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Routing large language models (LLMs) is a new paradigm that uses a router to recommend the best LLM from a pool of candidates for a given input.
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Domain adaptation for robust model routing
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MatFormer: Nested transformer for elastic inference
Fnu Devvrit, Sneha Kudugunta, Aditya Kusupati, Tim Dettmers, Kaifeng Chen, Inderjit S Dhillon, Yulia Tsvetkov, Hannaneh Hajishirzi, Sham M. Kakade, Ali Farhadi, and Prateek Jain. 2024 · 2024
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Yixin Liu and Pengfei Liu. 2021 · 2021
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Uniform convergence may be unable to explain generalization in deep learning
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Winogrande: An adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi. 2021 · 2021
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Contrastive learning for cold-start recommendation
Yinwei Wei, Xiang Wang, Qi Li, Liqiang Nie, Yan Li, Xuanping Li, and Tat-Seng Chua. 2021 · 2021
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Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
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Autoemb: Automated embedding dimensionality search in streaming recommendations
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DiPaCo: Distributed path composition
Arthur Douillard, Qixuan Feng, Andrei A. Rusu, Adhiguna Kuncoro, Yani Donchev, Rachita Chhaparia, Ionel Gog, Marc’Aurelio Ranzato, Jiajun Shen, and Arthur Szlam. 2024 · 2024
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GraphRouter: A graph-based router for llm selections
Tao Feng, Yanzhen Shen, and Jiaxuan You. 2024 · 2024
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Arcee’s mergekit: A toolkit for merging large language models
Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, Luke Meyers, Vladimir Karpukhin, Brian Benedict, Mark McQuade, and Jacob Solawetz. 2024 · 2024
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Model merging and safety alignment: One bad model spoils the bunch
Hasan Abed Al Kader Hammoud, Umberto Michieli, Fabio Pizzati, Philip Torr, Adel Bibi, Bernard Ghanem, and Mete Ozay. 2024 · 2024
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RouterBench: A benchmark for multi-LLM routing system
Qitian Jason Hu, Jacob Bieker, Xiuyu Li, Nan Jiang, Benjamin Keigwin, Gaurav Ranganath, Kurt Keutzer, and Shriyash Kaustubh Upadhyay. 2024b · 2024
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Attns: Attention-inspired numerical solving for limited data scenarios
Zhongzhan Huang, Mingfu Liang, Shanshan Zhong, and Liang Lin. 2024 · 2024
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Model stock: All we need is just a few fine-tuned models
Dong-Hwan Jang, Sangdoo Yun, and Dongyoon Han. 2024 · 2024
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Albert Q Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, et al. 2024 · 2024
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Prometheus 2: An open source language model specialized in evaluating other language models
Seungone Kim, Juyoung Suk, Shayne Longpre, Bill Yuchen Lin, Jamin Shin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, and Minjoon Seo. 2024 · 2024
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OrchestraLLM: Efficient orchestration of language models for dialogue state tracking
Chia-Hsuan Lee, Hao Cheng, and Mari Ostendorf. 2024 · 2024
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Optllm: Optimal assignment of queries to large language models
Yueyue Liu, Hongyu Zhang, Yuantian Miao, Van-Hoang Le, and Zhiqiang Li. 2024 · 2024
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Routoo: Learning to route to large language models effectively
Alireza Mohammadshahi, Arshad Rafiq Shaikh, and Majid Yazdani. 2024 · 2024
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Fisher mask nodes for language model merging
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Metallm: A high-performant and cost-efficient dynamic framework for wrapping llms
Quang H Nguyen, Duy C Hoang, Juliette Decugis, Saurav Manchanda, Nitesh V Chawla, and Khoa D Doan. 2024 · 2024
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RouteLLM: Learning to route LLMs with preference data
Isaac Ong, Amjad Almahairi, Vincent Wu, Wei-Lin Chiang, Tianhao Wu, Joseph E. Gonzalez, M Waleed Kadous, and Ion Stoica. 2024 · 2024
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Mechanistic design and scaling of hybrid architectures
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An introspective data augmentation method for training math word problem solvers
Jinghui Qin, Zhongzhan Huang, Ying Zeng, Quanshi Zhang, and Liang Lin. 2024 · 2024
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Optimising calls to large language models with uncertainty-based two-tier selection
Guillem Ramírez, Alexandra Birch, and Ivan Titov. 2024 · 2024
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Gpqa: A graduate-level google-proof q&a benchmark
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R Bowman. 2024 · 2024
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Fly-swat or cannon? cost-effective language model choice via meta-modeling
Marija Šakota, Maxime Peyrard, and Robert West. 2024 · 2024
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Harnessing the power of multiple minds: Lessons learned from llm routing
KV Srivatsa, Kaushal Kumar Maurya, and Ekaterina Kochmar. 2024 · 2024
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Zipit! merging models from different tasks without training
George Stoica, Daniel Bolya, Jakob Bjorner, Pratik Ramesh, Taylor Hearn, and Judy Hoffman. 2024 · 2024
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TensorOpera router: A multi-model router for efficient LLM inference
Dimitris Stripelis, Zijian Hu, Jipeng Zhang, Zhaozhuo Xu, Alay Dilipbhai Shah, Han Jin, Yuhang Yao, Salman Avestimehr, and Chaoyang He. 2024 · 2024
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Branch-train-mix: Mixing expert llms into a mixture-of-experts llm
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Knowledge fusion of large language models
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Mmlu-pro: A more robust and challenging multi-task language understanding benchmark
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Language models are super mario: Absorbing abilities from homologous models as a free lunch
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Large language model cascades with mixture of thought representations for cost-efficient reasoning
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LoraRetriever: Input-aware LoRA retrieval and composition for mixed tasks in the wild
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Mirror gradient: Towards robust multimodal recommender systems via exploring flat local minima
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Evan Frick, Connor Chen, Joseph Tennyson, Tianle Li, Wei-Lin Chiang, Anastasios N Angelopoulos, and Ion Stoica. 2025 · 2025
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Universal model routing for efficient llm inference
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