---
title: "Who cites Peter D. Bailis — 277 papers of our library"
description: "277 papers of the Elamur Research library cite the works of Peter D. Bailis, found in their bibliographies; the most cited first."
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---
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# Who cites Peter D. Bailis

310 citations of their works from 277 papers of our library (of the 149,439 whose bibliographies we read) · 58 with a page here, the most cited first · [← Peter D. Bailis](https://md.research.elamur.ai/free/en/authors/peter-d-bailis/)

1. [**On-Policy Distillation of Language Models: Learning from Self-Generated Mistakes arXiv:2306.13649**Rishabh Agarwal, Nino Vieillard, Yongchao Zhou, et al.*2023 · 299 citations*](https://md.research.elamur.ai/free/en/papers/agarwal-2023-policy-distillation-language-models-learning/)
2. [**Large Language Monkeys: Scaling Inference Compute with Repeated Sampling arXiv:2407.21787**Bradley Brown, Jordan Juravsky, Ryan Ehrlich, et al.*2024 · 270 citations*](https://md.research.elamur.ai/free/en/papers/brown-2024-large-language-monkeys-scaling-inference/)
3. **[DataComp: In search of the next generation of multimodal datasets](https://md.research.elamur.ai/free/en/papers/gadre-2023-datacomp-search-next-generation-multimodal/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, et al.*2023 · 224 citations*
4. [**EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty arXiv:2401.15077**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 208 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-speculative-sampling-requires-rethinking/)
5. [**LESS: Selecting Influential Data for Targeted Instruction Tuning arXiv:2402.04333**Mengzhou Xia, Sadhika Malladi, Suchin Gururangan, et al.*2024 · 178 citations*](https://md.research.elamur.ai/free/en/papers/xia-2024-less-selecting-influential-data-targeted/)
6. **[Unlocking Efficiency in Large Language Model Inference: A Comprehensive Survey of Speculative Decoding](https://md.research.elamur.ai/free/en/papers/xia-2024-unlocking-efficiency-large-language-model/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Heming Xia, Zhe Yang, Qingxiu Dong, et al.*2024 · 146 citations*
7. **[EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees](https://md.research.elamur.ai/free/en/papers/li-2024-eagle-2-faster-inference-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yuhui Li, Fangyun Wei, Chao Zhang, et al.*2024 · 133 citations*
8. [**A Survey on Efficient Inference for Large Language Models arXiv:2404.14294**Zixuan Zhou, Xuefei Ning, Ke Hong, et al.*2024 · 113 citations*](https://md.research.elamur.ai/free/en/papers/zhou-2024-survey-efficient-inference-large-language/)
9. **[Towards Efficient Generative Large Language Model Serving: A Survey from Algorithms to Systems](https://md.research.elamur.ai/free/en/papers/miao-2023-towards-efficient-generative-large-language/) [ACM Computing Surveys](https://md.research.elamur.ai/free/en/venues/acm-computing-surveys/)**Xupeng Miao, Gabriele Oliaro, Zhihao Zhang, et al.*2023 · 110 citations*
10. [**A Survey on Data Selection for Language Models arXiv:2402.16827**Alon Albalak, Yanai Elazar, Sang Michael Xie, et al.*2024 · 95 citations*](https://md.research.elamur.ai/free/en/papers/albalak-2024-survey-data-selection-language-models/)
11. [**LLM Inference Unveiled: Survey and Roofline Model Insights arXiv 2024**Zhihang Yuan, Yuzhang Shang, Yang Zhou, et al.*2024 · 91 citations*](https://md.research.elamur.ai/free/en/papers/yuan-2024-llm-inference-unveiled-survey-roofline/)
12. **[Rephrasing the Web: A Recipe for Compute and Data-Efficient Language Modeling](https://md.research.elamur.ai/free/en/papers/maini-2024-rephrasing-web-recipe-compute-data/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pratyush Maini, Skyler Seto, Richard Bai, et al.*2024 · 90 citations*
13. [**Why Do Multi-Agent LLM Systems Fail? arXiv:2503.13657**Mert Cemri, Melissa Z. Pan, Shuyi Yang, et al.*2025 · 89 citations*](https://md.research.elamur.ai/free/en/papers/cemri-2025-why-multi-agent-llm/)
