We present Nanbeige4.1-3B, a unified generalist language model that simultaneously achieves strong agentic behavior, code generation, and general reasoning with only 3B parameters. To the best of our knowledge, it is the first open-source small language model (SLM) to achieve such versatility in a single model. To improve reasoning and preference alignment, we combine point-wise and pair-wise reward modeling, ensuring high-quality, human-aligned responses. For code generation, we design complexity-aware rewards in Reinforcement Learning, optimizing both correctness and efficiency. In deep search, we perform complex data synthesis and incorporate turn-level supervision during training. This enables stable long-horizon tool interactions, allowing Nanbeige4.1-3B to reliably execute up to 600 tool-call turns for complex problem-solving. Extensive experimental results show that Nanbeige4.1-3B significantly outperforms prior models of similar scale, such as Nanbeige4-3B-2511 and Qwen3-4B, even achieving superior performance compared to much larger models, such as Qwen3-30B-A3B. Our results demonstrate that small models can achieve both broad competence and strong specialization simultaneously, redefining the potential of 3B parameter models.
DeShortcut-Align: Decoupling Spurious Shortcuts for Robust Safety Alignment in Large Reasoning Models
The State Key Laboratory of Blockchain and Data Security, Zhejiang University（浙江大学区块链与数据安全全国重点实验室）；Ant Group（蚂蚁集团）；Chongqing Ant Consumer Finance Co., Ltd（重庆蚂蚁消费金融有限公司）
Hit-RAG: Learning to Reason with Long Contexts via Preference Alignment
Tongji University（同济大学）；The City University of New York（纽约城市大学）；University of Technology Sydney（悉尼大学）；Huazhong University of Science and Technology（华中科技大学）；Shenzhen University of Advanced Technology（深圳先进技术大学）
Beyond representational alignment with brain-guided language models for robust reasoning
State Key Lab of General AI, School of Intelligence Science and Technology, Peking University（北京大学通用人工智能国家重点实验室、智能科学与技术学院）；Department of Psychological and Cognitive Sciences, Tsinghua University（清华大学心理与认知科学系）；Microsoft Research Asia（微软亚洲研究院）
Evo-PI: Aligning Medical Reasoning via Evolving Principle-Guided Supervision
School of Computer Science, University of Auckland（奥克兰大学计算机科学学院）；Beijing University of Posts and Telecommunications（北京邮电大学）；Renyixun Health Technology Co., Ltd.（仁医讯健康科技有限公司）；National Yang Ming Chiao Tung University（国立阳明交通大学）；Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳））
Human-Aligned Bench: Fine-Grained Assessment of Reasoning Ability in MLLMs vs. Humans
Wuhan University（武汉大学）；Shanghai Artificial Intelligence Laboratory（上海人工智能实验室）；Shanghai Innovation Institute（上海创新研究院）；Harbin Institute of Technology（哈尔滨工业大学）
Deliberative Alignment is Deep, but Uncertainty Remains: Inference time safety improvement in reasoning via attribution of unsafe behavior to base model
