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论文提出 Mediator，一种离散、本体无关的 EHR 分词器，将任意临床概念映射到共享向量量化码本，使封闭词汇模型可迁移至 eICU，零样本任务 AUPRC 相对提升 29%。
The paper proposes Ruspan, a rubric-conditioned Automatic Short Answer Scoring framework that serializes question, answer, and rubric levels for single-pass LLM scoring, plus a Rubric-Independent Mask variant that improves zero-shot transfer on multilingual ASAS benchmarks with rubric-structure shift.
The paper introduces MACTS-EM, a multi-agent collaborative framework for time series forecasting that uses specialised agents, a meta-cognitive layer, emergent memory, and multimodal integration, reporting 8-12% accuracy gains and improved zero-shot transfer and regime-shift resilience across financial, climate, energy, and pandemic datasets.
FetchMan is a vision-based humanoid policy trained entirely in simulation, capable of zero-shot transfer to diverse real-world scenes and objects for loco-manipulation tasks.
This paper presents a transferable learned temporal prior for outbreak transmission reconstruction, demonstrating improved performance on a real Andes virus benchmark and highlighting the importance of quantifying uncertainty in transmission labels.
This paper proposes a reinforcement learning approach to enable large language models to translate unseen languages by leveraging in-context linguistic knowledge, outperforming in-context learning and supervised fine-tuning.
ReactiveGWM is a reactive game world model that enables dynamic player-NPC interactions by decoupling player controls from NPC behaviors using diffusion models and cross-attention modules, achieving zero-shot strategy transfer across different games.
The paper introduces Diamond Attention, a method for multi-agent reinforcement learning that uses structured randomness to break symmetry and enable role differentiation among homogeneous agents, achieving perfect coordination in symmetric tasks like the XOR game.
CPCANet is a domain generalization framework that uses Common Principal Component Analysis to discover structured domain-invariant subspaces, achieving state-of-the-art performance in zero-shot transfer.