14. [**A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well? arXiv:2503.24235**Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, et al.*2025 · 79 citations*](https://md.research.elamur.ai/free/en/papers/zhang-2025-survey-test-time-scaling-large/)
15. **[Finding Support Examples for In-Context Learning](https://md.research.elamur.ai/free/en/papers/li-2023-finding-support-examples-context-learning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xiaonan Li, Xipeng Qiu*2023 · 78 citations*
16. [**Scaling Large Language Model-based Multi-Agent Collaboration arXiv:2406.07155**Chen Qian, Zihao Xie, YiFei Wang, et al.*2024 · 70 citations*](https://md.research.elamur.ai/free/en/papers/qian-2024-scaling-large-language-model/)
17. **[What Did I Do Wrong? Quantifying LLMs' Sensitivity and Consistency to Prompt Engineering](https://md.research.elamur.ai/free/en/papers/errica-2025-what-did-i-do-wrong/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Federico Errica, Davide Sanvito, Giuseppe Siracusano, et al.*2025 · 63 citations*
18. [**Deep Think with Confidence arXiv:2508.15260**Yichao Fu, Xuewei Wang, Yuandong Tian, et al.*2025 · 61 citations*](https://md.research.elamur.ai/free/en/papers/fu-2025-deep-think-confidence/)
19. [**Superfiltering: Weak-to-Strong Data Filtering for Fast Instruction-Tuning arXiv:2402.00530**Ming Li, Yong Zhang, Shwai He, et al.*2024 · 60 citations*](https://md.research.elamur.ai/free/en/papers/li-2024-superfiltering-weak-strong-data-filtering/)
20. [**Rho-1: Not All Tokens Are What You Need arXiv:2404.07965**Zhenghao Lin, Zhibin Gou, Yeyun Gong, et al.*2024 · 59 citations*](https://md.research.elamur.ai/free/en/papers/lin-2024-rho-1-all-tokens-need/)
21. [**AI Agents That Matter arXiv:2407.01502**Sayash Kapoor, Benedikt Stroebl, Zachary S. Siegel, et al.*2024 · 55 citations*](https://md.research.elamur.ai/free/en/papers/kapoor-2024-ai-agents-that-matter/)
22. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)
23. **[Towards Thinking-Optimal Scaling of Test-Time Compute for LLM Reasoning](https://md.research.elamur.ai/free/en/papers/yang-2025-towards-thinking-optimal-scaling-test/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Wenkai Yang, Shuming Ma, Yankai Lin, et al.*2025 · 43 citations*
24. [**Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling arXiv:2410.11325**Wenda Xu, Rujun Han, Zifeng Wang, et al.*2024 · 41 citations*](https://md.research.elamur.ai/free/en/papers/xu-2024-speculative-knowledge-distillation-bridging-teacher/)
25. [**MambaByte: Token-free Selective State Space Model arXiv:2401.13660**Junxiong Wang, Tushaar Gangavarapu, Jing Nathan Yan, et al.*2024 · 35 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-mambabyte-token-free-selective-state/)
26. **[Turning Trash into Treasure: Accelerating Inference of Large Language Models with Token Recycling](https://md.research.elamur.ai/free/en/papers/luo-2025-turning-trash-into-treasure-accelerating/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xianzhen Luo, Yixuan Wang, Qingfu Zhu, et al.*2025 · 22 citations*
27. **[MAgICoRe: Multi-Agent, Iterative, Coarse-to-Fine Refinement for Reasoning](https://md.research.elamur.ai/free/en/papers/chen-2025-magicore-multi-agent-iterative-coarse/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Justin Chen, Archiki Prasad, Swarnadeep Saha, et al.*2025 · 20 citations*
28. **[Diversity-oriented Data Augmentation with Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2025-diversity-oriented-data-augmentation-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zaitian Wang, Jinghan Zhang, Xinhao Zhang, et al.*2025 · 17 citations*
29. [**Harnessing the Reasoning Economy: A Survey of Efficient Reasoning for Large Language Models arXiv:2503.24377**Rui Wang, Hongru Wang, Boyang Xue, et al.*2025 · 16 citations*](https://md.research.elamur.ai/free/en/papers/wang-2025-harnessing-reasoning-economy-survey-efficient/)
30. **[Automatic Combination of Sample Selection Strategies for Few-Shot Learning](https://md.research.elamur.ai/free/en/papers/pecher-2026-automatic-combination-sample-selection-strategies/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Branislav Pecher, Ivan Srba, Maria Bielikova, et al.*2026 · 15 citations*
