mlsanityData to 7 Oct 2026

Are Optimal Algorithms Still Optimal? Rethinking Sorting in LLM-Based Pairwise Ranking with Batching and Caching

arXiv 2505.24643 ↗First posted 30 May 2025cs.CLcited by 2

On the map: LLM reasoning → Knowledge- and tool-augmented reasoning

Abstract (arXiv)

We introduce a novel framework for analyzing sorting algorithms in pairwise ranking prompting (PRP), re-centering the cost model around LLM inferences rather than traditional pairwise comparisons. While classical metrics based on comparison counts have traditionally been used to gauge efficiency, our analysis reveals that expensive LLM inferences overturn these predictions; accordingly, our framework encourages strategies such as batching and caching to mitigate inference costs. We show that algorithms optimal in the classical setting can lose efficiency when LLM inferences dominate the cost under certain optimizations.

Key facts. Cited by 2 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 13 of its 23 references that are in the map. First posted on arXiv 30 May 2025.

Builds on

13 of 23 references.

References · 13

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2024The Llama 3 Herd of Modelscited by 14,192
  3. 2023Mistral 7Bcited by 3,065
  4. 2022Scaling Instruction-Finetuned Language Modelscited by 2,997
  5. 2019HuggingFace's Transformers: State-of-the-art Natural Language Processingcited by 2,201
  6. 2021BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Modelscited by 1,225
  7. 2020Document Ranking with a Pretrained Sequence-to-Sequence Modelcited by 373
  8. 2023Is ChatGPT Good at Search? Investigating Large Language Models as Re-Ranking Agentscited by 356
  9. 2020Overview of the TREC 2019 deep learning trackcited by 282
  10. 2021Overview of the TREC 2020 deep learning trackcited by 193
  11. 2023Zero-Shot Listwise Document Reranking with a Large Language Modelcited by 81
  12. 2020Active Sampling for Pairwise Comparisons via Approximate Message Passing and Information Gain Maximizationcited by 17
1 more
  1. 2023Sorting with Predictionscited by 14

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025GroupRank: A Groupwise Paradigm for Effective and Efficient Passage Reranking with LLMscited by 3
  2. 2026Active Learners as Efficient PRP Rerankerscited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025LLM Optimization Unlocks Real-Time Pairwise Reranking
  2. 2026Ranking Reasoning LLMs under Test-Time Scaling
  3. 2025SortBench: Benchmarking LLMs based on their ability to sort lists
  4. 2023Found in the Middle: Permutation Self-Consistency Improves Listwise Ranking in Large Language Models
  5. 2025Batched Self-Consistency Improves LLM Relevance Assessment and Ranking
  6. 2025R1-Ranker: Teaching LLM Rankers to Reason
  7. 2026Think When Needed: Model-Aware Reasoning Routing for LLM-based Ranking
  8. 2025Ranking Before Serving: Low-Latency LLM Serving via Pairwise Learning-to-Rank