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cs.AI2026

RadixFlow: Filling Execution Bubbles in Prefix-Cached Hybrid LLM Serving

Huihao Jing, Wenbin Hu, Shaojin Chen +6

Prefix reuse improves LLM inference by sharing the KV cache of common prompt prefixes. This helps only if the scheduler can execute a matched branch in the current worker round. Sc…

cs.AI2026

Same Operation, Different Permission: Evaluating Whether Guardrails Honor Authorization

Huihao Jing, Shaojin Chen, Wenbin Hu +5

As language-model agents write code, move money and change records on behalf of users, deciding whether an action is authorized has become a central safety problem. Guardrails are…

cs.AI2026

AuthorityLens: Rethinking LLM-Based Agent Systems Through the Lens of Authority

Shaojin Chen, Huihao Jing, Wun Yu Chan +7

LLM-based agents are increasingly deployed with authority over consequential resources and decisions in real systems. These agents often operate alongside human and LLM-based parti…

cs.AI2026

Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions

Huihao Jing, Wenbin Hu, Shaojin Chen +10

The capability of LLM agents to function as the ``brain'' of a system fundamentally expands the scope of analysis beyond a standalone model. Consequently, safety is no longer only…

cs.AI2026

Do Reasoning Models Enhance Embedding Models?

Wun Yu Chan, Shaojin Chen, Huihao Jing +5

State-of-the-art embedding models are increasingly derived from decoder-only Large Language Model (LLM) backbones adapted via contrastive learning. Given the emergence of reasoning…