Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:50:29.507664Z
Paper Citation Record · LEDGER
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
As of 17 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 10 inbound Pith citation observations for arXiv:2505.23387.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T19:27:35.889180Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
67 of 67 outbound references displayed
- verified exact0
- verified fuzzy20
- unresolved46
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
Observation 19bb2ec8-78db-4d56-8cfd-77d0d0bda6c0 · outbound
This paper cites GPT-4 Technical Report.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization GPT-4 Technical Report
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:23.483646Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 468da172-88cd-4971-b37d-8c5a53c6bfc9 · outbound
This paper cites SantaCoder: don't reach for the stars!.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization SantaCoder: don't reach for the stars!
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:23.535332Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f266989-003f-473f-bf97-4dbd7d2645d2 · outbound
This paper cites An orchestrated survey of methodologies for automated software test case generation.Journal of systems and software, 86(8):1978–2001, 2013.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization An orchestrated survey of methodologies for automated software test case generation.Journal of systems and software, 86(8):1978–2001, 2013
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:34.630886Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9eb01a86-3448-44a7-9bbb-77b90512f6c9 · outbound
This paper cites Introducing claude 3.5 sonnet, 6 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Introducing claude 3.5 sonnet, 6 2024
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:34.460316Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f4771a24-b08c-4463-a240-b05cf17fb19d · outbound
This paper cites Claude 3.7 sonnet and claude code, 2 2025.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Claude 3.7 sonnet and claude code, 2 2025
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:34.313485Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 03503e04-0ef7-4ff0-b052-418442383f6f · outbound
This paper cites Program Synthesis with Large Language Models.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Program Synthesis with Large Language Models
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:23.855659Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9fcb4b02-dc24-4bf0-a9d1-56a22cd1799d · outbound
This paper cites Code alpaca: An instruction-following llama model for code generation.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Code alpaca: An instruction-following llama model for code generation
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:24.037931Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 73ac9bfd-78db-4414-a0c4-8a553ef074e6 · outbound
This paper cites an unresolved cited work.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Unresolved cited work
Reference 8
- Resolution
- unresolved
- raw_fallback, observed 2026-08-07T12:50:34.158212Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 9c38a33c-8575-4f14-9e31-570569b308fc · outbound
This paper cites Evaluating Large Language Models Trained on Code.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Evaluating Large Language Models Trained on Code
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:24.180001Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ebecbb5f-4933-4c80-a794-f472fc657670 · outbound
This paper cites An introduction to algorithms and the big o notation.Introduction to Programming with Fortran: With Coverage of Fortran 90, 95, 2003, 2008 and 77, pages 359–364, 2015.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization An introduction to algorithms and the big o notation.Introduction to Programming with Fortran: With Coverage of Fortran 90, 95, 2003, 2008 and 77, pages 359–364, 2015
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:33.953988Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f0523b29-292a-4f91-9e29-160329a78769 · outbound
This paper cites Mhpp: Exploring the capabilities and limitations of language models beyond basic code generation, 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Mhpp: Exploring the capabilities and limitations of language models beyond basic code generation, 2024
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:33.772239Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b258fdba-ecdd-4cda-acbc-bd4bf3c12972 · outbound
This paper cites Docker.lınea].[Junio de 2017].
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Docker.lınea].[Junio de 2017]
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:33.580132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 457bd8db-44ed-4218-8753-a5053c9b1667 · outbound
This paper cites StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization StepCoder: Improve Code Generation with Reinforcement Learning from Compiler Feedback
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:24.562628Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ac43d93-2f3e-493a-a312-8bf844b68a09 · outbound
This paper cites Mercury: A code efficiency benchmark for code large language models.Advances in Neural Information Processing Systems, 37, 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Mercury: A code efficiency benchmark for code large language models.Advances in Neural Information Processing Systems, 37, 2024
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:33.390117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 45663742-0ae8-4af7-800d-af78d13af267 · outbound
This paper cites Chapman and Hall/CRC, 1994.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Chapman and Hall/CRC, 1994
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:24.724108Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5badb4da-5bed-4308-8c0b-fd622e9b4717 · outbound
This paper cites RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:24.815311Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 722ebdaf-510b-4de9-a384-35e57fd0cebb · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:24.899820Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f36078d5-eae7-49a9-b5e7-19be210922b6 · outbound
This paper cites Measuring coding challenge competence with apps.NeurIPS, 2021.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Measuring coding challenge competence with apps.NeurIPS, 2021
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:33.219909Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 08b14e2d-1020-4ba0-b9b3-75ecd3c05244 · outbound
