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11pp. Real executed benchmark numbers (enso-bench results/*.json via emit_paper.py): GPQA-Diamond enso 87.9 / ultra 90.4, HLE 29.4/29.2, LiveCodeBench 91.4/85.1, CharXiv 78.0/81.5, with per-benchmark metered costs. Includes routing-overhead, economics (1% aligned meter), and honest-reporting/limitations sections. PDF rebuilt fresh against the v2 verify-then-select results (committed PDF was stale).
245 lines
9.2 KiB
BibTeX
245 lines
9.2 KiB
BibTeX
% =====================================================================
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% Enso paper bibliography.
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% Hanzo internal artifacts + real external literature. No fabricated
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% author lists: where a paper's individual authors are not known to us
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% (e.g. Sakana's ICLR foundations), the institutional author is used.
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% =====================================================================
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% ---- Hanzo internal ----
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@misc{ensoengine,
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author = {{Hanzo Industries}},
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title = {{enso: Learned SLO-Constrained Routing Policy for hanzo-router}},
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howpublished = {\url{https://github.com/hanzoai/engine}},
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year = {2026}
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}
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@misc{hanzorouterpaper,
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author = {Zach Kelling},
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title = {{Hanzo Router: Memory-Aware, Local-First LLM Routing with a
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Learned SLO-Constrained Policy}},
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howpublished = {Hanzo Research},
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year = {2026}
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}
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@misc{hanzoengine,
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author = {{Hanzo Industries}},
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title = {{hanzo-engine: An OpenAI-Compatible LLM Inference Engine in Rust}},
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howpublished = {\url{https://github.com/hanzoai/engine}},
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year = {2026}
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}
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@misc{hanzogateway,
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author = {{Hanzo Industries}},
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title = {{Hanzo AI Gateway: One \texttt{/v1} API over a Discovered Model Fleet}},
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howpublished = {\url{https://api.hanzo.ai}},
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year = {2026}
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}
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@misc{zenrouter,
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author = {{Zen LM}},
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title = {{zen-router: A 0.6B Trainable Routing Model}},
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howpublished = {\url{https://github.com/zenlm/zen-router}},
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year = {2026}
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}
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% ---- The foil: Sakana AI Fugu and its ICLR foundations ----
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@misc{fugu,
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author = {{Sakana AI}},
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title = {{Fugu: A Learned Orchestrator over Frontier Language Models}},
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howpublished = {arXiv preprint arXiv:2606.21228, \url{https://sakana.ai/fugu-release}},
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year = {2026}
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}
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@inproceedings{trinity,
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author = {{Sakana AI}},
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title = {{Trinity: Evolutionary Composition of Language Model Experts}},
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booktitle = {International Conference on Learning Representations (ICLR)},
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year = {2026}
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}
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@inproceedings{conductor,
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author = {{Sakana AI}},
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title = {{Conductor: Reinforcement-Learned Orchestration of Model Ensembles}},
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booktitle = {International Conference on Learning Representations (ICLR)},
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year = {2026}
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}
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% ---- LLM routing and cascading ----
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@misc{routellm,
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author = {Isaac Ong and Amjad Almahairi and Vincent Wu and Wei-Lin Chiang and
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Tianhao Wu and Joseph E. Gonzalez and M. Waleed Kadous and Ion Stoica},
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title = {{RouteLLM: Learning to Route LLMs with Preference Data}},
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howpublished = {arXiv preprint arXiv:2406.18665},
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year = {2024}
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}
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@article{frugalgpt,
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author = {Lingjiao Chen and Matei Zaharia and James Zou},
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title = {{FrugalGPT: How to Use Large Language Models While Reducing Cost
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and Improving Performance}},
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journal = {arXiv preprint arXiv:2305.05176},
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year = {2023}
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}
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@inproceedings{hybridllm,
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author = {Dujian Ding and Ankur Mallick and Chi Wang and Robert Sim and
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Subhabrata Mukherjee and Victor R{\"u}hle and
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Laks V. S. Lakshmanan and Ahmed Hassan Awadallah},
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title = {{Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing}},
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booktitle = {International Conference on Learning Representations (ICLR)},
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year = {2024}
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}
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@article{automix,
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author = {Aman Madaan and Pranjal Aggarwal and Ankit Anand and
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Srividya Pranavi Potharaju and Swaroop Mishra and Pei Zhou and
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Aditya Gupta and Dheeraj Rajagopal and Karthik Kappaganthu and
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Yiming Yang and Shyam Upadhyay and Mausam and Manaal Faruqui},
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title = {{AutoMix: Automatically Mixing Language Models}},
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journal = {arXiv preprint arXiv:2310.12963},
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year = {2023}
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}
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@inproceedings{tabi,
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author = {Yiding Wang and Kai Chen and Haisheng Tan and Kun Guo},
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title = {{Tabi: An Efficient Multi-Level Inference System for Large
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Language Models}},
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booktitle = {Proceedings of the 18th European Conference on Computer Systems
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(EuroSys)},
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year = {2023},
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pages = {233--248},
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publisher = {ACM}
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}
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% ---- Multi-agent / ensemble synthesis (Enso Ultra) ----
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@inproceedings{moa,
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author = {Junlin Wang and Jue Wang and Ben Athiwaratkun and Ce Zhang and
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James Zou},
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title = {{Mixture-of-Agents Enhances Large Language Model Capabilities}},
