LLM Routing

LLM: Large Language Model

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30 papers in the last four weeks, up 88% on the four weeks before. 0.3% of all new papers.

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RA-MoE: Routing-Aligned Fine-Tuning for Multilingual Adaptation of Mixture-of-Experts Models
May 27, 2026Guanzhi Deng, Kuan Wu, Haibo Wang +6Mixture-of-Experts Language Models LLM Fine-Tuning
City University of Hong Kong, Hong Kong, China · Carnegie Mellon University, Pittsburgh, USA · The University of Hong Kong, Hong Kong, China
The Coverage Illusion: From Pre-retrieval Routing Failure to Post-retrieval Cascades in a Production RAG System
May 26, 2026Zafar Hussain, Kristoffer NielboLLM Inference Efficiency Retrieval-Augmented Generation
Aarhus University, Denmark
ReMoE: Boosting Expert Reuse through Router Fine-Tuning in Memory-Constrained MoE LLM Inference
May 26, 2026Xiongwei Zhu, Xiaojian Liao, Tianyang Jiang +3LLM Inference Efficiency Expert Offloading
School of Computer Science and Engineering, Beihang University, Beijing 100191, China · Huawei Technologies Ltd.
Beyond Query Memorization: Large Language Model Routing with Query Decomposition and Historical Matching
May 25, 2026Bo Lv, Jingbo SunOOD Generalization Question Decomposition
Tencent Hunyuan · University of Chinese Academy of Sciences
SeqRoute: Global Budget-Aware Sequential LLM Routing via Offline Reinforcement Learning
May 25, 2026Zhongling Xu, Shunan Zheng, Wei WangCost-Aware Inference Offline RL
Department of Operations Research and Industrial Engineering The University of Texas at Austin Austin, TX 78712
Learning to Route Languages for Multilingual Policy Optimization
May 25, 2026Geyang Guo, Hiromi Wakaki, Yuki Mitsufuji +2Multilingual Language Models RL for Language Models
Georgia Institute of Technology · Sony Group Corporation · Sony AI
Hera: Learning Long-Horizon Coordination for Device-Cloud Collaborative LLM Agents
May 23, 2026Yuxin Zhang, Mengxue Hu, Zheng Lin +8LLM Agent Training LLM Routing
1Fudan University · 2Alibaba Group · 3The University of Hong Kong +4
Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts
May 22, 2026Md Nurul Absar SiddikyMixture-of-Experts Language Models Expert Routing
Department of Electrical and Computer Engineering University of Hawai’i at M¯anoa Honolulu, HI, USA
XWind: A Cross-site Router for Large Language Model Inference Serving at Renewable Energy Farms
May 22, 2026Tella Rajashekhar Reddy, Atharva Deshmukh, Liangcheng Yu +7Energy-Efficient ML LLM Inference Serving
Microsoft
ModeSwitch-LLM: A Lightweight Phase-Aware Controller for Cross-Mode LLM Inference on a Single GPU
May 21, 2026Aman Sunesh, Ali Alshehhi, Hivansh DhakneLLM Inference Efficiency LLM Serving
Department of Computer Engineering NYU Abu Dhabi Abu Dhabi, United Arab Emirates · Courant Institute of Mathematical Sciences New York University New York, United States · Department of Computer Engineering New York University New York, United States
APM: Evaluating Style Personalization in LLMs with Arbitrary Preference Mappings
May 20, 2026Philipp Spohn, Leander Girrbach, Zeynep AkataLLM Evaluation LLM Personalization
Technical University of Munich, Helmholtz Munich · Munich Center for Machine Learning (MCML)
MMoA: An AI-Agent framework with recurrence for Memoried Mixure-of-Agent
May 18, 2026Rui ChuLLM Inference Acceleration Multi-Agent Systems
LogRouter: Adaptive Two-Level LLM Routing for Log Question Answering in Big Data Systems
May 18, 2026Mert Coskuner, Merve Zeybel, Melik Mert DolanLLM Inference Efficiency Cost-Aware Inference
TUBITAK BILGEM · Kocaeli, Turkey
Mixture of Experts for Low-Resource LLMs
May 17, 2026Ori Bar Joseph, Smadar Arvatz, Noam Kayzer +2Mixture-of-Experts Language Models Expert Routing
HyDRA: Hybrid Dynamic Routing Architecture for Heterogeneous LLM Pools
May 16, 2026Aashna Garg, Siddharth Singha Roy, Jinu Jang +2Cost-Aware Inference LLM Routing
Microsoft
Reasoning Can Be Restored by Correcting a Few Decision Tokens
May 16, 2026Changshuo Shen, Leheng Sheng, Yuxin Chen +2Efficient Language Model Reasoning Inference-Time Compute Allocation
University of Science and Technology of China, Hefei, China · National University of Singapore, Singapore
Contexting as Recommendation: Evolutionary Collaborative Filtering for Context Engineering
May 15, 2026Jiachen Zhu, Zhuoying Ou, Congmin Zheng +9LLM Prompting LLM Routing
Shanghai Jiao Tong Univ. · Univ. College London · Carnegie Mellon Univ. +1
BEAM: Binary Expert Activation Masking for Dynamic Routing in MoE
May 14, 2026Juntong Wu, Jialiang Cheng, Qishen Yin +5Sparse Mixture-of-Experts Mixture-of-Experts Inference
Taobao & Tmall Group of Alibaba · Shenzhen Graduate School, Peking University
CR^2: Cost-Aware Risk-Controlled Routing for Wireless Device-Edge LLM Inference
May 12, 2026Nan Xue, Shengkang Chen, Zhiyong Chen +4On-Device Language Model Inference LLM Inference
Cooperative Medianet Innovation Center, Shanghai Jiao Tong University, Shanghai 200240, China · Department of Broadband Communication, Pengcheng Laboratory, Shenzhen 518000, China · Future Network of Intelligent Institute (FNii), the Chinese University of Hong Kong (Shenzhen), Shenzhen 518172, China +1
GAR: Carbon-Aware Routing for LLM Inference via Constrained Optimization
May 12, 2026Disha Sheshanarayana, Rajat Subhra Pal, Manjira Sinha +1LLM Inference Efficiency Constrained Optimization
Manipal University Jaipur · TCS Research
LatentRouter: Can We Choose the Right Multimodal Model Before Seeing Its Answer?
May 11, 2026Xueqi Cheng, Yushun DongEfficient Multimodal Inference Multimodal Large Language Models
Department of Computer Science Florida State University University
Reasoning Is Not Free: Robust Adaptive Cost-Efficient Routing for LLM-as-a-Judge
May 11, 2026Wenbo Zhang, Lijinghua Zhang, Liner Xiang +1LLM-as-a-Judge Cost-Aware Inference
Department of Statistics, University of California, Irvine, USA.
Route Before Retrieve: Activating Latent Routing Abilities of LLMs for RAG vs. Long-Context Selection
May 11, 2026Yiwen Chen, Kuan Li, Fuzhen Zhuang +6LLM Prompting Long-Context Modeling
Beihang University · HKUST · Alibaba Group +1
UCCI: Calibrated Uncertainty for Cost-Optimal LLM Cascade Routing
May 11, 2026Varun KotteCost-Aware Inference Language Model Calibration
Independent Researcher.
A Communication-Theoretic Framework for LLM Agents: Cost-Aware Adaptive Reliability
May 9, 2026Hamed Omidvar, Vahideh AkhlaghiLLM Inference Efficiency AI Agent Reliability
INTELLERCE LLC San Jose, CA, USA
Iterative Critique-and-Routing Controller for Multi-Agent Systems with Heterogeneous LLMs
May 9, 2026Wenzhi Fang, Liangqi Yuan, Guangchen Lan +2Multi-Agent LLM Systems Multi-Agent Coordination
Purdue University · Yonsei University
Large Language Models over Networks: Collaborative Intelligence under Resource Constraints
May 9, 2026Liangqi Yuan, Wenzhi Fang, Shiqiang Wang +2LLM Inference Efficiency On-Device Language Model Inference
L. Yuan, W. Fang, and C. G. Brinton are with Purdue University, IN, USA. · S. Wang is with University of Exeter, UK. · H. V. Poor is with Princeton University, USA.
Unsolvability Ceiling in Multi-LLM Routing: An Empirical Study of Evaluation Artifacts
May 8, 2026Saloni Garg, Amit SagtaniLLM Evaluation LLM-as-a-Judge
Independent Researcher San Francisco, California, USA · San Francisco State University San Francisco, California, USA
When Are Experts Misrouted? Counterfactual Routing Analysis in Mixture-of-Experts Language Models
May 8, 2026Youngsik Yoon, Siwei Wang, Wei Chen +1Mixture-of-Experts Language Models LLM Routing
Department of Computer Science and Engineering, POSTECH, South Korea · Microsoft Research Asia, Beijing, China · Graduate School of Artificial Intelligence, POSTECH, South Korea
Switchcraft: AI Model Router for Agentic Tool Calling
May 8, 2026Sharad Agarwal, Pooria Namyar, Alec Wolman +3Tool-Augmented Language Model Agents Cost-Aware Inference
Microsoft Research · Microsoft · Stanford

