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20242026
most citedGLM-5: from Vibe Coding to Agentic Engineering

1 citations · 2 across the 8 of their papers we have counts for

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cs.LG2026

PulseInfer: I/O-Centric Sparse KV Cache Offloading for Efficient Long-Context LLM Decoding

Qiuyang Zhang, Kai Zhou, Kai Lu +6

Long-context LLM serving is increasingly bottlenecked by decode, where large KV caches limit batch size and underutilize GPUs. Sparse KV cache offloading expands effective capacity…

cs.LG2026

ScoutAttention: Efficient KV Cache Offloading via Layer-Ahead CPU Pre-computation for LLM Inference

Qiuyang Zhang, Kai Zhou, Ding Tang +5

Large language models encounter critical GPU memory capacity constraints during long-context inference, where KV cache memory consumption severely limits decode batch sizes. While…

cs.LG2026★ 1 cited

GLM-5: from Vibe Coding to Agentic Engineering

GLM-5-Team, :, Aohan Zeng +184

We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…

cs.SE2026

CodeCircuit: Toward Inferring LLM-Generated Code Correctness via Attribution Graphs

Yicheng He, Zheng Zhao, Zhou Kaiyu +3

Current paradigms for code verification rely heavily on external mechanisms-such as execution-based unit tests or auxiliary LLM judges-which are often labor-intensive or limited by…

cs.CR2026

Beyond Max Tokens: Stealthy Resource Amplification via Tool Calling Chains in LLM Agents

Kaiyu Zhou, Yongsen Zheng, Yicheng He +5

The agent--tool interaction loop is a critical attack surface for modern Large Language Model (LLM) agents. Existing denial-of-service (DoS) attacks typically function at the user-…