3 citations · 5 across the 19 of their papers we have counts for
17 papers · 1 filter
REFACT: Adaptive Fact Restatement for Compact and Faithful Chain-of-Thought Reasoning
Zhensheng Jin, Xin Dai, Zhenghao Liu +5
Large Language Models (LLMs) increasingly leverage long-form reasoning to solve complex tasks, yet their reasoning processes can deviate from the provided context when evidence is…
Beyond Reward Engineering: A Data Recipe for Long-Context Reinforcement Learning
Xiaoyue Xu, Sikui Zhang, Xiaorong Wang +2
Long-context reasoning is an essential capability for large language models, particularly when they are deployed as autonomous agents that must reason over lengthy trajectories. Re…
Rethinking the Role of Efficient Attention in Hybrid Architectures
Ziqing Qiao, Yinuo Xu, Chaojun Xiao +6
Modern language models increasingly adopt hybrid architectures that combine full attention with efficient attention modules, such as sliding-window attention (SWA) and recurrent se…
MiniCPM-o 4.5: Towards Real-Time Full-Duplex Omni-Modal Interaction
Junbo Cui, Bokai Xu, Chongyi Wang +33
Recent progress in multimodal large language models (MLLMs) has brought AI capabilities from static offline data processing to real-time streaming interaction, yet they still remai…
Student-in-the-Loop Chain-of-Thought Distillation via Generation-Time Selection
Chaoqun He, Yingfa Chen, Chaojun Xiao +2
Large reasoning models achieve strong performance on complex tasks through long chain-of-thought (CoT) trajectories, but directly transferring such reasoning processes to smaller m…
MiniCPM-SALA: Hybridizing Sparse and Linear Attention for Efficient Long-Context Modeling
MiniCPM Team, Wenhao An, Yingfa Chen +44
The evolution of large language models (LLMs) towards applications with ultra-long contexts faces challenges posed by the high computational and memory costs of the Transformer arc…