How to Select Pre-Trained Code Models for Reuse? A Learning Perspective | Paper Citation Record

Observation 10f57e13-c6d8-4c01-b4a5-17c4c94d0f64 · outbound

This paper cites Codebert: A pre-trained model for programming and natural languages,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Codebert: A pre-trained model for programming and natural languages,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:52.927085Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dea20c0b-cdb8-4024-a7d8-7330b83f5f82 · outbound

This paper cites Unified pre- training for program understanding and generation,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Unified pre- training for program understanding and generation,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:52.898033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 11c2b31a-5b0f-436c-a100-aae2734c2b4b · outbound

This paper cites Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Codet5: Identifier-aware unified pre-trained encoder-decoder models for code understanding and generation,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.317922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eea9f476-f10d-4551-ba20-cd678037cd2e · outbound

This paper cites Codegen: An open large language model for code with multi-turn program synthesis,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Codegen: An open large language model for code with multi-turn program synthesis,

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:52.712320Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e5ee5b39-f557-44e9-a6f6-bd17dd8c190f · outbound

This paper cites StarCoder: may the source be with you!.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective StarCoder: may the source be with you!

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.333707Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5b77cdf-4bf8-4269-a88e-d94092e91c9f · outbound

This paper cites Code Llama: Open Foundation Models for Code.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Code Llama: Open Foundation Models for Code

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.347378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d5c1b91-1fc4-41cb-9871-0c733d728380 · outbound

This paper cites BERT: pre-training of deep bidirectional transformers for language understanding,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective BERT: pre-training of deep bidirectional transformers for language understanding,

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:52.594772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d4e309a1-c3af-4b24-af5c-d73ed12335b2 · outbound

This paper cites Demystifying gpt-3 language model: A technical overview,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Demystifying gpt-3 language model: A technical overview,

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:52.418247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a44c04bb-3546-42bc-b179-6b8b217da047 · outbound

This paper cites Hugging Face,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Hugging Face,

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:52.318509Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1c1daacb-f580-4141-936a-ffa6afe08ce8 · outbound

This paper cites Tensorflow Hub,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Tensorflow Hub,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:52.210494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 55f98951-392d-492b-ae94-3a96c804093e · outbound

This paper cites Onnx model zoo,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Onnx model zoo,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:52.104768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation be99cbc8-3860-4624-853b-16979acf9f3d · outbound

This paper cites Pytorch hub,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Pytorch hub,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.995388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 636a2a13-3023-491e-a191-62035f1dcf7c · outbound

This paper cites What is the intended usage context of this model? an exploratory study of pre-trained models on various model repositories,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective What is the intended usage context of this model? an exploratory study of pre-trained models on various model repositories,

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.508962Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d0a50e7-dd15-41e2-abe8-2c19102804ff · outbound

This paper cites A survey on neural network interpretability,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective A survey on neural network interpretability,

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.534827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88428c75-33fa-4757-b450-8115756c8aaf · outbound

This paper cites Scaling Laws for Neural Language Models.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Scaling Laws for Neural Language Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.566746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b915205-336f-4dbb-8f73-0437e59a7f30 · outbound

This paper cites Which model to transfer? finding the needle in the growing haystack,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Which model to transfer? finding the needle in the growing haystack,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.764844Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f916bf9d-db15-4b6b-8171-82d272cc6d04 · outbound

This paper cites Neural data server: A large- scale search engine for transfer learning data,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Neural data server: A large- scale search engine for transfer learning data,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.692743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 296370dc-92a0-4261-83fb-b2af2c7e5155 · outbound

This paper cites Scalable transfer learning with expert models,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Scalable transfer learning with expert models,

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.613555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6cba1538-4d97-4356-88a9-fca691c23492 · outbound

This paper cites Scalable diverse model selec- tion for accessible transfer learning,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Scalable diverse model selec- tion for accessible transfer learning,

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.570620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 50046bb6-d19b-426b-876b-5c96fe8f3844 · outbound

