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Paper Citation Record · LEDGER

Semantic Source Code Segmentation using Small and Large Language Models

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 1 inbound Pith citation observation for arXiv:2507.08992.

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

pith.paper-citation-record.v1
2507.08992 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T18:14:06.430966Z

measured 43 of 43 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-18T18:24:14.848351Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T18:26:43.754522Z

Reference resolution

42 of 42 outbound references displayed

  • verified exact4
  • verified fuzzy13
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 09e7a8ff-09eb-4a86-b91b-d71589d4abad · outbound

This paper cites GPT-4 Technical Report.

Semantic Source Code Segmentation using Small and Large Language Models GPT-4 Technical Report

Reference 1

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no resolver link, observed 2026-08-06T18:13:05.182319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:05.182319Z digest=sha256:cf227f745b03dfdb590989e194eae83e5ad6e3ee7adee28ec560987d45d2d20a

Observation 5719370e-5cb1-4101-8a1d-b4b47eb5c381 · outbound

This paper cites Monitor-guided decoding of code lms with static analysis of repository context.

Semantic Source Code Segmentation using Small and Large Language Models Monitor-guided decoding of code lms with static analysis of repository context

Reference 2

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verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.237557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:13:05.280709Z digest=sha256:a4764aefebdbf89929937643cfa9937e431caee3674cac11a8094a4b20d5dd80

Observation 47fd636d-a19f-4f9b-9245-3daf2fa244a3 · outbound

This paper cites The claude 3 model family: Opus, sonnet, haiku.

Semantic Source Code Segmentation using Small and Large Language Models The claude 3 model family: Opus, sonnet, haiku

Reference 3

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no resolver link, observed 2026-08-06T18:13:05.351496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:05.351496Z digest=sha256:b9a5bf66193b3e91b49e09775c748a5f76d1554188a29ac2d689b9cd387f2402

Observation b77ce6ce-952f-488b-8fff-afac19e35d8e · outbound

This paper cites Experience with GitHub Copilot for Developer Productivity at Zoominfo.

Semantic Source Code Segmentation using Small and Large Language Models Experience with GitHub Copilot for Developer Productivity at Zoominfo

Reference 4

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no resolver link, observed 2026-08-06T18:13:05.433827Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:05.433827Z digest=sha256:65264311cbb9909c8f70c19a3ede47c2fdef5730d2b85697cb9d0fedb2075517

Observation f681f682-2876-4242-98f0-cce72ee09cda · outbound

This paper cites Improving Segmentation for Technical Support Problems.

Semantic Source Code Segmentation using Small and Large Language Models Improving Segmentation for Technical Support Problems

Reference 5

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verified exact
local_arxiv, observed 2026-08-06T18:14:06.896220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:13:05.534077Z digest=sha256:1461adf2e34b08352934f4b004555d964f10c2fed5f1cedeb52976aa07c88c55

Observation 7d344381-90d3-47cb-a53b-1997c2d5306f · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Semantic Source Code Segmentation using Small and Large Language Models Evaluating Large Language Models Trained on Code

Reference 6

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no resolver link, observed 2026-08-06T18:13:05.637926Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:05.637926Z digest=sha256:437e3e2ce49f41667b739c2f8e2a4d14c33eba9fa47a82736c970b528f4d26fe

Observation 9f62be24-d7e4-44c3-8127-3ea61553da72 · outbound

This paper cites Advances in domain independent linear text segmentation.

Semantic Source Code Segmentation using Small and Large Language Models Advances in domain independent linear text segmentation

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:14:06.853162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:13:05.706019Z digest=sha256:f55abd108cfa8d8b5f6e527f249e58c3a4c2ed661649e7b1d4aa2f5f2be54397

Observation 6a0a3d9d-4c04-4352-87be-812b6f3b9494 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Semantic Source Code Segmentation using Small and Large Language Models BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 8

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no resolver link, observed 2026-08-06T18:13:05.781656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:05.781656Z digest=sha256:356d89163b2a38a09b0dbb574260cd4c1d9f4f840b9f15f418573863bb9f044e

Observation 93da85aa-9701-4565-be52-baa7871d0497 · outbound

This paper cites GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding.

Semantic Source Code Segmentation using Small and Large Language Models GenCodeSearchNet: A Benchmark Test Suite for Evaluating Generalization in Programming Language Understanding

Reference 9

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no resolver link, observed 2026-08-06T18:13:05.849772Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:05.849772Z digest=sha256:a357caf7d0aef49cb963e7c5091d48e7385e71851ad1f878c8e3243d4230b909

Observation 9982aa18-6f5e-4434-9f6e-3631ae910107 · outbound

This paper cites Logical Segmentation of Source Code.

