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Training language models to follow instructions with human feedback
Making language models bigger does not inherently make them better at following a user's
intent. For example, large language models can generate outputs that are untruthful, toxic, or …
intent. For example, large language models can generate outputs that are untruthful, toxic, or …
Embodied navigation with multi-modal information: A survey from tasks to methodology
Embodied AI aims to create agents that complete complex tasks by interacting with the
environment. A key problem in this field is embodied navigation which understands multi …
environment. A key problem in this field is embodied navigation which understands multi …
Core challenges in embodied vision-language planning
Recent advances in the areas of multimodal machine learning and artificial intelligence (AI)
have led to the development of challenging tasks at the intersection of Computer Vision …
have led to the development of challenging tasks at the intersection of Computer Vision …
GlitchBench: Can large multimodal models detect video game glitches?
Large multimodal models (LMMs) have evolved from large language models (LLMs) to
integrate multiple input modalities such as visual inputs. This integration augments the …
integrate multiple input modalities such as visual inputs. This integration augments the …
Less is more: Generating grounded navigation instructions from landmarks
We study the automatic generation of navigation instructions from 360-degree images
captured on indoor routes. Existing generators suffer from poor visual grounding, causing …
captured on indoor routes. Existing generators suffer from poor visual grounding, causing …