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booktitle = {International Conference on Learning Representations (ICLR)},
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year = {2025}
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}
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@inproceedings{llmblender,
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author = {Dongfu Jiang and Xiang Ren and Bill Yuchen Lin},
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title = {{LLM-Blender: Ensembling Large Language Models with Pairwise
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Ranking and Generative Fusion}},
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booktitle = {Proceedings of the 61st Annual Meeting of the Association for
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Computational Linguistics (ACL)},
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year = {2023}
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}
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@inproceedings{selfconsistency,
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author = {Xuezhi Wang and Jason Wei and Dale Schuurmans and Quoc Le and
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Ed H. Chi and Sharan Narang and Aakanksha Chowdhery and Denny Zhou},
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title = {{Self-Consistency Improves Chain of Thought Reasoning in
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Language Models}},
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booktitle = {International Conference on Learning Representations (ICLR)},
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year = {2023}
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}
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% ---- Learning machinery ----
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@inproceedings{linucb,
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author = {Lihong Li and Wei Chu and John Langford and Robert E. Schapire},
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title = {{A Contextual-Bandit Approach to Personalized News Article
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Recommendation}},
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booktitle = {Proceedings of the 19th International Conference on World Wide Web
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(WWW)},
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year = {2010},
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pages = {661--670},
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publisher = {ACM}
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}
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@article{ridge,
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author = {Arthur E. Hoerl and Robert W. Kennard},
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title = {{Ridge Regression: Biased Estimation for Nonorthogonal Problems}},
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journal = {Technometrics},
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volume = {12},
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number = {1},
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pages = {55--67},
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year = {1970},
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publisher = {Taylor \& Francis}
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}
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@article{grpo,
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author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and
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Junxiao Song and Xiao Bi and Haowei Zhang and Mingchuan Zhang and
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Y. K. Li and Y. Wu and Daya Guo},
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title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in
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Open Language Models}},
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journal = {arXiv preprint arXiv:2402.03300},
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year = {2024}
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}
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@article{sepcmaes,
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author = {Raymond Ros and Nikolaus Hansen},
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title = {{A Simple Modification in CMA-ES Achieving Linear Time and Space
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Complexity}},
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journal = {Parallel Problem Solving from Nature (PPSN X), LNCS 5199},
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pages = {296--305},
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year = {2008},
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publisher = {Springer}
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}
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% ---- Benchmarks ----
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@inproceedings{swebench,
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author = {Carlos E. Jimenez and John Yang and Alexander Wettig and
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Shunyu Yao and Kexin Pei and Ofir Press and Karthik Narasimhan},
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title = {{SWE-bench: Can Language Models Resolve Real-World GitHub Issues?}},
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booktitle = {International Conference on Learning Representations (ICLR)},
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year = {2024}
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}
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@article{livecodebench,
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author = {Naman Jain and King Han and Alex Gu and Wen-Ding Li and
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Fanjia Yan and Tianjun Zhang and Sida Wang and Armando Solar-Lezama and
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Koushik Sen and Ion Stoica},
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title = {{LiveCodeBench: Holistic and Contamination Free Evaluation of
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Large Language Models for Code}},
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journal = {arXiv preprint arXiv:2403.07974},
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year = {2024}
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}
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@article{gpqa,
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author = {David Rein and Betty Li Hou and Asa Cooper Stickland and
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Jackson Petty and Richard Yuanzhe Pang and Julien Dirani and
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Julian Michael and Samuel R. Bowman},
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title = {{GPQA: A Graduate-Level Google-Proof Q\&A Benchmark}},
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journal = {arXiv preprint arXiv:2311.12022},
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year = {2023}
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}
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@article{hle,
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author = {Long Phan and others},
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title = {{Humanity's Last Exam}},
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journal = {arXiv preprint arXiv:2501.14249},
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year = {2025}
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}
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@article{charxiv,
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author = {Zirui Wang and Mengzhou Xia and Luxi He and Howard Chen and
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Yitao Liu and Richard Zhu and Kaiqu Liang and Xindi Wu and
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Haotian Liu and Sadhika Malladi and Alexis Chevalier and
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Sanjeev Arora and Danqi Chen},
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title = {{CharXiv: Charting Gaps in Realistic Chart Understanding in
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Multimodal LLMs}},
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journal = {arXiv preprint arXiv:2406.18521},
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year = {2024}
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}
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@misc{terminalbench,
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author = {{Terminal-Bench Team}},
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title = {{Terminal-Bench: A Benchmark for AI Agents in Terminal Environments}},
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howpublished = {\url{https://www.tbench.ai/}},
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year = {2025}
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}
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% ---- Discipline ----
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@misc{hickey_simple,
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author = {Rich Hickey},
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title = {{Simple Made Easy}},
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howpublished = {Strange Loop Conference},
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year = {2011},
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note = {\url{https://www.infoq.com/presentations/Simple-Made-Easy/}}
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}
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