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Paper Citation Record · LEDGER

Readability-Robust Code Summarization via Meta Curriculum Learning

As of 8 August 2026, this Paper Citation Record lists 60 of 60 outbound references and 3 inbound Pith citation observations for arXiv:2601.05485.

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

pith.paper-citation-record.v1
2601.05485 v2

Coverage vector

measured 60 of 60 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-03T11:41:14.745213Z

measured 63 of 63 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-30T01:36:39.836224Z

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

60 of 60 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved60
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

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

Outbound references

Observation b80d743b-0bc3-47be-97da-a4b0fadb055d · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Readability-Robust Code Summarization via Meta Curriculum Learning DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 1

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source=pdf_text observed=2026-08-03T11:41:13.949451Z digest=sha256:9db41b0fb1a4b45454e413fb7c35c45c03e37d209a878c50e67f2e6b5683257c

Observation 33b0b43a-ca2a-4837-b38d-f70fae37c75a · outbound

This paper cites Qwen2.5-Coder Technical Report.

Readability-Robust Code Summarization via Meta Curriculum Learning Qwen2.5-Coder Technical Report

Reference 2

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source=pdf_text observed=2026-08-03T11:41:14.002527Z digest=sha256:38b005dbef7ad4ac1560e4cc1b6de1a9fcb50244007f14d121991668d765d6b2

Observation bc00d741-5326-4214-be51-46b950ceae21 · outbound

This paper cites Code needs comments: Enhancing code llms with comment augmentation,.

Readability-Robust Code Summarization via Meta Curriculum Learning Code needs comments: Enhancing code llms with comment augmentation,

Reference 3

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source=pdf_text observed=2026-08-03T11:41:14.055532Z digest=sha256:e43f49e36d99f350aeb64ef5f972031728cb5f8afc0940d40435f4c9c8f423d5

Observation 2c917284-abbd-474c-931f-9f3b0ce5b159 · outbound

This paper cites LLM-Assisted Code Cleaning For Training Accurate Code Generators.

Readability-Robust Code Summarization via Meta Curriculum Learning LLM-Assisted Code Cleaning For Training Accurate Code Generators

Reference 4

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source=pdf_text observed=2026-08-03T11:41:14.113907Z digest=sha256:92d69629152c35a2b025cddd1f449a107fa70ca048de90a43f954763b807f9e1

Observation 1d7c4e10-f2e9-4e2e-a0c1-55b52490cec9 · outbound

This paper cites How do your code llms perform? empowering code instruction tuning with really good data,.

Readability-Robust Code Summarization via Meta Curriculum Learning How do your code llms perform? empowering code instruction tuning with really good data,

Reference 5

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source=pdf_text observed=2026-08-03T11:41:14.234889Z digest=sha256:168fd8c9e5ebb49a8600d913ef952df7550098f4ee22e1626c8c427c952e7de8

Observation 0db9cecf-745d-4aa5-bc55-440abecbc0e6 · outbound

This paper cites Do comments follow commenting conventions? a case study in java and python,.

Readability-Robust Code Summarization via Meta Curriculum Learning Do comments follow commenting conventions? a case study in java and python,

Reference 6

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source=pdf_text observed=2026-08-03T11:41:14.286510Z digest=sha256:48e7ef32bc1d983d1787783f2cdb68b752e4dd2e3dd48ff952cf665db902aefb

Observation 53834ea6-2d7f-4195-addf-b48f547009e3 · outbound

This paper cites Are we building on the rock? on the importance of data preprocessing for code summarization,.

Readability-Robust Code Summarization via Meta Curriculum Learning Are we building on the rock? on the importance of data preprocessing for code summarization,

Reference 7

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source=pdf_text observed=2026-08-03T11:41:14.393471Z digest=sha256:7bec2e15b029af81d80d2f802a7ba1930463dc10583e94725c0272d91031d86d

Observation 67de2762-a9bc-46a7-bc05-42b36d42df48 · outbound

This paper cites Adversarial robustness for code,.

Readability-Robust Code Summarization via Meta Curriculum Learning Adversarial robustness for code,

Reference 8

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source=pdf_text observed=2026-08-03T11:41:14.555218Z digest=sha256:6a9cad2d3b6617e27d1f4a1bcf6878a07929de815b4b9d3f09ce6a95e7e38bad

Observation 4af5c222-77ee-4f35-836b-115b8cb34c35 · outbound

This paper cites Towards generating summaries for lexically confusing code through code erosion.

