Oct 12, 2023 · This framework improves model selection and bolsters the robustness of multi-modal agents in multi-step reasoning. In the absence of suitable ...
Jan 16, 2024 · This framework aims to enhance model selection and improve the robustness of multi-modal agents in multi-step reasoning scenarios. In the ...
This framework improves model selection and bolsters the robustness of multi-modal agents in multi-step reasoning. In the absence of suitable benchmarks, we ...
An ideal model selection method for multi-modal reasoning scenarios should allocate the optimal model choice per subtask or subtask type, so as to maximize the ...
This framework improves model selection and bolsters the robustness of multi-modal agents in multi-step reasoning, and enables dynamic model selection, ...
dynamic model selection, considering both user inputs and subtask dependencies, thereby robustifying the overall reasoning process. Our code and benchmark:
Towards Robust Multi-Modal Reasoning via Model Selection. Liu, Xiangyan*, Li, Rongxue*, Ji, Wei, and Lin, Tao. In International Conference on Learning ...
Feb 1, 2023 · We provide an information-theoretical analysis of how the modality complementariness affects the multi-modal robustness.
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Sep 25, 2024 · ... Multi-modal Assistant that can Plan, Execute, Inspect, and Learn Github · Star. M3 - Towards Robust Multi-Modal Reasoning via Model Selection ...
Towards Robust Multi-Modal Reasoning via Model Selection
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The paper presents a framework to improve model selection and the robustness of multi-modal agents in multi-step reasoning.