May 27, 2026, cs.CLJ/K move · Enter open · S save

RA-MoE: Routing-Aligned Fine-Tuning for Multilingual Adaptation of Mixture-of-Experts Models

Guanzhi Deng, Kuan Wu, Haibo Wang, Shing Yin Wong+5

City University of Hong Kong, Hong Kong, China · Carnegie Mellon University, Pittsburgh, USA · The University of Hong Kong, Hong Kong, China

Mixture-of-Experts Language Models LLM Fine-Tuning LLM Routing Mixture-of-Experts Models

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Mixture-of-Experts (MoE) models enable efficient LLM scaling, yet adapting them to non-English downstream tasks remains challenging. Standard multilingual fine-tuning largely ignores their heterogeneous routing structure. Across multiple MoE models and tasks, we find strong cross-lingual routing alignment in middle layers, with routing divergence associated with target-language performance gaps. Motivated by this observation, we propose RA-MoE (Routing-Aligned MoE Fine-Tuning), a three-stage framework for multilingual MoE adaptation. RA-MoE categorizes parallel examples into four correctness groups (cc/ci/ic/ii) and identifies task-relevant experts in middle layers. It then selectively aligns target-language routing on ci examples toward successful English routing patterns, jointly matching the total routing mass assigned to task experts and its relative allocation among them. Experiments across three MoE models, three downstream tasks, and six target languages show that RA-MoE consistently outperforms standard SFT and strong routing-aware baselines. Further analyses confirm the intended routing changes and reveal that middle-layer task routing is largely shared and transferable across languages, providing mechanistic evidence for the cross-language transferability of task-specific routing.

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Latest papers 224