Correcting robot manipulation policies through human intervention holds great promise for real-world deployment, yet human operators are inherently imperfect in both the actions they provide and the timing of their intervention signals. While the former has been extensively discussed in reinforcement learning (RL), the...
Xin-Yi Zhang, Yi-Nuo Zhao, Pei Ren et al.· 1 citation
Kairos is introduced, a video dataset for video-language modeling with time-resolved annotations that supports fine-grained evaluation, long-range modeling and reasoning, instruction data construction, representation learning, and video generation.
Ruibo Ming, Lei Sun, De-Heng Zhang et al.· 0 citations
TTL-SR is proposed, a geometry-aware Test-Time Learning framework for quantitative Spatial Reasoning that leverages geometric consistency constraints and unlabeled test data to adapt models to target domains to boost spatial reasoning performance.
Ge-Ge Zhang, Shuai-Cheng Niu, Gang Dai et al.· 0 citations
A Multi-dimensional Evaluation-Verification Reward (EVR) decomposes evaluation into distinct visual criteria; for each criterion, an MLLM Evaluator generates multiple candidate hypotheses, and a Verifier grounds each claim in concrete visual evidence to accept or reject it, producing reliable and fine-grained reward si...
This work proposes a Scale-wise Conditional Decoding mechanism, which projects semantic signals from a frozen vision encoder into scale-specific layers of the VAR backbone, and introduces a Unified Control Alignment strategy (SCALAR-Uni) to handle diverse control modalities within a single projection space.
Ryan Xu, Dong-Yang Jin, Shawn Chen et al.· International Journal of Com...· 1 citation
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