31. **[FR-Spec: Accelerating Large-Vocabulary Language Models via Frequency-Ranked Speculative Sampling](https://md.research.elamur.ai/free/en/papers/zhao-2025-fr-spec-accelerating-large-vocabulary/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Weilin Zhao, Tengyu Pan, Xu Han, et al.*2025 · 15 citations*
32. **[Dynamic Parallel Tree Search for Efficient LLM Reasoning](https://md.research.elamur.ai/free/en/papers/ding-2025-dynamic-parallel-tree-search-efficient/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yifu Ding, Wentao Jiang, Shunyu Liu, et al.*2025 · 13 citations*
33. **[SEED: Accelerating Reasoning Tree Construction via Scheduled Speculative Decoding](https://md.research.elamur.ai/free/en/papers/wang-2025-seed-accelerating-reasoning-tree-construction/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zhenglin Wang, Jialong Wu, Yilong Lai, et al.*2025 · 8 citations*
34. **[LogitSpec: Accelerating Retrieval-based Speculative Decoding via Next Next Token Speculation](https://md.research.elamur.ai/free/en/papers/liu-2026-logitspec-accelerating-retrieval-based-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Tianyu Liu, Qitan Lv, Hao Li, et al.*2026 · 6 citations*
35. **[KNN-SSD: Enabling Dynamic Self-Speculative Decoding via Nearest Neighbor Layer Set Optimization](https://md.research.elamur.ai/free/en/papers/song-2026-knn-ssd-enabling-dynamic-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mingbo Song, Heming Xia, Jun Zhang, et al.*2026 · 5 citations*
36. **[LongSpec: Long-Context Lossless Speculative Decoding with Efficient Drafting and Verification](https://md.research.elamur.ai/free/en/papers/yang-2026-longspec-long-context-lossless-speculative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Penghui Yang, Cunxiao Du, Fengzhuo Zhang, et al.*2026 · 5 citations*
37. **[DeepPrune: Parallel Scaling without Inter-trace Redundancy](https://md.research.elamur.ai/free/en/papers/tu-2026-deepprune-parallel-scaling-without-inter/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shangqing Tu, Yaxuan Li, Yushi Bai, et al.*2026 · 3 citations*
38. **[Metacognitive Self-Correction for Multi-Agent System via Prototype-Guided Next-Execution Reconstruction](https://md.research.elamur.ai/free/en/papers/shen-2026-metacognitive-self-correction-multi-agent/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Shen, Qi Zhang, Song Wang, et al.*2026 · 3 citations*
39. **[SSSD: Simply-Scalable Speculative Decoding](https://md.research.elamur.ai/free/en/papers/marzollo-2026-sssd-simply-scalable-speculative-decoding/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michele Marzollo, Jiawei Zhuang, Niklas Roemer, et al.*2026 · 3 citations*
40. **[EvoRoute: Experience-Driven Self-Routing LLM Agent Systems](https://md.research.elamur.ai/free/en/papers/zhang-2026-evoroute-experience-driven-self-routing/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Guibin Zhang, Haiyang Yu, Kaiming Yang, et al.*2026 · 2 citations*
41. **[Sparrow: Text-Anchored Window Attention with Visual-Semantic Glimpsing for Speculative Decoding in Video LLMs](https://md.research.elamur.ai/free/en/papers/zhang-2026-sparrow-text-anchored-window-attention/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Libo Zhang, Zhaoning Zhang, Hongwanyang, et al.*2026 · 2 citations*
42. **[Speculative Decoding Speed-of-Light: Optimal Lower Bounds via Branching Random Walks](https://md.research.elamur.ai/free/en/papers/pankratov-2026-speculative-decoding-speed-light-optimal/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Sergey Pankratov, Dan Alistarh*2026 · 1 citation*
43. **[VecCISC: Improving Confidence-Informed Self-Consistency with Reasoning Trace Clustering and Candidate Answer Selection](https://md.research.elamur.ai/free/en/papers/petullo-2026-veccisc-improving-confidence-informed-self/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**James Petullo, Sonny George, Dylan Cashman, et al.*2026 · 1 citation*
44. **[A Scalable Multi-LLM Collaboration System with Retrieval-based Selection and Exploration-Exploitation-Driven Enhancement](https://md.research.elamur.ai/free/en/papers/tang-2026-scalable-multi-llm-collaboration-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shengji Tang, Jianjian Cao, Weihao Lin, et al.*2026*
