.1
We're working hard on our next Big New Release, coming out in the next few weeks :)
Help support our releases, donations used for models and datasets: sequelbox/SupportOpenSource
Open source matters. Fight for it with us.
with love and friendship,
allegra
Firstly, our new Raiden-Mini dataset, powered by DeepSeek's newest deepseek-ai/DeepSeek-V3.2-Speciale model!
- A V3.2-Speciale reasoning showcase: the Raiden prompts test the model's creative, analytic, and general reasoning skills!
- HEAD TO HEAD: a comparison subset pits V3.2-Speciale against V3.2 with the same prompts, providing a direct look at each model's advantages!
Get the new Raiden-Mini dataset: sequelbox/Raiden-Mini-DeepSeek-V3.2-Speciale
On the model side, we've also brought Shining Valiant 3 to Ministral 3!
- Science-reasoning: sequelbox/Celestia3-DeepSeek-R1-0528 for physics, biology, chemistry, compsci, astronomy, Earth science, and information theory.
- AI to build AI: the sequelbox/Mitakihara-DeepSeek-R1-0528 dataset for high-quality reasoning performance on AI, MLOps, math and CUDA, complex adaptive and agentic systems, cognition, logic, linguistics, simulation, knowledge management, and more!
- Creative reasoning and general chat performance supplemented with sequelbox/Raiden-DeepSeek-R1
Get the newest SV3: ValiantLabs/Ministral-3-14B-Reasoning-2512-ShiningValiant3
Esper 3.1 is available for Ministral 3 as well: ValiantLabs/Ministral-3-14B-Reasoning-2512-Esper3.1
We're working hard on our next Big New Release, coming out in the next few weeks :)
Help support our releases, donations used for models and datasets: sequelbox/SupportOpenSource
Open source matters. Fight for it with us.
with love and friendship,
allegra
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15 Outstanding Research Papers from NeurIPS 2025
NeurIPS 2025, as a premier annual event in machine learning and computational neuroscience, tackles major topics like the future of AI, current research, and the most difficult challenges. While we’re not attending this year, we’re closely following the updates and today we pull together a quick, easy-to-digest roundup of a few standout papers so you can jump in without getting overwhelmed.
Here is a list of 15 papers from NeurIPS 2025, including 8 top research papers that received awards, along with 7 others that caught our attention:
1. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks → https://neurips.cc/virtual/2025/loc/san-diego/test-of-time/128328
Test of Time Award winner. Introduces the RPN, a small convnet that predicts objectness and boxes on shared features, enabling Faster R-CNN to share computation and run around 5 fps on a GPU
2. Artificial Hivemind: The Open-Ended Homogeneity of LMs (and Beyond) → https://neurips.cc/virtual/2025/loc/san-diego/poster/121421
Releases a huge open-ended prompt dataset, showing that LLMs often fall into an “artificial hivemind” – generate surprisingly similar answers – and measuring diversity collapse
3. Optimal Mistake Bounds for Transductive Online Learning → https://neurips.cc/virtual/2025/loc/san-diego/poster/119098
Settles a 30-year-old question by showing how much unlabeled data helps in online learning – it gives a precise quadratic advantage with tight matching bounds
4. Gated Attention for LLMs: Non-linearity, Sparsity, and Attention-Sink-Free → https://neurips.cc/virtual/2025/loc/san-diego/poster/120216
Demonstrates how gating actually affects attention: a simple sigmoid gate after Scaled Dot-Product Attention (SDPA) boosts performance, stability, and long-context behavior by adding useful nonlinearity and sparse modulation
Read further below ⬇️
Also, subscribe to the Turing Post: https://www.turingpost.com/subscribe
NeurIPS 2025, as a premier annual event in machine learning and computational neuroscience, tackles major topics like the future of AI, current research, and the most difficult challenges. While we’re not attending this year, we’re closely following the updates and today we pull together a quick, easy-to-digest roundup of a few standout papers so you can jump in without getting overwhelmed.
