Paper Citation Record · LEDGER

MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 37 inbound Pith citation observations for arXiv:2208.08227.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2208.08227 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 37 of 37 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T14:18:33.053114Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-02T22:17:25.584510Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 46277a58-65a3-4e94-8ce4-a6bd3367bbda · inbound

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code cites this paper.

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 247

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:34:42.875327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 1d62edd9-b64b-40c5-a008-bca400849495 · inbound

A Survey on Large Language Models for Code Generation cites this paper.

A Survey on Large Language Models for Code Generation MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:18:06.772744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation af0a18d4-c815-421d-8eb1-a7d96af12ea7 · inbound

Qwen2.5-Coder Technical Report cites this paper.

Qwen2.5-Coder Technical Report MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:33:38.933028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f254911f-c9bc-4589-b7c6-b262e42e460f · inbound

A Preliminary Study of Multilingual Code Language Models for Code Generation Task Using Translated Benchmarks cites this paper.

A Preliminary Study of Multilingual Code Language Models for Code Generation Task Using Translated Benchmarks MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T14:18:33.053114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ab0d37de-0ee3-4c0c-8500-07ad65129277 · inbound

FullStack Bench: Evaluating LLMs as Full Stack Coders cites this paper.

FullStack Bench: Evaluating LLMs as Full Stack Coders MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T05:20:05.316083Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3e9cd2b-d5c0-4f69-95ba-b880f9ae19bc · inbound

Unseen Horizons: Unveiling the Real Capability of LLM Code Generation Beyond the Familiar cites this paper.

Unseen Horizons: Unveiling the Real Capability of LLM Code Generation Beyond the Familiar MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T18:16:26.681696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63495120-6e32-4cfd-a125-a2cedc611067 · inbound

Code LLMs: A Taxonomy-based Survey cites this paper.

Code LLMs: A Taxonomy-based Survey MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T18:03:57.147196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation edf61a2f-d584-47d1-97c1-1a56428d139f · inbound

On the Limit of Language Models as Planning Formalizers cites this paper.

On the Limit of Language Models as Planning Formalizers MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T16:41:11.139620Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ba2c3add-a3ea-4529-8d8a-4ec616d75e43 · inbound

CodeV: Issue Resolving with Visual Data cites this paper.

CodeV: Issue Resolving with Visual Data MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T05:39:29.880683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eab8472a-0f9c-4082-a7f1-7396a547589d · inbound

Instruction-Following Pruning for Large Language Models cites this paper.

Instruction-Following Pruning for Large Language Models MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-10T22:19:29.075540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 89818690-6712-48b7-9bef-ea0c78aabcb7 · inbound

An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities cites this paper.

An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T15:43:03.027496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c862b68-9df5-48f0-8b77-1af04008f362 · inbound

SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model cites this paper.

SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 156

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:30:02.924503Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation c0093bee-6441-4fec-988d-22238b0e5997 · inbound

LessLeak-Bench: A First Investigation of Data Leakage in LLMs Across 83 Software Engineering Benchmarks cites this paper.

LessLeak-Bench: A First Investigation of Data Leakage in LLMs Across 83 Software Engineering Benchmarks MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-08T16:26:32.068824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b433847b-73ec-43e4-95e8-cdc00ff52f7f · inbound

Towards a Science of Causal Interpretability in Deep Learning for Software Engineering cites this paper.

Towards a Science of Causal Interpretability in Deep Learning for Software Engineering MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-07T15:29:49.670235Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87e2efdb-0046-440d-9965-ce658358a6ec · inbound

SwiftEval: Developing a Language-Specific Benchmark for LLM-generated Code Evaluation cites this paper.

SwiftEval: Developing a Language-Specific Benchmark for LLM-generated Code Evaluation MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-07T12:29:17.854881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7019c4b-ba3f-410e-a2fa-98961a55c0e3 · inbound

AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length cites this paper.

AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T04:30:43.590827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51b4cef8-aec5-4d8e-87ed-7da0de47cde5 · inbound

Context-Aware CodeLLM Eviction for AI-assisted Coding cites this paper.

Context-Aware CodeLLM Eviction for AI-assisted Coding MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:20.600047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d79c2e7d-0f16-4eb4-91ee-76665084bdc5 · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:23.679977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 39ed476d-e59e-4400-a5e9-5dad069ce0c9 · inbound

Coding Triangle: How Does Large Language Model Understand Code? cites this paper.

Coding Triangle: How Does Large Language Model Understand Code? MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T19:15:31.911884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97742432-eee2-45d9-8f71-b792fa671509 · inbound

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators cites this paper.

AutoCodeBench: Large Language Models are Automatic Code Benchmark Generators MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-05T21:18:26.294753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65c94b43-ce96-48f7-b8ca-36d854ada713 · inbound

MiMo-V2-Flash Technical Report cites this paper.