Readability-Robust Code Summarization via Meta Curriculum Learning Towards generating summaries for lexically confusing code through code erosion

Reference 9

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source=pdf_text observed=2026-08-03T11:41:14.612253Z digest=sha256:0aab83d5b696672f8416ac1e66687f1fead37ecb1da214012ac1dd43f6a78f8c

Observation 8af120d7-6626-40fe-88c4-293f20bdb6cd · outbound

This paper cites How effectively do code language models understand poor-readability code?.

Readability-Robust Code Summarization via Meta Curriculum Learning How effectively do code language models understand poor-readability code?

Reference 10

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source=pdf_text observed=2026-08-03T11:41:14.630962Z digest=sha256:1efc8ccc4dc56705ec07fa8024a31c8738da81bccdfa1311b910ee1217d72846

Observation 7997bfa0-c06f-4fdd-8028-78de856bbf99 · outbound

This paper cites Beyond chat: a framework for llms as human-centered support systems,.

Readability-Robust Code Summarization via Meta Curriculum Learning Beyond chat: a framework for llms as human-centered support systems,

Reference 11

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source=pdf_text observed=2026-08-03T11:41:14.633183Z digest=sha256:165ca1d8c99ad3a604f6752bc281449ae71d7f2348c6720bba32f33e17861903

Observation 661ff4b2-f767-4ea9-883e-002c4059787e · outbound

This paper cites Contrastive Code Representation Learning.

Readability-Robust Code Summarization via Meta Curriculum Learning Contrastive Code Representation Learning

Reference 12

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source=pdf_text observed=2026-08-03T11:41:14.635721Z digest=sha256:69bd7285a43b1118c29d33b3f066425cd859b087c1a5c513341316be8125476f

Observation 47ac3269-78e2-4c52-beca-44133a6e7a7d · outbound

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

Readability-Robust Code Summarization via Meta Curriculum Learning CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 13

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source=pdf_text observed=2026-08-03T11:41:14.638324Z digest=sha256:5d393c7024e58d80c606abda7a22998b2441ca4a8acf460b6779f2b4db44d229

Observation df309ab7-4045-4d85-89fd-06ed9495e311 · outbound

This paper cites Summarizing source code using a neural attention model,.

Readability-Robust Code Summarization via Meta Curriculum Learning Summarizing source code using a neural attention model,

Reference 14

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source=pdf_text observed=2026-08-03T11:41:14.640934Z digest=sha256:8b3aca2bfd998df91113ee58831d478de309e3765e982ba540cbfbaaeb3d712d

Observation ca70c017-ba67-495d-a0e8-e506af2b8fb0 · outbound

This paper cites Cross-entropy loss functions: Theoretical analysis and applications,.

Readability-Robust Code Summarization via Meta Curriculum Learning Cross-entropy loss functions: Theoretical analysis and applications,

Reference 15

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source=pdf_text observed=2026-08-03T11:41:14.643199Z digest=sha256:10c65797eef27ffcee228ca77cc6c1694a1a1e2791566fe04d3b1827f76e23b1

Observation 20d214d2-a295-4623-91de-a17414e7e43b · outbound

This paper cites Curriculum learning,.

Readability-Robust Code Summarization via Meta Curriculum Learning Curriculum learning,

Reference 16

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source=pdf_text observed=2026-08-03T11:41:14.645362Z digest=sha256:c264ad8488dbd82015ddbbf964eea1c26a3477fbb8651ef24a6dc75957f82217

Observation a2f45312-a65e-47b9-871f-98e36e81ca44 · outbound

This paper cites Evolving culture versus local minima,.

Readability-Robust Code Summarization via Meta Curriculum Learning Evolving culture versus local minima,

Reference 17

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source=pdf_text observed=2026-08-03T11:41:14.647461Z digest=sha256:7758b6d1e4fea6aff25bacb46f8ff6e073a84ffc1688cdd489b5a56d950c4c60

Observation db9227ad-3e98-47aa-8ade-28cf003d635b · outbound

This paper cites Why curriculum learn- ing & self-paced learning work in big/noisy data: A theoretical perspective,.