This paper cites Codecot: Tackling code syntax errors in cot reasoning for code generation, 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Codecot: Tackling code syntax errors in cot reasoning for code generation, 2024
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:33.019551Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b478f50e-0d9c-4771-b248-cec0d4d2b89b · outbound
This paper cites Effilearner: Enhancing efficiency of generated code via self-optimization.Advances in Neural Information Processing Systems, 37:84482–84522, 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Effilearner: Enhancing efficiency of generated code via self-optimization.Advances in Neural Information Processing Systems, 37:84482–84522, 2024
Reference 20
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:32.790748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 446d9409-f8a4-4237-aab9-80fbe517bf5f · outbound
This paper cites Effibench: Benchmarking the efficiency of automatically generated code.Advances in Neural Information Processing Systems, 37:11506–11544, 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Effibench: Benchmarking the efficiency of automatically generated code.Advances in Neural Information Processing Systems, 37:11506–11544, 2024
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:32.549057Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 8d701659-174a-4c4d-afeb-08c29b63f765 · outbound
This paper cites EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization EffiCoder: Enhancing Code Generation in Large Language Models through Efficiency-Aware Fine-tuning
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:25.227030Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 92b7a3da-f89a-4ff5-aa5d-51097c8b5401 · outbound
This paper cites Bias testing and mitigation in llm-based code generation.ACM Transactions on Software Engineering and Methodology, 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Bias testing and mitigation in llm-based code generation.ACM Transactions on Software Engineering and Methodology, 2024
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:32.310975Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e47b6424-dece-40b9-be72-358d58537a21 · outbound
This paper cites Measuring the Influence of Incorrect Code on Test Generation.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Measuring the Influence of Incorrect Code on Test Generation
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:25.350738Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 28372f51-1e5a-44a1-a159-8e2af24c6d33 · outbound
This paper cites Zhang, Michael Luck, Qingwen Bu, Yuhao Qing, and Heming Cui.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Zhang, Michael Luck, Qingwen Bu, Yuhao Qing, and Heming Cui
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:25.414753Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e9830e7-59f7-4d76-b684-647962f480f7 · outbound
This paper cites OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:25.476308Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 85dcd90d-1106-43d6-be37-fce6f7f671e7 · outbound
This paper cites Qwen2.5-Coder Technical Report.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Qwen2.5-Coder Technical Report
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:25.619468Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 494b4c79-dec5-4857-a27c-146e6ac0731c · outbound
This paper cites Ashraful Islam, Mohammed Eunus Ali, and Md Rizwan Parvez.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Ashraful Islam, Mohammed Eunus Ali, and Md Rizwan Parvez
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:31.958871Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation bdd1d97f-5a85-4f00-bf56-e344fc4e7c4c · outbound
This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:25.816411Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a57ee1a0-903a-49fb-8d93-adc1c0903f55 · outbound
This paper cites A Survey on Large Language Models for Code Generation.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization A Survey on Large Language Models for Code Generation
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:25.949940Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5f6a845a-08fe-4409-936e-3cd8fcac0ce8 · outbound
This paper cites Gonzalez, Hao Zhang, and Ion Stoica.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Gonzalez, Hao Zhang, and Ion Stoica
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:26.056841Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1149084b-f88c-4659-ab68-623086d0a859 · outbound
This paper cites Coderl: Mastering code generation through pretrained models and deep reinforcement learning.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Coderl: Mastering code generation through pretrained models and deep reinforcement learning
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:31.646333Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d1335fe5-2825-46e4-9764-ee4e5a722cf1 · outbound
This paper cites Competition-level code generation with alphacode.Science, 378(6624):1092–1097, 2022.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Competition-level code generation with alphacode.Science, 378(6624):1092–1097, 2022
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:26.277047Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2fbd8b7c-5ee1-4003-a086-1a9d9256e68c · outbound
This paper cites DeepSeek-V3 Technical Report.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization DeepSeek-V3 Technical Report
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:26.377727Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1dcf8880-cb30-428f-a2c4-c71d6bf5fce9 · outbound
This paper cites Is your code generated by chatGPT really correct? rigorous evaluation of large language models for code generation.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Is your code generated by chatGPT really correct? rigorous evaluation of large language models for code generation
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:26.394353Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 901b1cf3-73e3-462e-8e60-18cfe99e9c15 · outbound
This paper cites Evaluating Language Models for Efficient Code Generation.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Evaluating Language Models for Efficient Code Generation
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:26.404596Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3d2f7533-58d2-4b83-b9c0-79448fbafd5d · outbound
This paper cites Refining chatgpt-generated code: Characterizing and mitigating code quality issues.ACM Transactions on Software Engineering and Methodology, 33(5):1–26, 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Refining chatgpt-generated code: Characterizing and mitigating code quality issues.ACM Transactions on Software Engineering and Methodology, 33(5):1–26, 2024
