提出联合训练策略与世界观模型的新方法，让语言智能体在复杂任务中表现更佳。
arXiv:2606.02388v1 Announce Type: new Abstract: Reinforcement learning (RL) improves large language model (LLM) agents by teaching them which actions …
首个孟加拉语大模型多任务幻觉评估框架，填补低资源语言评测空白
arXiv:2605.31483v1 Announce Type: new Abstract: Despite Bengali being the sixth most spoken language in the world, no prior work has systematically ev…
视网膜影像结合可解释多任务学习，揭示微血管信号用于2型糖尿病全身风险分层，AI医疗新突破。
arXiv:2605.24913v1 Announce Type: cross Abstract: Retinal imaging provides a non-invasive window into systemic microvascular health and has emerged as…
多任务微调新方法，用连续提示优化实现参数高效的大模型适配，减少数据需求。
arXiv:2605.14055v1 Announce Type: cross Abstract: Parameter-Efficient Fine-Tuning (PEFT) is widely used for adapting Large Language Models (LLMs) for …
提出Flow-OPD新方法，用同策略蒸馏解决流匹配模型在多任务对齐中的奖励稀疏和梯度干扰问题。
arXiv:2605.08063v3 Announce Type: replace-cross Abstract: Existing Flow Matching (FM) text-to-image models suffer from two critical bottlenecks under …
设计师兼开发者吐槽多角色切换的沮丧日常，道出创意工作者的普遍痛点
Today I’m struggling with context-switching as I’m hopping wildly between front-end development to visual design and icon alignment back to copywritin…
打破传统荧光标记依赖，多任务学习与混合架构（CNN+Transformer+LLM）让无标记单细胞成像同时完成白细胞分类和蛋白表达预测，为高通量血液分析开辟了低成本、可解释的新路径。
arXiv:2605.14717v1 Announce Type: cross Abstract: Label-free single-cell imaging offers a scalable, non-invasive alternative to fluorescence-based cyt…