% refs.bib -- ThakiCloud AI Research
% All arXiv entries verified against the arXiv API on 2026-09-23.
% Own-prior entries verified via the Hugging Face dataset API on 2026-09-23.
% BFCL web entry verified (HTTP 200) on 2026-09-23.

% ---------------- Own prior work (ThakiCloud) ----------------

@techreport{thaki2026ensamblerouter,
  title     = {Cross-Tier Model Ensemble Voting for Skill Routing: A Cost--Quality Study Beyond Single-Signal Retrieval Fusion},
  author    = {{ThakiCloud AI Research (Hyojung Han)}},
  year      = {2026},
  month     = aug,
  institution = {ThakiCloud},
  url       = {https://thakicloud.com/tech-blog/ko/research/ensemble-tier-voting-skill-router/},
  note      = {Dataset: \url{https://huggingface.co/datasets/thaki-AI/daily-paper-2026-08-06-ensemble-tier-voting-skill-router}}
}

@techreport{thaki2026toolcallcliff,
  title     = {The Tool-Call Cliff: Measuring the Accuracy Decay of Agentic Structured Output Under Low-Bit Quantization in Self-Hosted H200 Serving},
  author    = {{ThakiCloud AI Research (Hyojung Han)}},
  year      = {2026},
  month     = sep,
  institution = {ThakiCloud},
  url       = {https://thakicloud.com/tech-blog/ko/research/tool-call-quantization-cliff/},
  note      = {Dataset: \url{https://huggingface.co/datasets/thaki-AI/daily-paper-2026-09-17-tool-call-quantization-cliff}}
}

@techreport{thaki2026verbositytax,
  title     = {The Reasoning Verbosity Tax: Per-Turn Cost--Quality Frontiers of Explicit vs.\ Compact Chain-of-Thought in Self-Hosted Agentic LLMs on H200},
  author    = {{ThakiCloud AI Research (Hyojung Han)}},
  year      = {2026},
  month     = sep,
  institution = {ThakiCloud},
  url       = {https://thakicloud.com/tech-blog/ko/research/reasoning-verbosity-tax-agentic-cost/},
  note      = {Dataset: \url{https://huggingface.co/datasets/thaki-AI/daily-paper-2026-09-11-reasoning-verbosity-tax-agentic-cost}}
}

@techreport{thaki2026manifestorder,
  title     = {The Manifest Order: Measuring KV-Cache Prefix Reuse and Token Cost Savings from Skill-Manifest and Tool-Schema Ordering in Unattended Agentic Loops on H200},
  author    = {{ThakiCloud AI Research (Hyojung Han)}},
  year      = {2026},
  month     = sep,
  institution = {ThakiCloud},
  url       = {https://thakicloud.com/tech-blog/ko/research/agentic-prefix-reuse-manifest-ordering/},
  note      = {Dataset: \url{https://huggingface.co/datasets/thaki-AI/daily-paper-2026-09-20-agentic-prefix-reuse-manifest-ordering}}
}

% ---------------- External: post-2026-03 (verified 2026-09-23) ----------------

@misc{arxiv260528840,
  title   = {How Consistent Are {LLM} Agents? Measuring Behavioral Reproducibility in Multi-Step Tool-Calling Pipelines},
  author  = {Yagubyan, Abel},
  year    = {2026},
  month   = apr,
  eprint  = {2605.28840},
  url     = {https://arxiv.org/abs/2605.28840}
}

@misc{arxiv260508680,
  title   = {Semantic Voting: Execution-Grounded Consensus for {LLM} Code Generation},
  author  = {Jiang, Shan and Yi, Zijian and Zhu, Chenguang},
  year    = {2026},
  month   = may,
  eprint  = {2605.08680},
  url     = {https://arxiv.org/abs/2605.08680}
}

@misc{arxiv260805643,
  title   = {Refining Over Resampling: Test-Time Self-Correction for {LLM} Reasoning},
  author  = {Bilal, Ahsan and Mohsin, Muhammad Ahmed and Umer, Muhammad and Trigg, Lena},
  year    = {2026},
  month   = aug,
  eprint  = {2608.05643},
  url     = {https://arxiv.org/abs/2608.05643}
}

@misc{arxiv260806370,
  title   = {The Bitter Lesson of Tool Calling},
  author  = {Patel, Ishan and Sen, Sahil and Lumer, Elias and Subbiah, Vamse Kumar},
  year    = {2026},
  month   = aug,
  eprint  = {2608.06370},
  url     = {https://arxiv.org/abs/2608.06370}
}

@misc{arxiv260327905,
  title   = {ATLAS-RTC: Closing the Loop on {LLM} Agent Output with Token-Level Runtime Control},
  author  = {Cruz, Christopher},
  year    = {2026},
  month   = mar,
  eprint  = {2603.27905},
  url     = {https://arxiv.org/abs/2603.27905}
}





