Materials
comprehensive benchmark on eight tasks
Large Language Models (LLMs) with strong abilities in natural language processing tasks have emerged and have been applied in various kinds of areas such as science, finance and software engineering.
Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents Zihao Wang
These additional behavior tokens will be augmented to the vocabulary of pretrained Multimodal Language Models. With this encoder, we then pack long-term multimodal interactions involving task instructions, memories, thoughts, observations, textual responses, behavior trajectories, etc .
Optimizing over trained GNNs via symmetry breaking
Although GNNs are powerful tools for these "forward" prediction tasks, few works discuss the "backward" (or inverse) problem defined on trained GNNs.
Infusing Synthetic Data with Real-World Patterns for Zero-Shot Material State Segmentation
Minerals in rocks, sediment in soil, dust on surfaces, infection on leaves, stains on fabrics, and foam in liquids are some of these almost infinite numbers of states and patterns.
TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials
The development of efficient machine learning models for molecular systems representation is becoming crucial in scientific research.
