GPA-LM vs groundingLMM
GPA-LM: This repository serves as a comprehensive collection of research papers focused on the intersection of game-playing agents and large language models. It covers various methods, applications, and challenges, providing a dynamic timeline of recent advancements in the field of LLM-based agents for games.; groundingLMM: GLaMM (Grounding Large Multimodal Model) is an end-to-end trained LMM capable of generating natural language responses integrated with object segmentation masks, enabling visual grounding and versatile interaction with images at multiple granularity levels. It introduces the novel task of Grounded Conversation Generation (GCG), supports various downstream applications like referring expression segmentation and region-level captioning, and is underpinned by the large-scale GranD dataset.
TL;DR
Staying updated with the latest research in LLM-based game agents.
Interactive visual assistants that understand and respond to user queries about specific image regions.
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