3 papers
cs.CL2026
Data-Efficient Language Modeling: From Frontier Advancement to Principle-Guided Model Improvement
Shuxing Yang, Kaihao Zhu, Junjie Yang +13
Learning from limited text requires models to use context, generalize to new inputs, and retain useful capabilities. Qiushi Engine conducted a long-horizon, end-to-end autonomous r…
cs.AI2026
Learning to Predict Middle-Layer Attention in MLLMs for Visual Token Pruning
Yuyao Sun, Tao Deng, Shuang Li +3
Multimodal large language models (MLLMs) achieve strong performance across diverse vision-language tasks, but their efficiency is limited by the cost of processing numerous visual…
cs.AI2026
Qiushi Engine on AstaBench E2E-Bench-Hard
Wenhao Li, Shuxing Yang, Fujia Chen +13
This report analyzes Qiushi Engine v0.8 across all 40 test tasks in AstaBench E2E-Bench-Hard, a benchmark that requires autonomous agents to carry a research question through exper…