Causal discovery algorithms and tools for implementing new ones
Build LLM agents that explain why, not just what. Attribution-driven agent requirements engineering framework. Based on the 4D-ARE Paper - https://arxiv.org/abs/2601.04556
Bridging generative world models and causal reasoning for realistic yet adversarial safety-critical scenario generation.
Step-by-step causal inference — method selection, assumptions, and robustness checks
The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.
The cause2e package provides tools for performing an end-to-end causal analysis of your data. Developed by Daniel Grünbaum (@dg46).
Active Bayesian Causal Inference (Neurips'22)
Causal RL Environments Simulator
永久性记忆，8层认知+直觉+因果记忆系统让 AI Agent 记住长期上下文 | 13维因果推理+Factlet精萃+Wiki+睡梦沉淀 | OpenClaw/Hermes 记忆开源项目 | AI Agent记忆
Knowledge-Augmented Language Models for Cause-Effect Relation Classification https://arxiv.org/abs/2112.08615
⚡ Temporal Browser Intelligence & Agent-Owned Workflow Runtime with 350 Certified MCP Tools & Python SDK · Sub-Millisecond DOM Time-Travel, Target Memory & Deterministic Automation.
Official implementation of "Transitivity Recovering Decompositions: Interpretable and Robust Fine-Grained Relationships", NeurIPS 2023.
AI系统结构化因果逻辑框架——可审计、可追溯的推理，无需替换现有模型。守真·稳态（KISS's Law）。极省Token，与黑箱共存。
Hierarchical Causal Latent State Machines for Object-Centric World Modeling
Persistent computational understanding for the AI tools you already use. A governed cognitive layer that transforms distributed observations into reusable understanding across models and interfaces.
Curated, annotated research on reasoning gaps in large language models — temporal reasoning, causal reasoning, and beyond.
🔥 让AI像专家一样诊断 | 3种创新方法 | 跨领域通用 | 精美可视化
VCRBench: Exploring Long-form Causal Reasoning Capabilities of Large Video Language Models
7-layer RAG framework that eliminates semantic drift + context poisoning. Faithfulness 0.94 vs 0.71 Naive RAG. +13.6 EM on multi-hop QA.
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