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Paper Citation Record · LEDGER

Readability-Robust Code Summarization via Meta Curriculum Learning

As of 22 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 2026-08-21T06:32:19.484+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:e669b3a43afac32ca517bb4dafa377e9b77706deebe4b31107fd85f4d6c4b02d

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:fb9e03576fe68b338e2370f22d7170bb9b406b684b4128044c529d6544ee929a

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=sha256:353f8df2390760a21a28c92e6f49cc6c75676959e35557e5133f3765b3bf759b

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:f2d4989bec150f36b9e03837c2da8c588ec0b2e64bb24fa1b2fbfa06d99300f9

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=sha256:507c201f2998bc54ab45d647c442bfc5010961b9df7fad34a618a74d14a87c5d

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=sha256:697f57c116512daf615340bd4ad9556bc44036f023f391090f22d7ed83cde03c

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:f11abb7e35a6c45f76a5a44cee58b512568bd41ef3f15038319e26fd993c1e7f

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:e777e0ae8861162ce1e9bd74e9ec80d8c0531454f4bd0252ec7cd7ebd37e6d00

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:a76ad9f4efe57021afc6fc1aec81a7f66c354c3fc9879757a4d82d33d57f988a

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:acebe76b34abfef1d3f61b2ccef8984598bd003f27c9cd6239f81cd7c5a2cf76

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=sha256:154fae96d5e3ef90448bb5c99130b87515cf46de0650d1c9fc29d544e799a4b6

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=sha256:3bcff5ac2a14fbcd4893b6ded666bb40f48013405d069a55f52e3d4c7c5e2b4f

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=sha256:112f87e9f720b844404456867a3f417a25ff8cfac6169a20285376297075eb44

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=sha256:6acf9fafc53b92e917c20118095550fb51871da6da1d0f8b055c33d632e35fda

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=sha256:74ec891c86e5f529d0a82d05b37e424dfa0abba7aa320e5174fc8fe5994582b2

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=sha256:6c21aad5f058537fc50d7850f7432e3e7820e34231255dcc3036456e6e153158

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=sha256:5e00592ab9e17448ec7183c5a3c2c43521d444804bfb28582b10259a08279040

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=sha256:8562f36528ad950ad8d40f29a58db5b78b302f218f54fae51c8468e5e71ff07d

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=sha256:5c9b90f27fdf2d936ad68f9cf649904ee2b835d3f183ff92e9fd127e321edf92

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=sha256:3686bce1e1cea28b8937139dc73e8ac412c0994e600222d0ad1ff01eb3e8dec2

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=sha256:48b7855a12dc2e48c35e597075f5e1f10725bf2183b9f5ff16bd519d47bbf904

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:b35f63894f87b94e597698b1b05cacfb28b19262ce5c6d57b3657df31263ab65

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:c03ea9776745fac6e83cde768c1fb8fe5cd67d85cf7bf9660a159af1147efcde

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=sha256:75dda4ff62f282fdc835cf9a289a37de23dfc8f0d058f0bf2245f80d3e31e33e

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=sha256:14b8bfba57e19bc8c191293a86180e4a4f1fefbdd526efb4e0f0b8001a02234a

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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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=sha256:45cc8e8f3d5ebab9194082b8e5e5c1bf0cc87fee74372f8ab2460474d62f9420

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=sha256:4b429f2f0935f318bfd2d4c0c17db82fe07dea55293ce5e5da965b06c2fb12e0

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=sha256:7f6e844bdcffe7d213e8d90f8b51cd3572dc2a1e40e61a7cdd6abca5684dcec5

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:ce49207b081931865e2a2b41d59a331861fdbc849ab0c5489eb34a2390062b9f

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:bc2a8651740cdc5fe6083bd558f65ab8c889c8316094b02dabb653249212107a

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:b515db63cccdec2b3b788ddd9901d9b8fd1786a08571f8500ab9b451160a67c7

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=sha256:3b3b369deb72fc292cf11f0c4d627cd19284ae145deefcb3ebf3f0ceb6194ca3