This paper cites An information-theoretic approach to transferability in task transfer learning,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective An information-theoretic approach to transferability in task transfer learning,

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.498143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2f18d5d4-5731-4e05-a6d4-c1281e36aae4 · outbound

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

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.694835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 674340e1-2e46-4443-9279-9f753ee22a0e · outbound

This paper cites The Stack: 3 TB of permissively licensed source code.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective The Stack: 3 TB of permissively licensed source code

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.717123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8430b323-93bf-427b-a6fa-814339c4e636 · outbound

This paper cites An extensive study on pre-trained models for program understanding and generation,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective An extensive study on pre-trained models for program understanding and generation,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.466513Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c761503d-e47e-4b07-8e04-d9f7a69e6a58 · outbound

This paper cites Graphcodebert: Pre- training code representations with data flow,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Graphcodebert: Pre- training code representations with data flow,

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.425541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bc18bae5-abbd-4891-9d04-9f86a6a7394f · outbound

This paper cites CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.782722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d10d4d32-d6d6-418e-9a1f-db7de33b5f15 · outbound

This paper cites Codegeex: A pre- trained model for code generation with multilingual benchmarking on humaneval-x,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Codegeex: A pre- trained model for code generation with multilingual benchmarking on humaneval-x,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.359882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 48a63c44-b022-466e-8fa5-b4ac2ede48cf · outbound

This paper cites Competition- level code generation with alphacode,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Competition- level code generation with alphacode,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.292865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0d825199-f3b6-46ad-a774-1c148eb9dbab · outbound

This paper cites Electra: Pre- training text encoders as discriminators rather than generators,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Electra: Pre- training text encoders as discriminators rather than generators,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:51.212766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e3207d25-6475-416e-832f-ef5c3cc50e26 · outbound

This paper cites BART: Denoising sequence-to- sequence pre-training for natural language generation, translation, and comprehension,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective BART: Denoising sequence-to- sequence pre-training for natural language generation, translation, and comprehension,

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.875258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4bb3456-804e-4b13-bdbf-8a55b923abb9 · outbound

This paper cites Exploring the limits of transfer learning with a unified text-to-text transformer,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Exploring the limits of transfer learning with a unified text-to-text transformer,

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:45.899050Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0ed73d4-7590-4aae-a8b5-54ee800538b4 · outbound

This paper cites Devign: Effective vulner- ability identification by learning comprehensive program semantics via graph neural networks,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Devign: Effective vulner- ability identification by learning comprehensive program semantics via graph neural networks,

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.961052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation e88e4e12-6797-481a-8eec-d6208572869c · outbound

This paper cites Convolutional neural networks over tree structures for programming language processing,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Convolutional neural networks over tree structures for programming language processing,

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.814748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0a87d1cf-82cb-40f4-bd1b-c90786631a65 · outbound

This paper cites Scc: Automatic classification of code snippets,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Scc: Automatic classification of code snippets,

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.758570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 04e0f955-5593-426e-8e55-a6c7edb48686 · outbound

This paper cites CodeBERTScore: Eval- uating code generation with pretrained models of code,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective CodeBERTScore: Eval- uating code generation with pretrained models of code,

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.662166Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 67437e4e-de20-4de5-84f4-ab16a8773fd4 · outbound

This paper cites Code Parrot,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Code Parrot,

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.574759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0c0c29ff-e371-4b69-9bf2-484355c35e4d · outbound

This paper cites On the transferability of pre-trained language models for low-resource programming languages,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective On the transferability of pre-trained language models for low-resource programming languages,

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:46.056192Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6776d6a6-82d7-4b83-b6f4-87836e4d6c05 · outbound

This paper cites How could neural networks understand programs?.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective How could neural networks understand programs?

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.366161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 916b9ab7-51b4-4a95-98cf-906246dc6d1a · outbound

This paper cites Cumulated gain-based evaluation of ir techniques,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Cumulated gain-based evaluation of ir techniques,

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.236116Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f24b88d7-2b00-4b9e-8165-a146d3eeeb29 · outbound

This paper cites Rank- ing neural checkpoints,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Rank- ing neural checkpoints,

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.114749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2b70bd7e-baf6-44b7-8905-f78ef3ba67dd · outbound

This paper cites How stable are transferability metrics evaluations?.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective How stable are transferability metrics evaluations?