Readability-Robust Code Summarization via Meta Curriculum Learning Why curriculum learn- ing & self-paced learning work in big/noisy data: A theoretical perspective,

Reference 18

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source=pdf_text observed=2026-08-03T11:41:14.649552Z digest=sha256:abfb11f99ef067611b9f7c4adbc71a5a8bb98ea2c8a14e7d74b35967c0d7b077

Observation 03146a1c-eb77-4cb7-8fb3-190f71a99d0b · outbound

This paper cites Learning a similarity metric discriminatively, with application to face verification,.

Readability-Robust Code Summarization via Meta Curriculum Learning Learning a similarity metric discriminatively, with application to face verification,

Reference 19

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source=pdf_text observed=2026-08-03T11:41:14.651632Z digest=sha256:bca20841b019f56e3aa6dc040e9a5e75b383824e17b814fa413f2a904dd5628c

Observation d4571364-f443-460f-999b-1aa038c9a5b3 · outbound

This paper cites Prototypical networks for few- shot learning,.

Readability-Robust Code Summarization via Meta Curriculum Learning Prototypical networks for few- shot learning,

Reference 20

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source=pdf_text observed=2026-08-03T11:41:14.653894Z digest=sha256:4e9720a3aa5a4898af8129f7e0f709e1a3701bd10b2359ded248c3e7c633f46c

Observation ab0e1962-7e51-43df-a47a-1407a79ece83 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks,.

Readability-Robust Code Summarization via Meta Curriculum Learning Model-agnostic meta-learning for fast adaptation of deep networks,

Reference 21

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source=pdf_text observed=2026-08-03T11:41:14.656078Z digest=sha256:b2cf4411a431ee15197878a0dcdca07389a04d2560f047e9b562a190086086a3

Observation 403b3780-a635-4fd0-b432-5021e0db1122 · outbound

This paper cites On First-Order Meta-Learning Algorithms.

Readability-Robust Code Summarization via Meta Curriculum Learning On First-Order Meta-Learning Algorithms

Reference 22

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source=pdf_text observed=2026-08-03T11:41:14.658382Z digest=sha256:0538477921d6f08aebb763e7187c8f061194cf7e3f4d9c7c6cc7516d918b2eec

Observation 41d65f41-8f81-4843-9736-f1c0acef7931 · outbound

This paper cites Learning a metric for code read- ability,.

Readability-Robust Code Summarization via Meta Curriculum Learning Learning a metric for code read- ability,

Reference 23

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source=pdf_text observed=2026-08-03T11:41:14.661009Z digest=sha256:b27c946d10f3678691fb789fafc05fbb17c8921a3a91c6cc600ddf16db6ca17e

Observation 271448c6-a7f3-4296-8875-4247ea544b9b · outbound

This paper cites Improving code readability models with textual features,.

Readability-Robust Code Summarization via Meta Curriculum Learning Improving code readability models with textual features,

Reference 24

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source=pdf_text observed=2026-08-03T11:41:14.663157Z digest=sha256:22d83235981fe6c6e90df0bd31e10c2e7534f9c793110838c2312b5212045e42

Observation cca6ac96-024b-4310-83a7-943bddb80616 · outbound

This paper cites Towards Learning (Dis)-Similarity of Source Code from Program Contrasts.

Readability-Robust Code Summarization via Meta Curriculum Learning Towards Learning (Dis)-Similarity of Source Code from Program Contrasts

Reference 25

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source=pdf_text observed=2026-08-03T11:41:14.666084Z digest=sha256:0ca1959b49302a93b4ab33d14e94ef35917cb82d09f9dfaea8890ae2846825a9

Observation 37353c3c-235b-4a4d-a48a-8e460d876107 · outbound

This paper cites NatGen: generative pre-training by “naturalizing.

Readability-Robust Code Summarization via Meta Curriculum Learning NatGen: generative pre-training by “naturalizing

Reference 26

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source=pdf_text observed=2026-08-03T11:41:14.668481Z digest=sha256:6900a467ac49dfe50609819a3d047d30298391fe7ca1c8c3eaf39da19ffae8a2

Observation efd97d9a-048b-4368-8966-6a485a6d9d9f · outbound

This paper cites Structured Neural Summarization.

Readability-Robust Code Summarization via Meta Curriculum Learning Structured Neural Summarization

Reference 27

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source=pdf_text observed=2026-08-03T11:41:14.670732Z digest=sha256:6d88620691090d8f654e51ebd8c4dbc307c8ea1d0138d9f6aeb5394dbd638d00

Observation a6439d37-9615-4214-800f-9b66f29bc8e3 · outbound

This paper cites Neural reverse engineering of stripped binaries using augmented control flow graphs,.

