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Xitong Gao

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#artificial intelligence Preprint Oct 2026

iS-KV: Online Low-Rank KV Cache Compression via Block-Incremental SVD

Long chain-of-thought reasoning substantially increases KV-cache memory during autoregressive decoding, as every generated token introduces new key and value states and causes the cache to grow linearly with decoding length. Existing KV-cache compression methods typically control this growth through token eviction, but...

Yi-Ren Zhao, Guang-Hui Song, Tianrui Qin et al. · 0 citations
#artificial intelligence Preprint Sep 2026

A2M: Trace-Optimized Agent Hijacking in the MCP Ecosystem

Agents using the Model Context Protocol (MCP) rely on semantic matching to select tools from third-party servers, exposing a semantic supply-chain risk through attacker-controlled metadata and outputs. We introduce A2M (Attraction-to-Manipulation), a two-stage black-box framework for hijacking MCP agents. The Attractio...

Lai-Zhen Li, Xuan Wang, Pei-Cheng Zhao et al. · 0 citations
#artificial intelligence Preprint Sep 2026

Grow the Harness, Not the Context: From Strategy-Free Scaffolds to Reusable Specialist Agents

Large language model (LLM) agents often handle streams of related tasks, yet standard harnesses repeatedly ask the model to reconstruct the same control decisions inside each task's context. We study whether task feedback can instead turn recurring control into reusable executable code, while reserving LLM calls for ta...

Lai-Zhen Li, Jia-Rui Li, Juanjuan Zhao et al. · 1 citation
Preprint Jul 2026

CoCoScale: Leveraging Layer-wise Scaling to Unlock the Potential of Online LLM Serving

CoScale is proposed, a layer-wise dynamic scaling mechanism that selectively expands the parallelism of hot layers onto idle resources reclaimed from underutilized devices, enabling elastic data parallelism without altering model architectures or adding hardware overhead.

Jingfeng Wu, Yiyuan He, Minxian Xu et al. · 0 citations

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