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cs.LG2025
Long-Context Attention Benchmark: From Kernel Efficiency to Distributed Context Parallelism
Tao Bu, Qiangang Wang, Bowen Zeng +4
Transformer-based large language models (LLMs) have achieved remarkable success, yet their standard attention mechanism incurs quadratic computation and memory costs with respect t…
cs.LG2025★ 1 cited
Marco-o1 v2: Towards Widening The Distillation Bottleneck for Reasoning Models
Huifeng Yin, Yu Zhao, Minghao Wu +9
Large Reasoning Models(LRMs) such as OpenAI o1 and DeepSeek-R1 have shown remarkable reasoning capabilities by scaling test-time compute and generating long Chain-of-Thought(CoT).…