teetone/RoboReward-8B
770k
•
Updated
•
27
•
2
Reed li
RobotDall
AI & ML interests
None yet
Recent Activity
liked
a model
about 14 hours ago
teetone/RoboReward-8B
liked
a model
about 15 hours ago
teetone/RoboReward-4B
liked
a dataset
1 day ago
InternRobotics/InternData-A1
Organizations
liked
a
model
about 14 hours ago
liked
a
model
about 15 hours ago
liked
a
dataset
1 day ago
upvoted
a
collection
21 days ago
liked
a
model
23 days ago
liked
a
model
about 1 month ago
upvoted
a
collection
about 1 month ago
liked
a
model
about 2 months ago
upvoted
a
collection
about 2 months ago
liked
a
model
2 months ago
liked
3
datasets
3 months ago
liked
a
model
3 months ago
upvoted
2
collections
5 months ago
liked
2
datasets
5 months ago
liked
a
model
5 months ago
reacted to
Kseniase's
post with ❤️
5 months ago
Post
3492
12 Powerful World Models
World models are one of the most challenging areas in AI, pushing the boundaries of reasoning, perception, and planning. They're gen AI systems that help models and agents learn internal representations of real-world environments.
Today, we invite you to take a look at 12 standout examples:
1. WorldVLA → WorldVLA: Towards Autoregressive Action World Model (2506.21539)
This autoregressive world model integrates action prediction and visual world modeling in a single framework, allowing each to enhance the other. It introduces an attention masking strategy to reduce action prediction errors
2. SimuRA → https://arxiv.org/abs/2507.23773
A generalized world model that uses a language-based world model to simulate and plan actions before execution, enabling more general and flexible reasoning
3. PAN (Physical, Agentic, and Nested) world models → Critiques of World Models (2507.05169)
Has a hybrid architecture that combines discrete concept-based reasoning (via LLMs) with continuous perceptual simulation (via diffusion models), enabling rich multi-level, multimodal understanding and prediction
4. MineWorld by Microsoft Research → MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft (2504.08388)
Enables real-time, interactive world modeling in Minecraft by combining visual and action tokenization within an autoregressive Transformer. It uses parallel decoding for fast scene generation (4–7 FPS)
5. WorldMem → WORLDMEM: Long-term Consistent World Simulation with Memory (2504.12369)
Uses a memory bank with attention over time-stamped frames and states to maintain long-term and 3D spatial consistency in scene generation. So it reconstruct past scenes and simulate dynamic world changes across large temporal gaps
Read further below ⬇️
If you like this, also subscribe to the Turing post: https://www.turingpost.com/subscribe
Plus explore this article for a comprehensive overview of the history and current evolution of world models: https://www.turingpost.com/p/topic-35-what-are-world-models
World models are one of the most challenging areas in AI, pushing the boundaries of reasoning, perception, and planning. They're gen AI systems that help models and agents learn internal representations of real-world environments.
Today, we invite you to take a look at 12 standout examples:
1. WorldVLA → WorldVLA: Towards Autoregressive Action World Model (2506.21539)
This autoregressive world model integrates action prediction and visual world modeling in a single framework, allowing each to enhance the other. It introduces an attention masking strategy to reduce action prediction errors
2. SimuRA → https://arxiv.org/abs/2507.23773
A generalized world model that uses a language-based world model to simulate and plan actions before execution, enabling more general and flexible reasoning
3. PAN (Physical, Agentic, and Nested) world models → Critiques of World Models (2507.05169)
Has a hybrid architecture that combines discrete concept-based reasoning (via LLMs) with continuous perceptual simulation (via diffusion models), enabling rich multi-level, multimodal understanding and prediction
4. MineWorld by Microsoft Research → MineWorld: a Real-Time and Open-Source Interactive World Model on Minecraft (2504.08388)
Enables real-time, interactive world modeling in Minecraft by combining visual and action tokenization within an autoregressive Transformer. It uses parallel decoding for fast scene generation (4–7 FPS)
5. WorldMem → WORLDMEM: Long-term Consistent World Simulation with Memory (2504.12369)
Uses a memory bank with attention over time-stamped frames and states to maintain long-term and 3D spatial consistency in scene generation. So it reconstruct past scenes and simulate dynamic world changes across large temporal gaps
Read further below ⬇️
If you like this, also subscribe to the Turing post: https://www.turingpost.com/subscribe
Plus explore this article for a comprehensive overview of the history and current evolution of world models: https://www.turingpost.com/p/topic-35-what-are-world-models
- 1 reply