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:50.017468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 4ded69ff-5a59-4727-af17-d66b6433a026 · outbound

This paper cites Sup- port vector machines,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Sup- port vector machines,

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.924748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3d7a6650-6882-44ae-8f56-864d4a92fc5f · outbound

This paper cites Numerically stable, single-pass, parallel statistics algorithms,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Numerically stable, single-pass, parallel statistics algorithms,

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.826026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 875fe26b-890d-48d0-abca-910157617443 · outbound

This paper cites chatgpt,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective chatgpt,

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.754744Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1a547e1c-443b-4eca-92d2-7e679794be66 · outbound

This paper cites Deep learning for code intelligence: Survey, benchmark and toolkit,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Deep learning for code intelligence: Survey, benchmark and toolkit,

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:46.294841Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c135fb66-b08f-4715-a3f1-6f01c369323a · outbound

This paper cites Deep code search,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Deep code search,

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.701849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 95598d13-0eb2-4a4d-ac2c-0968527dccb2 · outbound

This paper cites Multi- modal attention network learning for semantic source code retrieval,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Multi- modal attention network learning for semantic source code retrieval,

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.673589Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fee9ecbf-28df-4d6f-afec-a8b11a9d1db5 · outbound

This paper cites Deep code comment gener- ation,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Deep code comment gener- ation,

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.623670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 822f6479-572a-4f71-bd88-349aece3e1c6 · outbound

This paper cites code2seq: Generating sequences from structured representations of code,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective code2seq: Generating sequences from structured representations of code,

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.538601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3b4b3478-cf91-4f77-b5fc-ebec8f405c5a · outbound

This paper cites Improving automatic source code summarization via deep reinforce- ment learning,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Improving automatic source code summarization via deep reinforce- ment learning,

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.464749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6829411e-c4f7-4cca-b1ac-c2bd65361d4e · outbound

This paper cites Reinforcement-learning-guided source code summarization us- ing hierarchical attention,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Reinforcement-learning-guided source code summarization us- ing hierarchical attention,

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.394778Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3f8b1a97-4512-43ef-9890-0f33fc9e63c6 · outbound

This paper cites Modeling hierarchical syntax structure with triplet position for source code summarization,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Modeling hierarchical syntax structure with triplet position for source code summarization,

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.363808Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dc4e6351-b57b-4abc-a7d4-0c4f9a4a744d · outbound

This paper cites Deep learning code fragments for code clone detection,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Deep learning code fragments for code clone detection,

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.305728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7704bcec-8b0b-4e9a-a25b-8c6c60bd5779 · outbound

This paper cites Fcca: Hybrid code representation for functional clone detection using attention networks,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Fcca: Hybrid code representation for functional clone detection using attention networks,

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.277209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 70789677-5eb6-41f4-be06-2538fbf23db7 · outbound

This paper cites Iterative refinement of project-level code context for precise code generation with compiler feedback,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Iterative refinement of project-level code context for precise code generation with compiler feedback,

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.209704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 13effeab-775f-43a7-b349-15314a9f23e2 · outbound

This paper cites Tree-to-tree neural networks for program translation,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Tree-to-tree neural networks for program translation,

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:49.095680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation ffd7c1e8-b36a-4924-b2bd-4567059ea3c7 · outbound

This paper cites Deep learning for code generation: A survey,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Deep learning for code generation: A survey,

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.996146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c25baf2f-46da-43dc-9ef5-e671cf8c2490 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective LLaMA: Open and Efficient Foundation Language Models

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:46.640058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68114ff7-e497-4a21-8868-77554ebe641f · outbound

This paper cites What do they capture? - A structural analysis of pre-trained language models for source code,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective What do they capture? - A structural analysis of pre-trained language models for source code,

