2 citations · 2 across the 14 of their papers we have counts for
17 papers
RoboFollow: Unveiling the Instruction Following Mirage in Embodied Agents
Chang Guo, Yukun Xie, Bohan Tan +6
Modern embodied agents achieve impressive success rates, yet their actual instruction-following ability is far weaker than these numbers suggest. We trace this illusion to a struct…
Grounded Semantic Re-Binding for Robust Instruction Generalization in Vision-Language-Action Models
Zhaokai Yin, Zhipeng Zhang
Vision-Language-Action (VLA) models excel in robotic manipulation but suffer catastrophic performance drops when canonical instructions are simply paraphrased. Although this brittl…
Libra: Taming Attention Workload Skew in Long-Context LLM Training with Bounded Sequence Pool
Yan Wang, Xiulong Yuan, Kaiming Yang +16
Long-context LLM training suffers from a load-balancing problem that sequence packing does not solve. Packing samples into fixed-token sequences balances memory and linear-cost ope…
GASE: Gaussian Splatting-Based Automated System for Reconstructing Embodied-Simulation Environments
Jiawei Zhang, Yiming Yan, Chao Liang +8
Training embodied agents in the real world requires skilled operators and expensive hardware. Simulation environments offer a compelling alternative by enabling large-scale, cost-e…
YouZhi: Towards High-Concurrency Financial LLMs via Adaptive GQA-to-MLA Transition
PSBC LLM Team, Huawei LLM Team, Ruihan Long +56
Large language models (LLMs) drive significant financial innovations, yet their high-concurrency deployment is severely bottlenecked by KV cache memory overhead, which inflates inf…
Silent Collapse in Recursive Learning Systems
Zhipeng Zhang
Recursive learning -- where models are trained on data generated by previous versions of themselves -- is increasingly common in large language models, autonomous agents, and self-…