Physical Intuition
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Benchmarks
BIG-bench
Most implemented
Scaling Language Models: Methods, Analysis & Insights from Training Gopher
Learning Physical Intuition of Block Towers by Example
Training Compute-Optimal Large Language Models
Examining the Source of Defects from a Mechanical Perspective for 3D Anomaly Detection
Physics-Inspired Distributed Radio Map Estimation
Papers
GeoTLM: Geometry-aware Tactile-Language Models for Contact Motion Orientation Reasoning of Dynamic Objects
Modern tactile-language models (TLMs) have shown potential for robot learning tasks, such as material and texture recognition. However, for contact-rich scenarios, these TLMs struggle to understand the physical propertie…
Physical IntuitionSparse probes and murky physics: a case study of interpretability challenges in a foundation model for continuum dynamics
Generative AI emulators are increasingly used in scientific domains where we already have strong theory, benchmarks, and physical intuition. This raises a central evaluation and interpretability question: when a foundati…
Physical IntuitionPRISM: PRior-guided Imagination Sampling in world Models
A learned world model provides a powerful physical intuition for evaluating future states. But its effectiveness in continuous control also depends critically on how candidate actions are generated for model-based planni…
Continuous ControlPhysical IntuitionA Machine-to-Machine Knowledge-Guided LLM Agent for Generalizable Radiotherapy Treatment Planning
In this work, we propose a prototype machine-to-machine (M2M) knowledge-guided Large Language Model (LLM) framework for automated radiotherapy treatment planning. In the proposed paradigm, Treatment Planning Parameter (T…
Reinforcement LearningPhysical IntuitionMDGYM: Benchmarking AI Agents on Molecular Simulations
The promise of AI-driven scientific discovery hinges on whether AI agents can autonomously design and execute the computational workflows that underpin modern science. Molecular dynamics (MD) simulation presents a natura…
Physical IntuitionCode GenerationFrom Equations to Algorithms and Data: Transforming Microwave Engineering and Education with Machine Learning
Conventional microwave engineering education relies heavily on analytical methods, canonical circuit topologies, and intuition-driven design, which have proven effective at microwave frequencies. However, as systems incr…
Physical Intuition