45. **[An Empirical Study of Speculative Decoding for Small Language Models](https://md.research.elamur.ai/free/en/papers/mainardi-2026-empirical-study-speculative-decoding-small/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Luca Mainardi, Selcuk Sandikci, Joaquin Vanschoren*2026*
46. **[Calibrated Speculative Decoding: Frequency-Guided Candidate Selection for Efficient Inference](https://md.research.elamur.ai/free/en/papers/zhouxuwen-2026-calibrated-speculative-decoding-frequency-guided/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhouxuwen, Fangxin Liu, Chao Wang, et al.*2026*
47. **[Chronos: Learning Temporal Dynamics of Reasoning Chains for Test-Time Scaling](https://md.research.elamur.ai/free/en/papers/zhang-2026-chronos-learning-temporal-dynamics-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kai Zhang, Jiayi Liao, Chengpeng Li, et al.*2026*
48. **[From Tokens to Steps: Verification-Aware Speculative Decoding for Efficient Multi-Step Reasoning](https://md.research.elamur.ai/free/en/papers/purohit-2026-tokens-steps-verification-aware-speculative/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kiran Purohit, Ramasuri Narayanam, Soumyabrata Pal*2026*
49. **[HCSpec: Two-Tier Horizontal Cascade Speculative Decoding for High-Efficiency Large Language Model Inference](https://md.research.elamur.ai/free/en/papers/zhang-2026-hcspec-two-tier-horizontal-cascade/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yizhou Zhang, Siming Chen, Hao Ye, et al.*2026*
50. **[Let Retrievers Think Before Action: Thought-Augmented Embedding for Dense Retrieval](https://md.research.elamur.ai/free/en/papers/yan-2026-let-retrievers-think-before-action/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ruiran Yan, Wen Xiong, Ze Liu, et al.*2026*
51. **[MARS: Unleashing the Power of Speculative Decoding via Margin-Aware Verification](https://md.research.elamur.ai/free/en/papers/song-2026-mars-unleashing-power-speculative-decoding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingwei Song, Xinyu Wang, Hanbin Wang, et al.*2026*
52. **[Measuring Distribution Shift in User Prompts and Its Effects on LLM Performance](https://md.research.elamur.ai/free/en/papers/seegmiller-2026-measuring-distribution-shift-user-prompts/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parker Seegmiller, Sarah Masud Preum*2026*
53. **[MelTrim: Coarse-to-Fine Data Pruning for Speech Classification](https://md.research.elamur.ai/free/en/papers/wang-2026-meltrim-coarse-fine-data-pruning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shaobo Wang, Tianle Niu, Xuan Ouyang, et al.*2026*
54. **[RouteMoA: Dynamic Routing without Pre-Inference Boosts Efficient Mixture-of-Agents](https://md.research.elamur.ai/free/en/papers/wang-2026-routemoa-dynamic-routing-without-pre/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jize Wang, Han Wu, Zhiyuan You, et al.*2026*
55. **[SpecBound: Adaptive Bounded Self-Speculation with Layer-wise Confidence Calibration](https://md.research.elamur.ai/free/en/papers/wen-2026-specbound-adaptive-bounded-self-speculation/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhuofan Wen, Yang Feng*2026*
56. **[Taming “Zombie” Agents: A Markov State-Aware Framework for Resilient Multi-Agent Evolution](https://md.research.elamur.ai/free/en/papers/zhang-2026-taming-zombie-agents-markov-state/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Taolin Zhang, Pukun Zhao, Qizhou Chen, et al.*2026*
57. **[TokenTiming: A Dynamic Alignment Method for Universal Speculative Decoding Model Pairs](https://md.research.elamur.ai/free/en/papers/xiao-2026-tokentiming-dynamic-alignment-method-universal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sibo Xiao, Fu Jinyuan, Zhongle Xie, et al.*2026*
58. **[Training-Free Adaptive Speculative Decoding via Linguistic Priors](https://md.research.elamur.ai/free/en/papers/wang-2026-training-free-adaptive-speculative-decoding/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jingyi Wang, Jiaqi Huang, Zunnan Xu, et al.*2026*

219 more citing papers of our library have no page here yet.

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