MiMo-V2-Flash Technical Report MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-12T11:33:32.647434Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 041508af-e0e6-4576-a07e-ce7a8f8fc705 · inbound

FLeX: Fourier-based Low-rank EXpansion for multilingual transfer cites this paper.

FLeX: Fourier-based Low-rank EXpansion for multilingual transfer MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T22:25:53.442333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 6a702406-1203-403c-a4d7-9d6a4e43e04d · inbound

Think Before You Code: Dual Reasoning for the NLSafety-Utility Trade-Off in LLM Code Generation cites this paper.

Think Before You Code: Dual Reasoning for the NLSafety-Utility Trade-Off in LLM Code Generation MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:56:03.145255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 8b0ef50f-c145-495c-b96d-e7d67baef4ea · inbound

Think Before You Code: Dual Reasoning for the NLSafety-Utility Trade-Off in LLM Code Generation cites this paper.

Think Before You Code: Dual Reasoning for the NLSafety-Utility Trade-Off in LLM Code Generation MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T00:19:56.108802Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aba0ec63-3d1c-4dea-ad31-da87e812dcf3 · inbound

LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review cites this paper.

LLM-Based Multi-Agent Systems for Code Generation: A Multi-Vocal Literature Review MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-15T19:56:33.750408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d0485bf0-4f79-4403-a644-59bb932e7edc · inbound

Improving LLM Code Reasoning via Semantic Equivalence Self-Play with Formal Verification cites this paper.

Improving LLM Code Reasoning via Semantic Equivalence Self-Play with Formal Verification MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T06:51:46.287422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 0fc96fdc-fdc0-4d49-9490-052b971d6830 · inbound

Co-Located Tests, Better AI Code: How Test Syntax Structure Affects Foundation Model Code Generation cites this paper.

Co-Located Tests, Better AI Code: How Test Syntax Structure Affects Foundation Model Code Generation MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T12:01:05.329045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d7527281-47b5-4fe4-8913-06b10116bfa6 · inbound

SWE Atlas: Benchmarking Coding Agents Beyond Issue Resolution cites this paper.

SWE Atlas: Benchmarking Coding Agents Beyond Issue Resolution MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:36:58.178943Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation f6d60447-ce09-4d77-ae35-042e591483f3 · inbound

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models cites this paper.

Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 35

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T05:42:21.082359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 5d1945f9-8e87-4334-8287-02cc960f9925 · inbound

Hydra: Efficient, Correct Code Generation via Checkpoint-and-Rollback Support cites this paper.

Hydra: Efficient, Correct Code Generation via Checkpoint-and-Rollback Support MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:37:40.176613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation ae278ee2-a9f4-4bf5-b879-bbf44793dc73 · inbound

BootstrapAgent: Distilling Repository Setup into Reusable Agent Knowledge cites this paper.

BootstrapAgent: Distilling Repository Setup into Reusable Agent Knowledge MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-20T17:08:41.969898Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 090c46dc-5e5f-4efd-bf25-0dc56501c3f1 · inbound

MONA: Muon Optimizer with Nesterov Acceleration for Scalable Language Model Training cites this paper.

MONA: Muon Optimizer with Nesterov Acceleration for Scalable Language Model Training MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-06-29T19:23:54.143475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation bf5c8108-ad02-446c-b7a3-d0b32069b8dc · inbound

Functional Entropy: Predicting Functional Correctness in LLM-Generated Code with Uncertainty Quantification cites this paper.

Functional Entropy: Predicting Functional Correctness in LLM-Generated Code with Uncertainty Quantification MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T13:23:27.742271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation 49a89c34-db48-4d51-8f34-c53829fca4bb · inbound

Porting Declarative UI to HarmonyOS: A Heuristic-guided LLM Approach cites this paper.

Porting Declarative UI to HarmonyOS: A Heuristic-guided LLM Approach MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-02T19:37:18.927927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation caf117cf-3aa1-4a29-abad-5d5dac84f78c · inbound

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale cites this paper.

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 183

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T22:17:25.586047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

Observation d612cc47-3909-41de-b7e0-6c70d99a0fa7 · inbound

FindStatBench: Evaluating Large Language Models on Combinatorial Code Synthesis cites this paper.

FindStatBench: Evaluating Large Language Models on Combinatorial Code Synthesis MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T13:53:03.342870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 199f1d7c-8401-4a15-88c9-ef66789762df · inbound

SCOPE: Synthetic Conditional Objectives for Policy Evolution in Black-Box Combinatorial Optimization cites this paper.

SCOPE: Synthetic Conditional Objectives for Policy Evolution in Black-Box Combinatorial Optimization MultiPL-E: A Scalable and Extensible Approach to Benchmarking Neural Code Generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-01T04:26:46.342292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.