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cs.CL2026
ATLAS: All-round Testing of Long-context Abilities across Scales
Deli Huang, Cunguang Wang, Hongyin Tang +15
Long-context language models now advertise context windows up to millions of tokens, yet evaluations typically report a single length or a narrow task family, masking two failure m…
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.CL2024
Look Before You Leap: Towards Decision-Aware and Generalizable Tool-Usage for Large Language Models
Anchun Gui, Jian Li, Yong Dai +2
Tool-augmented large language models (LLMs) are attracting widespread attention when accessing up-to-date knowledge and alleviating hallucination issues. Nowadays, advanced closed-…