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cs.LG2026
Stepped MoE: Segment-Level Routing with Configurable Inference Complexity
Arnav Kundu, Zhaoyang Xu, Bairu Hou +3
Training large language models (LLMs) is resource-intensive, and adapting them for diverse deployment scenarios with varying computational constraints remains challenging. While el…
cs.CL2026
CompliBench: Benchmarking LLM Judges for Compliance Violation Detection in Dialogue Systems
Jingbo Yang, Guanyu Yao, Bairu Hou +5
As Large Language Models (LLMs) are increasingly deployed as task-oriented agents in enterprise environments, ensuring their strict adherence to complex, domain-specific operationa…
cs.AI2026
Ares: Adaptive Reasoning Effort Selection for Efficient LLM Agents
Jingbo Yang, Bairu Hou, Wei Wei +2
Modern agents powered by thinking LLMs achieve high accuracy through long chain-of-thought reasoning but incur substantial inference costs. While many LLMs now support configurable…