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:31.355615Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation b645b98e-207d-455b-a7fa-b67c1182f7a9 · outbound
This paper cites StarCoder 2 and The Stack v2: The Next Generation.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization StarCoder 2 and The Stack v2: The Next Generation
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:26.687342Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb8d02a6-cfb5-4e96-b0ad-45eb984f4414 · outbound
This paper cites WizardCoder: Empowering Code Large Language Models with Evol-Instruct.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:26.792726Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f35a0c77-24bc-44db-b4fa-10f686a0fd94 · outbound
This paper cites The llama 4 herd: The beginning of a new era of natively multimodal ai innovation.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization The llama 4 herd: The beginning of a new era of natively multimodal ai innovation
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:31.081251Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 93a71e4a-fe8b-4a52-82b8-9f69abb06b3c · outbound
This paper cites OctoPack: Instruction Tuning Code Large Language Models.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization OctoPack: Instruction Tuning Code Large Language Models
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.026954Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b028048c-f4f5-4732-91dd-22fbbe098333 · outbound
This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.094115Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 064be610-7300-4050-b626-fd9dd388fd70 · outbound
This paper cites Introducing openai o3 and o4-mini, 4 2025.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Introducing openai o3 and o4-mini, 4 2025
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:30.800178Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 45870295-1a6a-4563-b2c4-6584df34f3b8 · outbound
This paper cites Zhang, Heming Cui, Siu-Ming Yiu, Dong Huang, See-Kiong Ng, and Luu Anh Tuan.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Zhang, Heming Cui, Siu-Ming Yiu, Dong Huang, See-Kiong Ng, and Luu Anh Tuan
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:30.584280Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d768de9e-9a5d-4dd6-91bd-2962dc171164 · outbound
This paper cites How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization How Efficient is LLM-Generated Code? A Rigorous & High-Standard Benchmark
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.276056Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 43e114bd-4d8f-457f-9ca7-bfe336ed532c · outbound
This paper cites Direct preference optimization: Your language model is secretly a reward model.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Direct preference optimization: Your language model is secretly a reward model
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.345353Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 77eeb386-b4ad-4930-96a9-263eb0ef08b3 · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.475345Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1957a6dd-8bff-4a8e-809e-b216b82fbce4 · outbound
This paper cites HybridFlow: A Flexible and Efficient RLHF Framework.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization HybridFlow: A Flexible and Efficient RLHF Framework
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.598252Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 564cc66c-78cb-4f7c-9a6d-36d52c42892d · outbound
This paper cites Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Efficient and Green Large Language Models for Software Engineering: Literature Review, Vision, and the Road Ahead
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.702240Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae1fa2d6-8fdb-48d9-8e30-51fbb49bd72a · outbound
This paper cites Learning Performance-Improving Code Edits.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Learning Performance-Improving Code Edits
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.836357Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e1bb270e-7f0f-4abc-a70d-79a771fb7f03 · outbound
This paper cites CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.939356Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation acf1e616-757f-40d2-8eac-a58cebcbb587 · outbound
This paper cites LLaMA: Open and Efficient Foundation Language Models.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization LLaMA: Open and Efficient Foundation Language Models
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:27.997213Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c1ec2e52-8874-46a8-a3f7-314142942e33 · outbound
This paper cites ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization ECCO: Can We Improve Model-Generated Code Efficiency Without Sacrificing Functional Correctness?
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.085835Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11b8eb8f-4ef8-49a9-9824-7dd480fb5620 · outbound
This paper cites Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.141142Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad6dd3da-fa85-4285-8449-befd7caddbd3 · outbound
This paper cites Finetuned Language Models Are Zero-Shot Learners.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Finetuned Language Models Are Zero-Shot Learners
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.229504Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6158f97a-520d-47e9-a578-c453f4f2ba4d · outbound
This paper cites Magicoder: Empow- ering code generation with OSS-instruct.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Magicoder: Empow- ering code generation with OSS-instruct
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:30.396424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 2eb1c552-0b1d-46b8-8c6d-933607e2e3e2 · outbound
This paper cites Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.424341Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dba9e3d8-c622-4c48-900b-ffb25c58fa41 · outbound
This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization WizardLM: Empowering large pre-trained language models to follow complex instructions
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.568252Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ae38b73-4d33-4c53-aa58-bd40f5be8991 · outbound
This paper cites Qwen2.5 Technical Report.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Qwen2.5 Technical Report
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.668207Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b7813645-9f34-4a7b-b5ea-f2014113db0f · outbound
