Tyrant
@wearice.bsky.social
Reposted by Tyrant
Jacqueline Mitchell, Yasser Shaaban: Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verification https://arxiv.org/abs/2511.00202 https://arxiv.org/pdf/2511.00202 https://arxiv.org/html/2511.00202
November 4, 2025 at 6:34 AM
Jacqueline Mitchell, Yasser Shaaban: Position: Vibe Coding Needs Vibe Reasoning: Improving Vibe Coding with Formal Verification https://arxiv.org/abs/2511.00202 https://arxiv.org/pdf/2511.00202 https://arxiv.org/html/2511.00202
Reposted by Tyrant
Revolutionizing Cryptography: AI Agents Automate Lean Formal Verification#Japan#Tokyo#Nyx_Foundation#cryptographic_protocols#Lean_language
Revolutionizing Cryptography: AI Agents Automate Lean Formal Verification
Discover how the Nyx Foundation successfully automated the Lean formal verification of cryptographic protocols using AI agents, enhancing security and efficiency.
third-news.com
November 4, 2025 at 8:54 AM
Revolutionizing Cryptography: AI Agents Automate Lean Formal Verification#Japan#Tokyo#Nyx_Foundation#cryptographic_protocols#Lean_language
Reposted by Tyrant
For anyone interested in fine-tuning or aligning LLMs, I’m running this free and open course called smol course. It’s not a big deal, it’s just smol.
🧵>>
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December 3, 2024 at 9:21 AM
For anyone interested in fine-tuning or aligning LLMs, I’m running this free and open course called smol course. It’s not a big deal, it’s just smol.
🧵>>
🧵>>
Reposted by Tyrant
We're about to launch the biggest collaboration effort since the Open Assistant.
Let's get the highest quality data for open foundation models with all the nuances & diversity of each language, all with data provenance and transparency
Join us as language lead:
docs.google.com/forms/d/10XI...
Let's get the highest quality data for open foundation models with all the nuances & diversity of each language, all with data provenance and transparency
Join us as language lead:
docs.google.com/forms/d/10XI...
Language Lead sign-up
At Hugging Face 🤗, we're launching a big community initiative to improve LLM training for many languages. We're looking for Language Leads to help us cultivate specific languages during this initiativ...
docs.google.com
December 3, 2024 at 4:53 PM
We're about to launch the biggest collaboration effort since the Open Assistant.
Let's get the highest quality data for open foundation models with all the nuances & diversity of each language, all with data provenance and transparency
Join us as language lead:
docs.google.com/forms/d/10XI...
Let's get the highest quality data for open foundation models with all the nuances & diversity of each language, all with data provenance and transparency
Join us as language lead:
docs.google.com/forms/d/10XI...
Reposted by Tyrant
Ever wonder how well frontier models (Claude 3.5 Sonnet, Gemini 1.5 Flash & Pro, GPT-4o, o1-mini & o1-preview) play Atari, chess, or tic-tac-toe?
We present LMAct, an in-context imitation learning benchmark with long multimodal demonstrations (arxiv.org/abs/2412.01441).
🧵 1/N
We present LMAct, an in-context imitation learning benchmark with long multimodal demonstrations (arxiv.org/abs/2412.01441).
🧵 1/N
December 3, 2024 at 5:15 PM
Ever wonder how well frontier models (Claude 3.5 Sonnet, Gemini 1.5 Flash & Pro, GPT-4o, o1-mini & o1-preview) play Atari, chess, or tic-tac-toe?
We present LMAct, an in-context imitation learning benchmark with long multimodal demonstrations (arxiv.org/abs/2412.01441).
🧵 1/N
We present LMAct, an in-context imitation learning benchmark with long multimodal demonstrations (arxiv.org/abs/2412.01441).
🧵 1/N
Reposted by Tyrant
Yeah in the sense of RF. Although RF wont get you to OT (Qiang Liu himself has a counterexample). But if you consider noisy flow matching (a la stochastic interpolant) then this procedure converges to EOT. Shameless plug + concurrent paper arxiv.org/abs/2303.16852 + arxiv.org/abs/2304.00917
Diffusion Schrödinger Bridge Matching
Solving transport problems, i.e. finding a map transporting one given distribution to another, has numerous applications in machine learning. Novel mass transport methods motivated by generative model...
arxiv.org
November 30, 2024 at 12:35 PM
Yeah in the sense of RF. Although RF wont get you to OT (Qiang Liu himself has a counterexample). But if you consider noisy flow matching (a la stochastic interpolant) then this procedure converges to EOT. Shameless plug + concurrent paper arxiv.org/abs/2303.16852 + arxiv.org/abs/2304.00917