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[ICML 2026] LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior
Workshop on World Models - Day 1 (WM@Booth 2026)
Do AI Models Follow Our Definitions | ICML 2026 Oral
LLMs Can Call Tools -- But Can They Understand Them (EACL 2026)
Every Local AI Engine Explained(2026) — Ollama, LM Studio, vLLM & 2 New
Leveraging LLMs for Causal Reasoning
The Next Evolution of AI — From LLMs to World Models
Beyond Prediction: How Causal AI Enables Better Decision-Making with Prof. Stefan Feuerriegel
CLIP… But For Decisions (Contrastive Language Models Explained)
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Last Updated: October 3, 2026
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Summary
Qinhong Zhou presents "LLawCo: Learning Laws of Cooperation for Modeling Embodied Multi-Agent Behavior" for the ... Day 2 - youtube.com/live/j_AujLxYUJc Day 3 - youtube.com/live/PkaYC3fwEsc Join us for WM a three-day ... LLM-based agents are everywhere, but most research focuses on just one step: getting the model to call the right tool. Can GPT-4 truly reason about cause and effect? Dive into how large language models GPT-4 tackle In this episode, Prof. Stefan Feuerriegel (LMU Munich, MCML) explains how CLM is a new System 1 model from Stanford and NVIDIA Research that works CLIP for decisions, embedding the situation ...
Towards Causal Artificial Intelligence Lm4plan Workshop Icml 2026.pdf
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