Semantic Source Code Segmentation using Small and Large Language Models Logical Segmentation of Source Code

Reference 10

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verified exact
local_arxiv, observed 2026-08-06T18:14:06.792889Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:13:05.919590Z digest=sha256:9839029e0b2632fda276f0cc9f7a6ff818c921e2c0bdd3152b3976198adb3f09

Observation 60530762-2a9c-476b-8542-5c47402c88cb · outbound

This paper cites LumberChunker: Long-Form Narrative Document Segmentation.

Semantic Source Code Segmentation using Small and Large Language Models LumberChunker: Long-Form Narrative Document Segmentation

Reference 11

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no resolver link, observed 2026-08-06T18:13:05.999683Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:05.999683Z digest=sha256:2f393f3d020c7a2f99c6610591520b9feb6fd8e01ed020ae2f974e4e61703103

Observation 38e6c7cd-620f-44ae-86b4-592c41901aaf · outbound

This paper cites CodeBERT: A Pre-Trained Model for Programming and Natural Languages.

Semantic Source Code Segmentation using Small and Large Language Models CodeBERT: A Pre-Trained Model for Programming and Natural Languages

Reference 12

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unresolved
no resolver link, observed 2026-08-06T18:13:06.126279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:06.126279Z digest=sha256:b2b569f253e7e922a0203a9c994254863208e6a70131ec56e8fa88a45cbcb5f8

Observation 8f6b7f47-6a3f-4ab7-aeda-5037c4ffe9e7 · outbound

This paper cites The limits of the identifiable: Challenges in python version identification with deep learning.

Semantic Source Code Segmentation using Small and Large Language Models The limits of the identifiable: Challenges in python version identification with deep learning

Reference 13

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verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.197133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:13:06.220863Z digest=sha256:46d5c9b594a2348fd93949221cb4586abba3521a043542d5449ed1c77f6e0dc2

Observation 8a6c2fbe-9d23-4453-b8f0-1fe3d9bafab6 · outbound

This paper cites Topic segmentation of semi-structured and unstructured conversational datasets using language models.

Semantic Source Code Segmentation using Small and Large Language Models Topic segmentation of semi-structured and unstructured conversational datasets using language models

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.180963Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:13:06.288372Z digest=sha256:936c2726bfe9752bde328a1993b60fe14c481f8a411a26e0769bc948fb169ec3

Observation 338c9c17-c485-4cd9-a1a2-3da721b00ed3 · outbound

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

Semantic Source Code Segmentation using Small and Large Language Models DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 15

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unresolved
no resolver link, observed 2026-08-06T18:13:06.408039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:06.408039Z digest=sha256:b575e29a4e83ea2c820325102d618a9ddd1ea6a0e25dfdcff47055ba9f574581

Observation 41fd656c-0d31-4d14-84cf-b553a7db0da9 · outbound

This paper cites Qwen2.5-Coder Technical Report.

Semantic Source Code Segmentation using Small and Large Language Models Qwen2.5-Coder Technical Report

Reference 16

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no resolver link, observed 2026-08-06T18:13:06.480669Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:13:06.480669Z digest=sha256:01f1a80707122cdecbca1ba572894722aa7a45cb7c99fcaf7185d26b1d9a8bd8

Observation 816731af-b5ba-4564-b9d7-a77b4c9f4893 · outbound

This paper cites Topic segmentation and labeling in asynchronous conversations.

Semantic Source Code Segmentation using Small and Large Language Models Topic segmentation and labeling in asynchronous conversations

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.163912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.127692Z digest=sha256:d740ff3659f585a06b7732dd66c3c0d04714f46ede673095a45f07d73226e362

Observation ff1c3f9b-44bf-472c-86a8-7a39ce3bcd9e · outbound

This paper cites Text Segmentation as a Supervised Learning Task.

Semantic Source Code Segmentation using Small and Large Language Models Text Segmentation as a Supervised Learning Task

Reference 18

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unresolved
no resolver link, observed 2026-08-06T18:14:06.166674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.166674Z digest=sha256:77e0e9bcd16f757523d895a09049f58bafb7c460965c100822974c5e86b9e239

Observation 750001ce-a999-4303-abf3-a3de6e30c3e5 · outbound

This paper cites The measurement of observer agreement for categorical data.