Readability-Robust Code Summarization via Meta Curriculum Learning Neural reverse engineering of stripped binaries using augmented control flow graphs,

Reference 28

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source=pdf_text observed=2026-08-03T11:41:14.673283Z digest=sha256:a6315ba9b3c6a1277512e1f63598289b945bbb46d242b20a99e087a15497807c

Observation c8fd30d6-fb56-4dda-b395-3c971eb8c4b6 · outbound

This paper cites Debin: Predicting debug information in stripped binaries,.

Readability-Robust Code Summarization via Meta Curriculum Learning Debin: Predicting debug information in stripped binaries,

Reference 29

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source=pdf_text observed=2026-08-03T11:41:14.675506Z digest=sha256:1326303b72b85e4b51722b2682cc6c908d8048ce1fcf15ae11d8e92c4523dc42

Observation cff88d72-c32d-4208-aaa6-1b3759a5bdb6 · outbound

This paper cites Measur- ing neural efficiency of program comprehension,.

Readability-Robust Code Summarization via Meta Curriculum Learning Measur- ing neural efficiency of program comprehension,

Reference 30

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source=pdf_text observed=2026-08-03T11:41:14.677561Z digest=sha256:a1de2e2da9f91869f252abaa0c700909d2785e8f22ef71ed2fb5aec81a24a149

Observation 35d91b9d-1bba-469b-aad4-2c7de89fec47 · outbound

This paper cites Understanding understanding source code with functional magnetic resonance imaging,.

Readability-Robust Code Summarization via Meta Curriculum Learning Understanding understanding source code with functional magnetic resonance imaging,

Reference 31

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source=pdf_text observed=2026-08-03T11:41:14.679672Z digest=sha256:c97d02c0346182f6ade0a3509841dd544c3f6e7cf8b060b2ff9b7babeaad6223

Observation d6e0c41a-fb56-4ca0-8c4e-65f2f3f442e4 · outbound

This paper cites Contrastive code representation learning,.

Readability-Robust Code Summarization via Meta Curriculum Learning Contrastive code representation learning,

Reference 32

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source=pdf_text observed=2026-08-03T11:41:14.681784Z digest=sha256:4c30b128594e3db2a55a228bdab2ca2bff823d902a6295943cbd75f3d1a9d2c7

Observation 3c816ed2-bf73-453b-a052-38deb6ab834a · outbound

This paper cites Qwen2.5 Technical Report.

Readability-Robust Code Summarization via Meta Curriculum Learning Qwen2.5 Technical Report

Reference 33

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source=pdf_text observed=2026-08-03T11:41:14.683840Z digest=sha256:67d0791ae394a6cae381cd127fb95087cbe6052b14a607cd4186e29f90c48cda

Observation 1afa853b-bd51-4f6e-8181-3509197b1dce · outbound

This paper cites DeepSeek-V3 Technical Report.

Readability-Robust Code Summarization via Meta Curriculum Learning DeepSeek-V3 Technical Report

Reference 34

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source=pdf_text observed=2026-08-03T11:41:14.686285Z digest=sha256:4d010dd23305023129dd169cadfd87e553cce932cfc9d61d2cef34bf5f58c93f

Observation 7cf76613-aea8-455a-9989-b10bbe8364cb · outbound

This paper cites Introducing gemini 2.0: our new ai model for the agentic era,.

Readability-Robust Code Summarization via Meta Curriculum Learning Introducing gemini 2.0: our new ai model for the agentic era,

Reference 35

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source=pdf_text observed=2026-08-03T11:41:14.688565Z digest=sha256:eef04361f1ddfaa051c4e1ad21db64e8011f70df64a655ee704f8843b684e9cd

Observation 4a8b2644-879c-4b7e-8b86-34a663371084 · outbound

This paper cites Claude 3.5 sonnet,.

Readability-Robust Code Summarization via Meta Curriculum Learning Claude 3.5 sonnet,

Reference 36

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source=pdf_text observed=2026-08-03T11:41:14.690926Z digest=sha256:0d6d8d569c66a1e1e93915b8edf439815b778797eb92f4966770cec16d2bfe89

Observation 8f2445d0-add0-4f26-88bf-cc9e2dc600cc · outbound

This paper cites Hello gpt-4o,.