@misc{arxiv260423577,
  title   = {RouteNLP: Closed-Loop {LLM} Routing with Conformal Cascading and Distillation Co-Optimization},
  author  = {Guo, Dongxin and Wu, Jikun and Yiu, Siu Ming},
  year    = {2026},
  month   = apr,
  eprint  = {2604.23577},
  url     = {https://arxiv.org/abs/2604.23577}
}

@misc{arxiv260530898,
  title   = {UniScale: Adaptive Unified Inference Scaling via Online Joint Optimization of Model Routing and Test-Time Scaling},
  author  = {Huang, Kaiyu and Wang, Xingyu and Kong, Mingze and Shi, Zhubo},
  year    = {2026},
  month   = may,
  eprint  = {2605.30898},
  url     = {https://arxiv.org/abs/2605.30898}
}


@misc{arxiv260312520,
  title   = {When {LLM} Judge Scores Look Good but Best-of-{N} Decisions Fail},
  author  = {Landesberg, Eddie},
  year    = {2026},
  month   = mar,
  eprint  = {2603.12520},
  url     = {https://arxiv.org/abs/2603.12520}
}

@misc{arxiv260417433,
  title   = {Self-Consistency from Only Two Samples: CoT-PoT Ensembling for Efficient {LLM} Reasoning},
  author  = {Saparkhan, Raman and Hawasly, Majd and Parvez, Md Rizwan and Raza, Mohammad},
  year    = {2026},
  month   = apr,
  eprint  = {2604.17433},
  url     = {https://arxiv.org/abs/2604.17433}
}



@misc{arxiv260913559,
  title   = {Carbon-Aware Routing for Function Calling in Edge-Cloud {LLM} Systems},
  author  = {Panteleaki, Aikaterini Maria and Paramanayakam, Varatheepan and Tragoudas, Spyros and Anagnostopoulos, Iraklis},
  year    = {2026},
  month   = sep,
  eprint  = {2609.13559},
  url     = {https://arxiv.org/abs/2609.13559}
}

@misc{arxiv260713347,
  title   = {LLM-as-a-Judge Scores Are Unreliable Optimization Signals in Closed-Loop Table Recognition},
  author  = {Kim, Donghwan},
  year    = {2026},
  month   = jul,
  eprint  = {2607.13347},
  url     = {https://arxiv.org/abs/2607.13347}
}

@misc{arxiv260600135,
  title   = {On Effectiveness and Efficiency of Agentic Tool-calling and RL Training},
  author  = {Liu, Tong and Qian, Cheng and Cief, Matej and He, Yuan and Dan, Daniele},
  year    = {2026},
  month   = may,
  eprint  = {2606.00135},
  url     = {https://arxiv.org/abs/2606.00135}
}

% ---------------- External: pre-2026-03 classics (verified 2026-09-23) ----------------

@misc{arxiv220311171,
  title   = {Self-Consistency Improves Chain of Thought Reasoning in Language Models},
  author  = {Wang, Xuezhi and Wei, Jason and Schuurmans, Dale and Le, Quoc and Chi, Ed and Narang, Sharanya and Chowdhery, Aakanksha and Zhou, Denny},
  year    = {2022},
  eprint  = {2203.11171},
  url     = {https://arxiv.org/abs/2203.11171}
}







% ---------------- Benchmark (verified 2026-09-23) ----------------

@misc{bfcl2024leaderboard,
  title  = {Berkeley Function Calling Leaderboard (BFCL)},
  author = {{UC Berkeley (Gorilla project)}},
  year   = {2024},
  url    = {https://gorilla.cs.berkeley.edu/leaderboard.html},
  note   = {Dataset: \url{https://huggingface.co/datasets/gorilla-llm/Berkeley-Function-Calling-Leaderboard}}
}



@misc{arxiv240417140,
  title   = {Small Language Models Need Strong Verifiers to Self-Correct Reasoning},
  author  = {Zhang, Yunxiang and Khalifa, Muhammad and Logeswaran, Lajanugen and Kim, Jaekyeom and Bhatt, Gaurav and Zettable, Yulia and Faruqui, Manaal},
  year    = {2024},
  eprint  = {2404.17140},
  url     = {https://arxiv.org/abs/2404.17140}
}

@misc{arxiv250618781,
  title   = {Existing {LLMs} Are Not Self-Consistent For Simple Tasks},
  author  = {Lin, Zhenru and Tao, Jiawen and Yuan, Yang and Yao, Andrew Chi-Chih},
  year    = {2025},
  month   = jun,
  eprint  = {2506.18781},
  url     = {https://arxiv.org/abs/2506.18781}
}