Semantic Source Code Segmentation using Small and Large Language Models The measurement of observer agreement for categorical data

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.147986Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.242488Z digest=sha256:78aa457fcad9a181831d308571e4369c5f1dd5203a0e22a862bbb57c48654c20

Observation b03177cc-6cc8-4886-8257-fd83b128e5ed · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

Semantic Source Code Segmentation using Small and Large Language Models StarCoder 2 and The Stack v2: The Next Generation

Reference 20

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unresolved
no resolver link, observed 2026-08-06T18:14:06.257855Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.257855Z digest=sha256:20af81b1a36ae0d713c0b1048b8fd444e5dee246b2a0683f32b4c3c80b9aa989

Observation 5b114f65-c8b6-44fd-8faf-bf13eb0c2acc · outbound

This paper cites Text Segmentation by Cross Segment Attention.

Semantic Source Code Segmentation using Small and Large Language Models Text Segmentation by Cross Segment Attention

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-06T18:14:06.656030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.264775Z digest=sha256:ee08f220be65039bc1adb69594bf483858d06d5a9df07312e0427f9a5db8fccd

Observation 64cda335-2d9e-4266-b79c-8d2d921c8338 · outbound

This paper cites Exploring Code Analysis: Zero-Shot Insights on Syntax and Semantics with LLMs.

Semantic Source Code Segmentation using Small and Large Language Models Exploring Code Analysis: Zero-Shot Insights on Syntax and Semantics with LLMs

Reference 22

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unresolved
no resolver link, observed 2026-08-06T18:14:06.271650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.271650Z digest=sha256:279f66b1810f0ed72c9c190d73fb6d65cd5389b7f485621cc45bcb8e8773e98a

Observation 00a13d50-1815-45b6-82c6-0335e3099149 · outbound

This paper cites Evaluating ai-based code segmentation for abap programs in an industrial use case.

Semantic Source Code Segmentation using Small and Large Language Models Evaluating ai-based code segmentation for abap programs in an industrial use case

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.128464Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.277737Z digest=sha256:63b28436bbbae1182f1feb523885c3930cb40861e33235c61e0789b40e20a3a9

Observation 19c379a7-d2f1-47df-8d60-8a847da3f1cb · outbound

This paper cites Beamseg: A joint model for multi-document segmentation and topic identification.

Semantic Source Code Segmentation using Small and Large Language Models Beamseg: A joint model for multi-document segmentation and topic identification

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.112755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.284479Z digest=sha256:0e83c1b540d1b6a403379db6dabcd901d23a4fd94a83a16f1ced452e8c99ff9e

Observation db4aa14f-a804-4390-b5cb-a432b82360ed · outbound

This paper cites CodeGen2: Lessons for Training LLMs on Programming and Natural Languages.

Semantic Source Code Segmentation using Small and Large Language Models CodeGen2: Lessons for Training LLMs on Programming and Natural Languages

Reference 25

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no resolver link, observed 2026-08-06T18:14:06.296411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.296411Z digest=sha256:24476dee5907a5d0e33a0801c28b801e43c8df60809eceae1c9745851c8f38a2

Observation ec221f42-1d6e-4195-932f-3858574aecde · outbound

This paper cites Automated support for legacy code understanding.

Semantic Source Code Segmentation using Small and Large Language Models Automated support for legacy code understanding

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.093788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.323479Z digest=sha256:783c24e32f539ba039a92d4fb92b85dbc5d9ee1b93665d6c12f73dcf6b7658c0

Observation 44efb3c7-5187-4871-8314-6c8a6e217047 · outbound

This paper cites Unsupervised Dialogue Topic Segmentation in Hyperdimensional Space.

Semantic Source Code Segmentation using Small and Large Language Models Unsupervised Dialogue Topic Segmentation in Hyperdimensional Space

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T18:14:06.329912Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.329912Z digest=sha256:68120f33d18254f26087468bfdc1a6e2bf221f065daac813df0c69057a754df8

Observation 281a68cb-8419-486f-a3ea-cd5d1008d3da · outbound

This paper cites Topictiling: a text segmentation algorithm based on lda.

Semantic Source Code Segmentation using Small and Large Language Models Topictiling: a text segmentation algorithm based on lda

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.074454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.337992Z digest=sha256:54150d035c7feb2aa714f1b12c02437e964c9909b7c5d3f9ba844331891be058

Observation 4460500b-3e5a-4c88-9cee-8eca6994d519 · outbound

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

Semantic Source Code Segmentation using Small and Large Language Models Code Llama: Open Foundation Models for Code

Reference 29

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unresolved
no resolver link, observed 2026-08-06T18:14:06.343323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.343323Z digest=sha256:1b45f2d5dac961cee8431ca8de4ef46256d9c1a97141922f56da48f5aa9b5b05

Observation 3de14e9b-3e7a-4019-b5d9-9aa5fbcb355b · outbound

This paper cites Unsupervised Topic Segmentation of Meetings with BERT Embeddings.

