Humanoid locomotion in confined spaces requires continuous height adaptation across multiple locomotion modes, yet most existing approaches remain limited to height-adjustable bipedal walking. We present REACH, an RL-based hierarchical framework that enables a Unitree G1 humanoid to traverse height-constrained environm...
Shengzhang Xu, Yuning Guo, Weiyi Hu et al.· 0 citations
Unified conditional image generation requires a single model to preserve different aspects of a visual input while producing a target image that follows textual guidance. Pretrained video models provide a promising foundation by encoding visual transformations across time, yet existing approaches typically assign the c...
Yijing Lin, Zhendong Mao, Mengqi Huang et al.· 0 citations
This work introduces RoboAuto, a framework for robot program search that explicitly organizes physical understanding at the object, scene, and interaction levels through three components and shows that the knowledge base transfers across simulators and embodiments, and that program search performance scales with its si...
Bu-Zhao Liu, Jia-Ning Ye, Xiu Yuan et al.· 1 citation
ClaimNov is introduced, a fine-grained, interpretable claim-level novelty module that catches 97% of disguised papers at a 1.5% false-alarm rate, and cuts the LLM judge's false alarms from 11.8% to 1.5%.
Miri Liu, Xi-Yu Zhao, En-Cheng Xie et al.· 0 citations
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We present \tool, a query-efficient framework for black-box probabilistic verification. Given a fixed, sampleable input distribution and a binary property oracle, \tool assesses the property's violation probability $p$ against a threshold $\theta$. Under independent sampling and stateless oracle behavior, acceptance as...
Zexin Li, Weibo Zhang, Linyi Li et al.· 0 citations
On-policy distillation (OPD) improves language-model post-training by letting the student learn from its own sampled trajectories under teacher supervision, aligning the training process with inference-time behavior. However, the rollout policy in OPD is usually treated as fixed: each round samples directly from the cu...
Si-Rui Chen, Yun-Zhe Qi, Hao-Bo Xu et al.· 0 citations
Sequential trading agents produce decisions, orders, execution receipts, account states, and reports that need not agree, even when the final portfolio value is correctly computed. We present FIDES-Live, an operational extension of FIDES from generated strategy concordance to the audit of sequential agent traces. The p...
Arther Tian, Alex Ding, Simon Wu et al.· 0 citations
Recent long-tailed recognition (LTR) methods incorporate neural collapse (NC) and align features to a fixed Equiangular Tight Frame (ETF) as a uniform target for all classes. However, forcing tail classes to fully collapse over-contracts their samples and weakens generalization. To address this, we propose a controlled...
Video stylization typically transforms entire scenes, while local artistic editing requires precise region--style association, spatial control, and temporal consistency. We introduce LociArt, a unified paradigm for free-style local video stylization that explicitly specifies where to stylize and what style to apply whi...
Yuxuan Chen, Feng Xie, Jia-Gao Hu et al.· 0 citations
This work introduces RePPO, which adapts PPO to jointly optimize a compact population of diverse, high-quality policies using a population-dependent, dynamically shaped reward, and shows that directly optimizing compact populations with RePPO provides a scalable approach to QD-RL across increasingly complex domains.
Saeed Hedayatian, Harsh Shah, Celine Mneimneh et al.· 0 citations
Scientific drilling has produced large archives of physical, chemical and magnetic measurements linked to descriptions of the rock recovered. These archives are mostly incomplete: instruments sample at different intervals, recovery is partial, and destructive analyses preclude later measurement of the same material. We...
John M. Aiken, William Gilpin, Thorsten W. Becker· 0 citations
Perceiving human body motion is critical for multimodal systems that understand and assist people. Yet current evaluations of Multimodal Large Language Models (MLLMs) largely focus on objects, scenes, and coarse actions, leaving their ability to reason about the body itself poorly assessed. This is especially challengi...
Matea Tashkovska, Na\"el Ouerghemi, Haozhe Qi et al.· 0 citations