Readability-Robust Code Summarization via Meta Curriculum Learning Hello gpt-4o,

Reference 37

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source=pdf_text observed=2026-08-03T11:41:14.693190Z digest=sha256:7744985b1d057c7cf133688fc33e2d9cdb5fcad26479568780680cf7100ea8fe

Observation b1bac715-b6bb-4c51-a81a-6ebe01960937 · outbound

This paper cites Orange: a method for evaluating au- tomatic evaluation metrics for machine translation,.

Readability-Robust Code Summarization via Meta Curriculum Learning Orange: a method for evaluating au- tomatic evaluation metrics for machine translation,

Reference 38

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source=pdf_text observed=2026-08-03T11:41:14.695227Z digest=sha256:de2cc51abfd4a92524f785d57ebc6d08ee9f620a259d6ced9948acf230964981

Observation 35c6ffc8-de7f-427c-8b08-0a0340e8900d · outbound

This paper cites CodeT5: Identifier- aware unified pre-trained encoder-decoder models for code understanding and generation,.

Readability-Robust Code Summarization via Meta Curriculum Learning CodeT5: Identifier- aware unified pre-trained encoder-decoder models for code understanding and generation,

Reference 39

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Observation 83b98949-5a20-4108-aa21-899431079cef · outbound

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

Readability-Robust Code Summarization via Meta Curriculum Learning CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation

Reference 40

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source=pdf_text observed=2026-08-03T11:41:14.699865Z digest=sha256:9a972b435dd8f7e9071288c8c12f68d8cb91abe75114776360f229bbe36309b3

Observation 81165051-ace4-4a7a-873c-5d265cdb8068 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Readability-Robust Code Summarization via Meta Curriculum Learning Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 41

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source=pdf_text observed=2026-08-03T11:41:14.702387Z digest=sha256:6ad94794d6fd39f5a08fcf2a808eb95d4d3f29b989006560293f99a4c0c640f5

Observation 9e032804-bb78-4cc6-ab0d-daeb172097b1 · outbound

This paper cites What makes good in-context demonstrations for code in- telligence tasks with llms?.

Readability-Robust Code Summarization via Meta Curriculum Learning What makes good in-context demonstrations for code in- telligence tasks with llms?

Reference 42

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source=pdf_text observed=2026-08-03T11:41:14.704944Z digest=sha256:154cbef8044be731dc23b5a5fb498f3e41733e28c13c52e599dfcd11d182f19b

Observation bdebf47e-5d24-4a7f-b915-8349fd664c73 · outbound

This paper cites Element-aware summarization with large language models: Expert-aligned evaluation and chain- of-thought method,.

Readability-Robust Code Summarization via Meta Curriculum Learning Element-aware summarization with large language models: Expert-aligned evaluation and chain- of-thought method,

Reference 43

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source=pdf_text observed=2026-08-03T11:41:14.707199Z digest=sha256:923ffc74348aaf857c253b0fc1df8f83f4dc933072049e7fe55d337331a47c13

Observation 739a7843-f203-4b92-8747-e939cadd5f44 · outbound

This paper cites Language models can solve computer tasks,.

Readability-Robust Code Summarization via Meta Curriculum Learning Language models can solve computer tasks,

Reference 44

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source=pdf_text observed=2026-08-03T11:41:14.709444Z digest=sha256:d9afcfe69ed27e47bb6d03dd98f8583238b7ae2bd36df4587d8b6e6fa244e885

Observation f6a5ee52-690b-494a-a02e-660051765838 · outbound

This paper cites Source code summarization in the era of large language models,.

Readability-Robust Code Summarization via Meta Curriculum Learning Source code summarization in the era of large language models,

Reference 45

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source=pdf_text observed=2026-08-03T11:41:14.711585Z digest=sha256:7e344025a51ae8fec0c9d3c53b9e0ba7f729da8322ed8da1ebe2e1409fe82cfc

Observation b323c798-8301-4896-a39f-27906038d455 · outbound

This paper cites Pruning the unsurprising: Efficient code reasoning via first-token surprisal,.