Here is a list of 15 papers from NeurIPS 2025, including 8 top research papers that received awards, along with 7 others that caught our attention:
1. Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks → https://neurips.cc/virtual/2025/loc/san-diego/test-of-time/128328
Test of Time Award winner. Introduces the RPN, a small convnet that predicts objectness and boxes on shared features, enabling Faster R-CNN to share computation and run around 5 fps on a GPU
2. Artificial Hivemind: The Open-Ended Homogeneity of LMs (and Beyond) → https://neurips.cc/virtual/2025/loc/san-diego/poster/121421
Releases a huge open-ended prompt dataset, showing that LLMs often fall into an “artificial hivemind” – generate surprisingly similar answers – and measuring diversity collapse
3. Optimal Mistake Bounds for Transductive Online Learning → https://neurips.cc/virtual/2025/loc/san-diego/poster/119098
Settles a 30-year-old question by showing how much unlabeled data helps in online learning – it gives a precise quadratic advantage with tight matching bounds
4. Gated Attention for LLMs: Non-linearity, Sparsity, and Attention-Sink-Free → https://neurips.cc/virtual/2025/loc/san-diego/poster/120216
Demonstrates how gating actually affects attention: a simple sigmoid gate after Scaled Dot-Product Attention (SDPA) boosts performance, stability, and long-context behavior by adding useful nonlinearity and sparse modulation
Read further below ⬇️
Also, subscribe to the Turing Post: https://www.turingpost.com/subscribe
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ICYMI, transformers v5 is out!
Grab a coffee ☕ and go read the announcement blog https://huggingface.co/blog/transformers-v5
Grab a coffee ☕ and go read the announcement blog https://huggingface.co/blog/transformers-v5
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NEW RELEASE: Esper 3.1 for Ministral 3 14b, 8b, and 3b!
- Esper is our full-stack, full-cycle coding, DevOps, and architecture specialist!
- Our newest, best DeepSeek technical datasets emphasize more challenging queries and tough real-world coding tasks across a variety of programming languages and development paradigms:
- Titanium 3 for coding and reasoning in DevOps and architecture: sequelbox/Titanium3-DeepSeek-V3.1-Terminus
- Tachibana 3 for high-difficulty code production in a variety of topics and programming languages:
- sequelbox/Tachibana3-Part1-DeepSeek-V3.1-Terminus
- sequelbox/Tachibana3-Part2-DeepSeek-V3.2
- Mitakihara for MLOps, AI building, use, expertise, and research: sequelbox/Mitakihara-DeepSeek-R1-0528
Get Esper 3.1 now in all 3 Ministral 3 sizes! (We recommend 14b for general use.)
14b: ValiantLabs/Ministral-3-14B-Reasoning-2512-Esper3.1
8b: ValiantLabs/Ministral-3-8B-Reasoning-2512-Esper3.1
3b: ValiantLabs/Ministral-3-3B-Reasoning-2512-Esper3.1
We'll be bringing more models to Ministral soon, including Shining Valiant 3 :)
We're currently working hard on a big release in a new specialty - hoping to have that up on Valiant Labs before the end of the year! We'll keep pushing the boundaries of what personal-sized AI can do for you.
See our Experimental Reasoning models and open-source datasets: @sequelbox
Help us keep working for open source AI with a donation: sequelbox/SupportOpenSource
with love,
allegra
- Esper is our full-stack, full-cycle coding, DevOps, and architecture specialist!
- Our newest, best DeepSeek technical datasets emphasize more challenging queries and tough real-world coding tasks across a variety of programming languages and development paradigms:
- Titanium 3 for coding and reasoning in DevOps and architecture: sequelbox/Titanium3-DeepSeek-V3.1-Terminus
- Tachibana 3 for high-difficulty code production in a variety of topics and programming languages:
- sequelbox/Tachibana3-Part1-DeepSeek-V3.1-Terminus
- sequelbox/Tachibana3-Part2-DeepSeek-V3.2
- Mitakihara for MLOps, AI building, use, expertise, and research: sequelbox/Mitakihara-DeepSeek-R1-0528
Get Esper 3.1 now in all 3 Ministral 3 sizes! (We recommend 14b for general use.)
14b: ValiantLabs/Ministral-3-14B-Reasoning-2512-Esper3.1
8b: ValiantLabs/Ministral-3-8B-Reasoning-2512-Esper3.1
3b: ValiantLabs/Ministral-3-3B-Reasoning-2512-Esper3.1
We'll be bringing more models to Ministral soon, including Shining Valiant 3 :)
We're currently working hard on a big release in a new specialty - hoping to have that up on Valiant Labs before the end of the year! We'll keep pushing the boundaries of what personal-sized AI can do for you.
See our Experimental Reasoning models and open-source datasets: @sequelbox
Help us keep working for open source AI with a donation: sequelbox/SupportOpenSource
with love,
allegra
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