Paper Citation Record · LEDGER

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code

As of 9 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 1 inbound Pith citation observation for arXiv:2502.07046.

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

pith.paper-citation-record.v1
2502.07046 v2

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T14:01:12.457223Z

measured 49 of 49 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T10:50:14.360577Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

48 of 48 outbound references displayed

verified exact1
verified fuzzy31
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e549b6eb-122e-4bbe-8c47-980bb696e690 · outbound

This paper cites Program synthesis with large language models,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Program synthesis with large language models,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.855591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 627bea92-fe23-420e-8128-0a52f777cb2e · outbound

This paper cites Measuring Coding Challenge Competence With APPS.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Measuring Coding Challenge Competence With APPS

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.321790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fbb2e48f-1b78-4429-8aa2-6ff820d2cba6 · outbound

This paper cites Generation Probabilities are Not Enough: Improving Error Highlighting for AI Code Suggestions,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Generation Probabilities are Not Enough: Improving Error Highlighting for AI Code Suggestions,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.847526Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation ba42146a-0da8-4e85-af22-7ba81e7a3444 · outbound

This paper cites Toward deep learn- ing software repositories,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Toward deep learn- ing software repositories,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.839249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0c89a7f6-5214-434e-8665-4f5642d15c73 · outbound

This paper cites An empirical study on the usage of transformer models for code completion,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code An empirical study on the usage of transformer models for code completion,

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.831304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 52654754-43dc-4f5a-b60a-5d83d7546614 · outbound

This paper cites Ensemble Models for Neural Source Code Summarization of Subroutines.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Ensemble Models for Neural Source Code Summarization of Subroutines

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.335003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d2e308e-6efc-4304-9136-a9641a29ca55 · outbound

This paper cites An empirical investigation into the use of image captioning for automated software documentation,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code An empirical investigation into the use of image captioning for automated software documentation,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.823210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 12dc398b-42a0-4143-b978-68e46444eac7 · outbound

This paper cites Towards automating code review activities,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Towards automating code review activities,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.814741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8d721078-d1df-42cc-b401-bbb5cfab17b5 · outbound

This paper cites Using pre-trained models to boost code review automation,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Using pre-trained models to boost code review automation,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.806452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 648031ad-24a5-4bf4-a10a-1b7ef5f1f1fe · outbound

This paper cites Graph-based statistical language model for code,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Graph-based statistical language model for code,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.797909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1d188841-42e5-4dbe-87e8-6b686307aa49 · outbound

This paper cites Deep learning code frag- ments for code clone detection,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Deep learning code frag- ments for code clone detection,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.789337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation cac84f54-1073-4b10-bac2-d459e26cccc1 · outbound

This paper cites Deep learning similarities from different representations of source code,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Deep learning similarities from different representations of source code,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.780693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c958bb6b-00b9-438a-bc7e-b349b0e1d0ea · outbound

This paper cites Learning How to Mutate Source Code from Bug-Fixes,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Learning How to Mutate Source Code from Bug-Fixes,

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.772214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 743d9a33-e385-48e1-9269-4adc81c056c7 · outbound

This paper cites Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Devign: Effective Vulnerability Identification by Learning Comprehensive Program Semantics via Graph Neural Networks

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.764831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0a7dd488-7b95-4e0d-982a-dddbef8bbb5b · outbound

This paper cites Sorting and transforming program repair ingredients via deep learning code similarities,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Sorting and transforming program repair ingredients via deep learning code similarities,

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.757722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 62efcdd7-7bfe-4cb8-87a6-8c0c1589f4c1 · outbound

This paper cites On learning meaningful code changes via neural machine translation,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code On learning meaningful code changes via neural machine translation,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.750565Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation d5b5bc12-6269-4d07-8ee4-3a76101d7ecd · outbound

This paper cites An empirical investigation into learning bug-fixing patches in the wild via neural machine transla- tion,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code An empirical investigation into learning bug-fixing patches in the wild via neural machine transla- tion,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.743029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c22a15ef-5992-42a4-b924-986b094b1b45 · outbound

This paper cites Sequencer: Sequence-to- sequence learning for end-to-end program repair,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Sequencer: Sequence-to- sequence learning for end-to-end program repair,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.734900Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 43bf6bc3-fa57-42ce-905a-037364a08a95 · outbound

This paper cites Can we automatically fix bugs by learning edit operations?.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Can we automatically fix bugs by learning edit operations?

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.726932Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 232d3b32-1fd6-42e8-a811-a39ef26d941c · outbound

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

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.377875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85cfc176-7a88-417c-977d-174c50ca1519 · outbound

This paper cites Emergent Abilities of Large Language Models.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Emergent Abilities of Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.381200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fa58b265-1fcd-481d-81d5-e6219a1d7561 · outbound

This paper cites Large Language Models Are Human-Level Prompt Engineers.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Large Language Models Are Human-Level Prompt Engineers

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.384421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea4ce8c4-ef9a-4972-b61d-cf7ce44a1912 · outbound

This paper cites ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code ChatGPT Prompt Patterns for Improving Code Quality, Refactoring, Requirements Elicitation, and Software Design

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.387530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd2e0075-22fd-44bc-b65c-525916c9cb43 · outbound

This paper cites Prompting is pro- gramming: A query language for large language models,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Prompting is pro- gramming: A query language for large language models,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.718792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e6162be5-a1b5-46fa-a534-8623ffd99656 · outbound