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.923438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 74953e52-993f-4cbd-ae3e-eda24f44e02a · outbound

This paper cites Ast-probe: Recovering abstract syntax trees from hidden representations of pre-trained language models,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Ast-probe: Recovering abstract syntax trees from hidden representations of pre-trained language models,

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.882192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d9449691-1c8d-4789-9768-7fd306132172 · outbound

This paper cites Better context makes better code language models: a case study on function call argument completion,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Better context makes better code language models: a case study on function call argument completion,

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.860976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 7a657325-cac2-410b-bfff-71a45761d22e · outbound

This paper cites Towards efficient fine-tuning of pre-trained code models: An experi- mental study and beyond,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Towards efficient fine-tuning of pre-trained code models: An experi- mental study and beyond,

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:46.780005Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8377f6df-becf-46ac-91fe-ce97f6fc64c7 · outbound

This paper cites Automating code-related tasks through transformers: The impact of pre-training,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Automating code-related tasks through transformers: The impact of pre-training,

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.744830Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3b584344-d3a2-451e-bada-b6d04ddc68d3 · outbound

This paper cites Natural attack for pre-trained models of code,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Natural attack for pre-trained models of code,

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.703845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f1037e6d-861a-4f2a-a63e-bdffa20634dc · outbound

This paper cites ReCode: Robustness evaluation of code generation models,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective ReCode: Robustness evaluation of code generation models,

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.682324Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 01779071-668c-426c-9fdb-77cce64dd25a · outbound

This paper cites Status report: Software reusability,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Status report: Software reusability,

Reference 65

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.604750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation d12599ff-893b-4073-a303-294f19005b76 · outbound

This paper cites Software reuse research: Status and future,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Software reuse research: Status and future,

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.454749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c2774b82-e568-4dde-b676-986afe1955df · outbound

This paper cites Ranking and tuning pre-trained models: A new paradigm for exploiting model hubs,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Ranking and tuning pre-trained models: A new paradigm for exploiting model hubs,

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.365518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation c6a1891c-ebff-4073-8f3c-0d00f76a2b1c · outbound

This paper cites Do better imagenet models trans- fer better?.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Do better imagenet models trans- fer better?

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.255522Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0262ffe6-6442-4806-acc6-f815281d96a0 · outbound

This paper cites An empirical study of pre- trained model reuse in the hugging face deep learning model registry,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective An empirical study of pre- trained model reuse in the hugging face deep learning model registry,

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.176770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 9c82f233-4f8f-473c-b9d4-75da43d55797 · outbound

This paper cites What makes a high-quality training dataset for large language models: A practition- ers’ perspective,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective What makes a high-quality training dataset for large language models: A practition- ers’ perspective,

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:48.095440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f5dd5ecd-04dd-4b44-84f6-4de23ef3695c · outbound

This paper cites What to Pre-Train on? Efficient Intermediate Task Selection.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective What to Pre-Train on? Efficient Intermediate Task Selection

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-10T21:51:47.030516Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78a163af-825e-4b69-a162-8da3fb125b42 · outbound

This paper cites Coding- ptms: How to find optimal code pre-trained models for code embedding in vulnerability detection?.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Coding- ptms: How to find optimal code pre-trained models for code embedding in vulnerability detection?

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:47.982010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 2b014794-1c43-48ba-8184-906462b3f745 · outbound

This paper cites Model spider: Learning to rank pre-trained models efficiently,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Model spider: Learning to rank pre-trained models efficiently,

Reference 73

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:47.952437Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fd95b27e-8243-469f-b28d-a53d54499caf · outbound

This paper cites Guided recommendation for model fine-tuning,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Guided recommendation for model fine-tuning,

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:47.904450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 65f83917-4ade-4352-bd7e-d11c445f5254 · outbound

This paper cites Naturalcc: An open-source toolkit for code intelligence,.

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective Naturalcc: An open-source toolkit for code intelligence,

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-10T21:51:47.852120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Coverage vector

Reference resolution

Outbound references

Pith citing papers