This paper cites LLM4EFFI: Leveraging Large Language Models to Enhance Code Efficiency and Correctness.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization LLM4EFFI: Leveraging Large Language Models to Enhance Code Efficiency and Correctness
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.777021Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1479b453-fd6a-4059-9697-2fae65a8813c · outbound
This paper cites Focused-dpo: Enhancing code generation through focused preference optimization on error-prone points.arXiv preprint arXiv:2502.11475, 2025.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Focused-dpo: Enhancing code generation through focused preference optimization on error-prone points.arXiv preprint arXiv:2502.11475, 2025
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.872627Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1a1d3a14-8e2a-4b1e-bc73-9b1a235d957f · outbound
This paper cites A systematic literature review on large language models for automated program repair.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization A systematic literature review on large language models for automated program repair
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:28.952622Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 53c2939c-7ca9-4d28-967d-42f849ce694c · outbound
This paper cites Codegeex: A pre-trained model for code generation with multilingual benchmarking on humaneval-x.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Codegeex: A pre-trained model for code generation with multilingual benchmarking on humaneval-x
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:29.052783Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e139f44-2a97-4edf-a4a0-a2c171e0a289 · outbound
This paper cites Llamafactory: Unified efficient fine-tuning of 100+ language models.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Llamafactory: Unified efficient fine-tuning of 100+ language models
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:29.173199Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6737dbb1-562f-43f3-b232-1010bf84302a · outbound
This paper cites Debug like a human: A large language model debugger via verifying runtime execution step-by-step, 2024.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization Debug like a human: A large language model debugger via verifying runtime execution step-by-step, 2024
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-07T12:50:30.261687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 53fa0cad-94a7-426b-8f78-94bf78001534 · outbound
This paper cites BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions
Reference 66
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:50:29.403751Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3d7a45dd-2500-4667-b35e-b9e700dca317 · outbound
This paper cites <thinking> thing_content </thinking> <solution> solution_content </solution>.
Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization <thinking> thing_content </thinking> <solution> solution_content </solution>
Reference 67
- Resolution
- malformed identifier
- raw_fallback, observed 2026-08-07T12:50:30.109450Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Pith citing papers
Observation d24ad08c-0077-4fc8-bcb5-6bd98235db2a · inbound
A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.
A Survey of Reinforcement Learning for Large Reasoning Models Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 119
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T00:02:25.299885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 63ce1b29-3b42-47d7-9ac3-da77138d62bc · inbound
ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution cites this paper.
ParEVO: Synthesizing Code for Irregular Data: High-Performance Parallelism through Agentic Evolution Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 2024
- Resolution
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8091cb00-e0a4-413e-8745-630dca012d56 · inbound
An Initial Exploration of Contrastive Prompt Tuning to Generate Energy-Efficient Code cites this paper.
An Initial Exploration of Contrastive Prompt Tuning to Generate Energy-Efficient Code Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T16:40:10.533028Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 0ab1904a-5441-4146-b456-9d111cebdfb7 · inbound
Paper Espresso: From Paper Overload to Research Insight cites this paper.
Paper Espresso: From Paper Overload to Research Insight Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T22:45:47.882211Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f1c30b62-e7be-45ca-865c-b5e7fc4d2ce5 · inbound
AutoVecCoder: Teaching LLMs to Generate Explicitly Vectorized Code cites this paper.
AutoVecCoder: Teaching LLMs to Generate Explicitly Vectorized Code Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T11:43:14.954223Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation cf593b53-fee9-4d4c-8b60-9aa8ef710dc3 · inbound
Extrapolative Weight Averaging Reveals Correctness-Efficiency Frontiers in Code RL cites this paper.
Extrapolative Weight Averaging Reveals Correctness-Efficiency Frontiers in Code RL Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T14:43:30.585461Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 929a6b79-6e5d-4392-9ea1-d87fc9f941b7 · inbound
Chiseling Out Efficiency: Structured Skeleton Supervision for Efficient Code Generation cites this paper.
Chiseling Out Efficiency: Structured Skeleton Supervision for Efficient Code Generation Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T18:57:17.261414Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 340d2a8d-ac0f-4077-82c6-24e66db3da73 · inbound
SkelDPO: A Skeleton-Guided Direct Preference Optimization Framework for Efficient Code Generation cites this paper.
SkelDPO: A Skeleton-Guided Direct Preference Optimization Framework for Efficient Code Generation Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T19:07:17.720297Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 4ab10d0a-cf07-46ae-bac0-8c78fb288242 · inbound
Attention Amnesia in Hybrid LLMs: When CoT Fine-Tuning Breaks Long-Range Recall, and How to Fix It cites this paper.
Attention Amnesia in Hybrid LLMs: When CoT Fine-Tuning Breaks Long-Range Recall, and How to Fix It Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T13:10:55.920584Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f75767b9-bece-4bef-92df-e6872303254f · inbound
From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning cites this paper.
From Trainee to Trainer: LLM-Designed Training Environment for RL with Multi-Agent Reasoning Afterburner: Reinforcement Learning Facilitates Self-Improving Code Efficiency Optimization
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-06-27T01:00:19.847467Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.