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Fudan University, Shanghai Innovation Institute
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Legal agents exhibit starkly different performance across litigation stages, challenging the notion of a one-size-fits-all model in legal AI applications.
VLA models can lose up to 40% of their effectiveness in real-world scenarios due to occlusion, but viewpoint imagination offers a powerful solution to this pervasive challenge.
Gradual bridging with embodied trajectory-coupled data transforms VLMs into robust robot control policies, overcoming significant transfer challenges.