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:ce241c78f8113aa70d055da0eee776f75e1342f85aff8936db72a6be3414fc59

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=sha256:93465406f3a9ab688494d3aa3abb3115aba49e6aa72433b0366d2ee27a22fc0c

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=sha256:3a5105990a6e205c1132ffc4f6f740d92f0c29e9c1ac8bd1a25eb2f435002757

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=sha256:59ee60bdeb6ac2f45cd50a801432746eec1e8681339b7e043f2567b7566b9b72

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:ada447cdd1523ce95598ebfbe1b5165b774a0d66fc1ee7889bc216e61713254d

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:b7abde3d21d1d36dde2318ba9070683f30d00533b3d6a458c29d416e7fd33edc

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=sha256:1556212e70a5d5788e4cc44737fefa9a3377f070b1272efd8e75837296c53f8c

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=sha256:7e74b6da0e500849658f61dbe85bfefda06153ad862b4d69ae2c4c448a759d7c

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=sha256:4c605d91b2cdb0d00cfa907c9eb8f565a876272be716b08361112bdb30acc33f

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=sha256:38ffa22c6ae14f998b1ea726d3f6310cfe4647dce6cf1d061de83f026c475918

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=sha256:6dd13b2c0c7db93a2c7a3cc7583a732762ca81865cf594cd60cde51d2046d3f8

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=sha256:6aff07f10ec4b410d748e181f5fd750024e0aaac8611da365a64b89e0d0e52f5

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=sha256:2670694e02be2629bd931082bca12934f82c3cca2aae6ea6316f16b59e28cb6d

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=sha256:3ed77af1ae49b0450e031e1dfbbc6a1ae227a6d57885ee93d7236d0d49c56293

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:fe9c7c87c64167fa217ecf93d70f2a214a1cd62e11b1dd3d41e5a218b8f4cc5b

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=sha256:3ef8a51ed34b1c645a2426db706b72fc78bb0cacb08bde5184827a68670c25fc

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:bcc302de92c6b6ebac175b3dab73b44c4c0901b33421257bdf5dab4a67168cc4

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=sha256:58995837ef661f0423da6ddf0d8f85a17c42530600c6cae7505502b95f223efb

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=sha256:0fdef4c93fb0d3c7129f7843b7c57bb711e8cf8dab66b89048326e43c6ea999f

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:c2d062d37fa974a17363e6ee300ad29286ad4ae39d6f65693b1d200bd95fdae3

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=sha256:8714a7a66be851429a066d790bb07913f174fa559c6f68176fe267a5bd62f27a

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=sha256:12ae3e9057af7ef6d007d8092d266fe897998fe0bfe55a73a2fc1cc109171805

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:be7c0dccaef1499e47371c20dd47a6d90bacb5f9c26ba8436ba6973c2f55face

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=sha256:1686ed00e55cb87af6d8bedf221f66657eab00cdee43cd4cdc9511088cce955c

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=sha256:368f9d3ce16c1074c4cad347acbfd83c27bf3b6ab6ef62f4bd3c7b2aa4b8f960

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=sha256:79c5021df8ce2732dd2777ca53c097838769bcdfd846ca9b3d847eef6f19edf6

Pith citing papers

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

Seeing is Coding: On the Effectiveness of Vision Language Models in Code Understanding cites this paper.

Seeing is Coding: 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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-16T08:30:50.984873Z digest=sha256:6a1913f338eef084ab3306a915629597e058c101d5271194dd066505ca2c3315

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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-05-08T06:34:56.032634Z digest=sha256:4dd20526b563a5a022932c98d159279a3499da8c2a4ca9e47b06ade6fecb11bb

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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metadata mismatch
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 2026-08-21T06:32:19.484+00:00.

source=pdf_text observed=2026-06-30T01:36:39.836224Z digest=sha256:d8f5e9b67dd4e5d89d8b0703ee4462b1e00762813ab0825fa0119440b00d513a