Readability-Robust Code Summarization via Meta Curriculum Learning Pruning the unsurprising: Efficient code reasoning via first-token surprisal,

Reference 46

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source=pdf_text observed=2026-08-03T11:41:14.714001Z digest=sha256:6c49a399bda31ae9483ec1ef17794a74897c8b60fa5e78c396501e1273a42f3d

Observation 3e53d429-6a99-4cbb-b9a5-b835cfb4d26d · outbound

This paper cites GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of Thoughts.

Readability-Robust Code Summarization via Meta Curriculum Learning GlimpRouter: Efficient Collaborative Inference by Glimpsing One Token of Thoughts

Reference 47

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source=pdf_text observed=2026-08-03T11:41:14.716110Z digest=sha256:6be976c11918cbf85623bae99d29a31f7b9b6727d5b448fe3ff59a50981a3eaa

Observation bedf1d7a-8dfb-4548-991c-96fcba171751 · outbound

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

Readability-Robust Code Summarization via Meta Curriculum Learning CodeBERT: A pre-trained model for programming and natural languages,

Reference 48

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source=pdf_text observed=2026-08-03T11:41:14.718484Z digest=sha256:0f2989369fa6bf3554d87d18387b40c5329d70e8f7b781b20ac877005cbadc74

Observation 4f231056-cc80-4cff-9ce9-5596f221e23d · outbound

This paper cites Stack overflow developer survey 2022,.

Readability-Robust Code Summarization via Meta Curriculum Learning Stack overflow developer survey 2022,

Reference 49

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source=pdf_text observed=2026-08-03T11:41:14.723337Z digest=sha256:0ea924709e6dcd7fab491f3283c980d20631d47206a76730a0500526e36e05cc

Observation ddf8cf1e-d71c-4f0d-b8e6-bf1352f5d77e · outbound

This paper cites Tiobe index,.

Readability-Robust Code Summarization via Meta Curriculum Learning Tiobe index,

Reference 50

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source=pdf_text observed=2026-08-03T11:41:14.725508Z digest=sha256:62115928da5c864a288d805539a8ece7eb456f05388b5c506e673f331ac23b50

Observation 6b13db12-4fb0-4f8a-aacb-ad69a22c4696 · outbound

This paper cites Bridging the cyber-analysis gap: The democratization of data science,.

Readability-Robust Code Summarization via Meta Curriculum Learning Bridging the cyber-analysis gap: The democratization of data science,

Reference 51

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source=pdf_text observed=2026-08-03T11:41:14.727842Z digest=sha256:33cd23974a67e148d642e017a569c5ed218a117dbd60865d906cb9fbff5104ec

Observation a737f1dc-e9da-4fc2-b488-40e8efb5de45 · outbound

This paper cites In Line with Context: Repository-Level Code Generation via Context Inlining.

Readability-Robust Code Summarization via Meta Curriculum Learning In Line with Context: Repository-Level Code Generation via Context Inlining

Reference 52

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source=pdf_text observed=2026-08-03T11:41:14.729996Z digest=sha256:2a9652f7fd766cca5c99b4c795ac0bbebdd4b99b2468817837445d40c06ce84c

Observation c08ae329-712a-4d9e-beff-d12d887a1607 · outbound

This paper cites From code to cor- rectness: Closing the last mile of code generation with hierarchical debugging,.

Readability-Robust Code Summarization via Meta Curriculum Learning From code to cor- rectness: Closing the last mile of code generation with hierarchical debugging,

Reference 53

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source=pdf_text observed=2026-08-03T11:41:14.732291Z digest=sha256:39546d9b137fd8f9f84571d53f813a9035c58552c1578d8e0fd01f3c4c6486e8

Observation 1674c28d-3627-4080-84b6-33ed303656a6 · outbound

This paper cites Between lines of code: Unraveling the distinct patterns of machine and human program- mers,.

Readability-Robust Code Summarization via Meta Curriculum Learning Between lines of code: Unraveling the distinct patterns of machine and human program- mers,

Reference 54

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source=pdf_text observed=2026-08-03T11:41:14.734347Z digest=sha256:4ee946015080bd7cc3c2398a4206b550e450e0610510a5cf1cf4d72a05cf99d9

Observation 125af946-d7d3-43f0-b689-60a9fbb53f56 · outbound

This paper cites SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution.

Readability-Robust Code Summarization via Meta Curriculum Learning SWE-Debate: Competitive Multi-Agent Debate for Software Issue Resolution

Reference 55

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source=pdf_text observed=2026-08-03T11:41:14.736467Z digest=sha256:6a59ebf89454ed238a0426d2a41d4429dd27ccbc2d7660f53fc49fc24ed7bef3

Observation 41e1de39-4890-49c9-b668-60ea085cdfdd · outbound

This paper cites The impact of identifier style on effort and compre- hension,.

