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Beijing University of Posts and Telecommunications
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LongSpace reveals that integrating explicit spatial memory into MLLMs can dramatically enhance their performance on long-horizon tasks, a critical advancement for applications in autonomous navigation.
LLMs can escape suboptimal alignment equilibria by temporarily sacrificing performance on some objectives, paving the way for better overall trade-offs between conflicting preferences.
Reconstructing videos from brain activity gets a major boost with SemVideo, which uses hierarchical semantic guidance to produce more coherent and accurate reconstructions than ever before.
Data-parallel LLM fine-tuning can appear stable based on global metrics, but this paper reveals significant hidden worker-level divergence that can be diagnosed with simple metrics.
