Large Language Model
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 .
Order-Independence Without Fine Tuning
Reid McIlroy-Young, Katrina Brown, Conlan Olson, Linjun Zhang, Cynthia Dwork
Unlike humans, these ' Large Language Models ' (LLMs) are highly sensitive to small changes in their inputs, leading to unwanted inconsistency in their behavior.
DISP-LLM: Dimension-Independent Structural Pruning for Large Language Models
Structural pruning has emerged as a promising solution to reduce the costs of LLMs without requiring post-processing steps.
Scissorhands: Exploiting the Persistence of Importance Hypothesis for LLM KV Cache Compression at Test Time
Large language models(LLMs) have sparked a new wave of exciting AI applications. Hosting these models at scale requires significant memory resources.
Introspective Planning: Aligning Robots ' Uncertainty with Inherent Task Ambiguity
The reliability of LLM outputs has direct implications downstream robotics tasks.
OMG-LLaV A: Bridging Image-level, Object-level, Pixel-level Reasoning and Understanding
Current universal segmentation methods demonstrate strong capabilities in pixel-level image and video understanding. However, they lack reasoning abilities and cannot be controlled via text instructions.
