Z3, CVC5, Satisfiability, Constraint Solving, Automated Reasoning

Thinking with Types: type-level programming in Haskell
thinkingwithtypes.com·1d·
Discuss: Hacker News
🔠Type-Level Programming
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The Cantor Experiment: Forcing a GPT-5-Class AI to Forget a Century of Math
romainpeter.substack.com·11h·
Discuss: Substack
🔁Fixed-Point Theory
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Uncrossed Multiflows and Applications to Disjoint Paths
arxiv.org·2h
Process Calculi
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CompAgent: An Agentic Framework for Visual Compliance Verification
arxiv.org·2h
🧩Separation Logic
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Hybrid Neuro-Symbolic Reasoning for Adaptive Robotics Control in Dynamic Environments
dev.to·2d·
Discuss: DEV
🤖Robotics
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Adding New Capability in Existing Scientific Application with LLM Assistance
arxiv.org·2h
⚙️Compiler Design
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SpatialTraceGen: High-Fidelity Traces for Efficient VLM Spatial Reasoning Distillation
arxiv.org·2h
🧩Separation Logic
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STACKFEED: Structured Textual Actor-Critic Knowledge Base Editing with FeedBack
arxiv.org·2h
🧩Parser Combinators
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H-FA: A Hybrid Floating-Point and Logarithmic Approach to Hardware Accelerated FlashAttention
arxiv.org·2h
🔀OCaml Multicore
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Probing Knowledge Holes in Unlearned LLMs
arxiv.org·2h
🔍CBMC
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Human-AI Programming Role Optimization: Developing a Personality-Driven Self-Determination Framework
arxiv.org·2h
λFunctional Programming
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ShadowLogic: Backdoors in Any Whitebox LLM
arxiv.org·2h
🛡️seL4
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AI Models Write Code with Security Flaws 18–50% of the Time, New Study Finds
medium.com·13h·
Discuss: Hacker News
🏃Escape Analysis
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Visual Backdoor Attacks on MLLM Embodied Decision Making via Contrastive Trigger Learning
arxiv.org·1d
🎮Verification Games
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OSMGen: Highly Controllable Satellite Image Synthesis using OpenStreetMap Data
arxiv.org·2h
📦OPAM
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Efficient Curvature-aware Graph Network
arxiv.org·2h
🕸️Graph Theory
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Incremental Selection of Most-Filtering Conjectures and Proofs of the Selected Conjectures
arxiv.org·2h
⏱️Computational Complexity
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Python Integration for Scryer Prolog Using FFI (Research Project)
github.com·13h·
Discuss: Hacker News
📦Module Systems
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Beyond ImageNet: Understanding Cross-Dataset Robustness of Lightweight Vision Models
arxiv.org·2h
Existential Types
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