Semantic Source Code Segmentation using Small and Large Language Models Unsupervised Topic Segmentation of Meetings with BERT Embeddings

Reference 30

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unresolved
no resolver link, observed 2026-08-06T18:14:06.349554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.349554Z digest=sha256:aee1ccbb3635b760c0cf8a31e1e085d73ab33883364d6292c5085977fbd4a64e

Observation 2188a8eb-b8b7-4f7f-b0dc-3b1d103f4f19 · outbound

This paper cites Chaos to clarity with semantic inferencing for python source code snippets.

Semantic Source Code Segmentation using Small and Large Language Models Chaos to clarity with semantic inferencing for python source code snippets

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.057429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.355212Z digest=sha256:8118a764464755d060f4fc9ce604e2d1c445a1312c200da8ea544c3a2c32e497

Observation cbf3f1ee-b036-42ce-b29c-62457aaec833 · outbound

This paper cites Linguistic approach to segmenting source code.

Semantic Source Code Segmentation using Small and Large Language Models Linguistic approach to segmenting source code

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.034546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.359982Z digest=sha256:dd83a8fcd5d5b494573f863c4a01a496323e338aa05e73e1566bd6544f7364f4

Observation 45b2d580-965c-44f0-834c-c603bc2f61b0 · outbound

This paper cites Text Classification via Large Language Models.

Semantic Source Code Segmentation using Small and Large Language Models Text Classification via Large Language Models

Reference 33

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unresolved
no resolver link, observed 2026-08-06T18:14:06.368007Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.368007Z digest=sha256:cca16d0f3608b8c763fe68d1203716a1250962bf4488e1211570cb52a2e7643b

Observation 34ecd070-83dc-4f30-aa50-6c063fae7f68 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Semantic Source Code Segmentation using Small and Large Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 34

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unresolved
no resolver link, observed 2026-08-06T18:14:06.374612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.374612Z digest=sha256:c43fab548133defefe805fdc29b0d86aabb4474554b46ffe725d99d94a9b0844

Observation 19806ad2-d762-4ed0-9838-1e3f8ff1f20b · outbound

This paper cites Automatic segmentation of method code into meaningful blocks to improve readability.

Semantic Source Code Segmentation using Small and Large Language Models Automatic segmentation of method code into meaningful blocks to improve readability

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T18:14:07.015842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T18:14:06.379437Z digest=sha256:1831276e6b35bedb2ab4d710e57e5df3ef4fab404a01ac70083aa0231dc8b3b7

Observation 1a7c71e1-4a5b-41e7-9338-149820dd4c53 · outbound

This paper cites CodeT5+: Open Code Large Language Models for Code Understanding and Generation.

Semantic Source Code Segmentation using Small and Large Language Models CodeT5+: Open Code Large Language Models for Code Understanding and Generation

Reference 36

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unresolved
no resolver link, observed 2026-08-06T18:14:06.388934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:14:06.388934Z digest=sha256:049a9a3b14b7a25370f0a1d1f36ec86c6b10487b6dde6a482720122012a1d19d

Observation a1ca5300-8a9c-4980-bd76-bf664ce9b666 · outbound

This paper cites Coral: Code representation learning with weakly-supervised transformers for analyzing data analysis.

Semantic Source Code Segmentation using Small and Large Language Models Coral: Code representation learning with weakly-supervised transformers for analyzing data analysis

Reference 37

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This paper cites Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception.

Semantic Source Code Segmentation using Small and Large Language Models Meta-Chunking: Learning Text Segmentation and Semantic Completion via Logical Perception

Reference 38

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Semantic Source Code Segmentation using Small and Large Language Models write newline

Reference 39

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This paper cites @esa (Ref.

Semantic Source Code Segmentation using Small and Large Language Models @esa (Ref

Reference 40

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Semantic Source Code Segmentation using Small and Large Language Models Unresolved cited work

Reference 41

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Observation 69d90398-316e-447f-ade9-e6f252e2c762 · outbound

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Semantic Source Code Segmentation using Small and Large Language Models Unresolved cited work

Reference 42

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Pith citing papers

Observation a11549c5-5733-4f7e-9e45-71aebebbecb7 · inbound

ReDef: Do Code Language Models Truly Understand Code Changes for Just-in-Time Software Defect Prediction? cites this paper.

ReDef: Do Code Language Models Truly Understand Code Changes for Just-in-Time Software Defect Prediction? Semantic Source Code Segmentation using Small and Large Language Models

Reference 8

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