This paper cites Chain-of-Thought Prompting Elicits Reasoning in Large Language Models.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Chain-of-Thought Prompting Elicits Reasoning in Large Language Models

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.392293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d749fdad-591b-4578-a88c-cca7b4163a69 · outbound

This paper cites Snipgen tesbed to evaluate llms for code,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Snipgen tesbed to evaluate llms for code,

Reference 26

Resolution: verified exact; doi, observed 2026-08-08T14:01:12.482855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation fcb16e30-ae86-4a1a-b59a-06772d4a1bab · outbound

This paper cites Snipgen: A code snippet generation tool,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Snipgen: A code snippet generation tool,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.710018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 56e3ee4d-43fd-4146-8f97-3fd0d14f1fa2 · outbound

This paper cites Pydriller documentation,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Pydriller documentation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.701059Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation a8369563-d86b-4acf-8882-448a41fbb003 · outbound

This paper cites Tree-sitter documentation,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Tree-sitter documentation,

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.692135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation bfebb0c8-4613-453c-bf97-79bb0d2ac785 · outbound

This paper cites About codeql,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code About codeql,

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.683199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 22134da6-9649-4776-8533-226a5a4b12ee · outbound

This paper cites Benchmarking Causal Study to Interpret Large Language Models for Source Code ,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Benchmarking Causal Study to Interpret Large Language Models for Source Code ,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.674137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c401808f-b9cf-480d-a32e-51f2c4517e13 · outbound

This paper cites Evaluating and Explaining Large Language Models for Code Using Syntactic Structures.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Evaluating and Explaining Large Language Models for Code Using Syntactic Structures

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.410126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0f8892f4-0837-450f-8868-1635f3f31192 · outbound

This paper cites Which syn- tactic capabilities are statistically learned by masked language models for code?.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Which syn- tactic capabilities are statistically learned by masked language models for code?

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.665595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c1efbb6c-cb1f-4514-96e8-86aa6f5b7732 · outbound

This paper cites Improving ChatGPT Prompt for Code Generation.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Improving ChatGPT Prompt for Code Generation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.416321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d749108e-69a4-4cd6-999d-8c47cd006c01 · outbound

This paper cites The adverse effects of code duplication in machine learning models of code,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code The adverse effects of code duplication in machine learning models of code,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.657461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation f2150d84-1ce6-4307-9ad2-ae70d62fcbfe · outbound

This paper cites Neural Machine Translation with Byte-Level Subwords.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Neural Machine Translation with Byte-Level Subwords

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.422294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 527efccc-b606-4180-a966-7477b8f46d41 · outbound

This paper cites DeepFix: Fixing Common C Lan- guage Errors by Deep Learning,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code DeepFix: Fixing Common C Lan- guage Errors by Deep Learning,

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.648167Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 0c2ced99-c23b-4716-b273-a0bae037ae2d · outbound

This paper cites Competition-Level Code Generation with AlphaCode.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Competition-Level Code Generation with AlphaCode

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.428212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8bcc5f02-d53e-4d94-8af1-9e0239b3333a · outbound

This paper cites Learning to mine aligned code and natural language pairs from stack overflow,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Learning to mine aligned code and natural language pairs from stack overflow,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.639073Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 7f3ce7ad-ddd1-4612-9437-6c045ac0699c · outbound

This paper cites CodeSearchNet Challenge: Evaluating the State of Semantic Code Search.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.434210Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91dd3960-5656-44f9-ba0c-15cc4f72dc68 · outbound

This paper cites CodeXGLUE: A machine learning benchmark dataset for code understanding and generation.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code CodeXGLUE: A machine learning benchmark dataset for code understanding and generation

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.630977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3654f6d7-f90c-466c-828f-abdafcf93f54 · outbound

This paper cites xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.439905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 399c53c3-44ed-4d6c-bb98-a91f43602669 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Evaluating Large Language Models Trained on Code

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.442830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation becc6964-922b-42e5-9238-f71e1422b69f · outbound

This paper cites Securityeval dataset: Mining vul- nerability examples to evaluate machine learning-based code generation techniques,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Securityeval dataset: Mining vul- nerability examples to evaluate machine learning-based code generation techniques,

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.623591Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 319c41b6-aa47-4630-a892-4b22e56dd700 · outbound

This paper cites PythonSaga: Redefining the Benchmark to Evaluate Code Generating LLMs,.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code PythonSaga: Redefining the Benchmark to Evaluate Code Generating LLMs,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.615855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 6e492ce9-3a89-4638-9537-b67e6e15c36e · outbound

This paper cites Are large language models memorizing bug benchmarks?.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code Are large language models memorizing bug benchmarks?

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-08T14:01:12.607310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1c8586e3-95ca-4bfe-a1f3-7e21932a8abc · outbound

This paper cites EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code EvoPrompt: Connecting LLMs with Evolutionary Algorithms Yields Powerful Prompt Optimizers

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.454141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 423530aa-55dd-4efb-94cf-49f57c412f30 · outbound

This paper cites WizardLM: Empowering large pre-trained language models to follow complex instructions.

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code WizardLM: Empowering large pre-trained language models to follow complex instructions

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-08T14:01:12.457223Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation c4ba8229-943c-4ad3-b94a-4a0c14c37024 · inbound

Rethinking Software Empirical Studies with Structural Causal Models cites this paper.

Rethinking Software Empirical Studies with Structural Causal Models SnipGen: A Mining Repository Framework for Evaluating LLMs for Code

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-06-29T10:53:18.894445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.