22 citations · 23 across the 19 of their papers we have counts for
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cs.CL2026
Efficient Context Scaling with LongCat ZigZag Attention
Chen Zhang, Yang Bai, Jiahuan Li +19
We introduce LongCat ZigZag Attention (LoZA), which is a sparse attention scheme designed to transform any existing full-attention models into sparse versions with rather limited c…
cs.CL2026
Reasoning While Asking: Transforming Reasoning Large Language Models from Passive Solvers to Proactive Inquirers
Xin Chen, Feng Jiang, Yiqian Zhang +5
Reasoning-oriented Large Language Models (LLMs) have achieved remarkable progress with Chain-of-Thought (CoT) prompting, yet they remain fundamentally limited by a \emph{blind self…
cs.CL2025
Gradient Co-occurrence Analysis for Detecting Unsafe Prompts in Large Language Models
Jingyuan Yang, Bowen Yan, Rongjun Li +4
Unsafe prompts pose significant safety risks to large language models (LLMs). Existing methods for detecting unsafe prompts rely on data-driven fine-tuning to train guardrail model…