Readability-Robust Code Summarization via Meta Curriculum Learning The impact of identifier style on effort and compre- hension,

Reference 56

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source=pdf_text observed=2026-08-03T11:41:14.738789Z digest=sha256:43a14b4e1141cb790d6b776294ef87ae482bd2bd53fd82b845dff86253600fb5

Observation 78e2dc91-a1ed-48eb-a9dd-6787723754dd · outbound

This paper cites Clawsat: Towards both robust and accurate code models,.

Readability-Robust Code Summarization via Meta Curriculum Learning Clawsat: Towards both robust and accurate code models,

Reference 57

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source=pdf_text observed=2026-08-03T11:41:14.740871Z digest=sha256:fba54e1b9b3b1e2551f438638f57b7b61818a9d8d71b20b162fefadbf7e4ffc3

Observation 2917fde9-6f3f-478e-aea9-5578e7855c2b · outbound

This paper cites Meta-curriculum learning for domain adaptation in neural machine translation,.

Readability-Robust Code Summarization via Meta Curriculum Learning Meta-curriculum learning for domain adaptation in neural machine translation,

Reference 58

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source=pdf_text observed=2026-08-03T11:41:14.742977Z digest=sha256:f07f8821e2f7569f74e1780fe515fff950626a768e918ecc9b0c9a5452ad4818

Observation dcb87cb7-0461-4aef-b16a-c3df9b3d581e · outbound

This paper cites On the evaluation of neural code summarization,.

Readability-Robust Code Summarization via Meta Curriculum Learning On the evaluation of neural code summarization,

Reference 59

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source=pdf_text observed=2026-08-03T11:41:14.745213Z digest=sha256:39964968528f18b8cadf3bb1725dccb7cab6e6d9b0f58327a997f14f444a95ee

Observation 6361f2c0-d169-4c91-9a6a-288ddcb1014f · outbound

This paper cites Available: https://aclanthology.org/2020.findings- emnlp.139.

Readability-Robust Code Summarization via Meta Curriculum Learning Available: https://aclanthology.org/2020.findings- emnlp.139

Reference 1547

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source=pdf_text observed=2026-08-03T11:41:14.721093Z digest=sha256:70b798874508886c770342eb82ca6baeb0cd4d63ab54025d45c1e6a5a0c5ad23

Pith citing papers

Observation 96398156-b907-4d8c-909d-622b869e4be2 · inbound

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding cites this paper.

CodeOCR: On the Effectiveness of Vision Language Models in Code Understanding Readability-Robust Code Summarization via Meta Curriculum Learning

Reference 106

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arxiv_id, observed 2026-07-30T02:04:29.175019Z

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.

source=pdf_text observed=2026-05-16T08:30:50.984873Z digest=sha256:dab74130f545a706804621603cf27b3cd63d7d2e8d8d35fd08aedc1f2ebadc21

Observation 15e2ede5-48eb-4b59-a6f8-0111222f56a7 · inbound

ShredBench: Evaluating the Semantic Reasoning Capabilities of Multimodal LLMs in Document Reconstruction cites this paper.

ShredBench: Evaluating the Semantic Reasoning Capabilities of Multimodal LLMs in Document Reconstruction Readability-Robust Code Summarization via Meta Curriculum Learning

Reference 26

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arxiv_id, observed 2026-07-30T02:04:29.175019Z

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.

source=pdf_text observed=2026-05-08T06:34:56.032634Z digest=sha256:f756a653c2d459f936144624abc51ce1d0bc6807b2eae0c40f80853d87a3ea8e

Observation 2cda7514-34ff-4a16-9d57-59e1d58e30c1 · inbound

SWE-MeM: Learning Adaptive Memory Management for Long-Horizon Coding Agents cites this paper.

SWE-MeM: Learning Adaptive Memory Management for Long-Horizon Coding Agents Readability-Robust Code Summarization via Meta Curriculum Learning

Reference 62

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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.

source=pdf_text observed=2026-06-30T01:36:39.836224Z digest=sha256:636cd4bfd8c81131cf95a7b90a83affb1ff3e45d5736b32b1b1064364827dd33