Check out our work: GitHub: https://
github.com/zhaoxlpku/Subg
oalXL
… Datasets & Models: https://
huggingface.co/collections/xl
-zhao/subgoalxl-66c84b77e0eaf131c0cdac15
… Paper: https://
arxiv.org/abs/2408.11172
Join us in pushing the boundaries of AI reasoning! #AI #LLM #SubgoalXL #AIResearch #ProofFormalization #MachineAssistedProofs
CODE
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SubgoalXL: Advanced AI Reasoning and Proof Formalization Framework
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Subgoal-based framework improves theorem proving with expert learning
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Our new framework combines subgoal-based proofs with expert learning for theorem proving in Isabelle. Subgoal-based proofs break complex reasoning into intermediate steps, aligning with formal proof structures. Expert learning iteratively refines formal statement, proof,
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SubgoalXL Improves LLM Theorem Proving Efficiency
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SubgoalXL tackles two major challenges in LLM theorem proving: Scarcity of specialized theorem-proving data Complexity in multi-step reasoning for formal proofs
Our solution: Optimizing data efficiency and structuring proofs into manageable subgoals. -
DFIntelligence: Struggle with complex files, but better than Claude alone
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Edit: after 4h of use, it's a struggle to use for quite complex tasks across multiple files, and it quickly forgets important contexts. BUT it's still better than just Claude in chat. (I find myself having to copy-paste files onto
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FastHTML Lambda Integration Sample from AWS
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New sample from @awscloud showing how to use FastHTML with Lambda! 😀 https://
github.com/awslabs/aws-la
mbda-web-adapter/tree/main/examples/fasthtml-response-streaming
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Claude: finds files, understands queries, executes and modifies
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It finds files itself, it has a much better understanding of queries, it can run everything for you, and modify everything in multiple files at the same time. And above all, Claude.
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Hacker Cup Launches AI Track with Meta and Microsoft
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Hacker Cup – one of the preeminent coding competitions started an AI track w/ Meta & Microsoft problems are hardddd – only a handful of engineers reliably solve them – requires deep algorithmic knowledge, reasoning, planning and fast execution – to solve 5 problems in 30
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Gemini Pro 1.5 vs Sonnet 3.5: LLM Performance Across Programming Languages
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After benchmarking more than 80 LLMs, @zimmskal & team found that the best model isn't always a great match for your programming language. Google's Gemini Pro 1.5 worked well for Go, but not so much for Java & Ruby, for example. The best overall LLM was Anthropic’s Sonnet 3.5.
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Understanding different scopes of ctrl+k/i by context
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The trick is to understand that there are different scopes depending on whether you use ctrl+k/i in the terminal, in the chat, in a file, etc.
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NeuroSandboxWebUI: Local Interface for Multiple AI Models
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NeuroSandboxWebUI github: https://
github.com/Dartvauder/Neu
roSandboxWebUI
… (Windows/Linux) Local WebUI with Text, Image, Video, 3D, and Audio models in a Gradio interface. Translated on 14 languages