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Paper Citation Record · LEDGER

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

As of 23 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 100 inbound Pith citation observations for arXiv:1909.09436.

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

pith.paper-citation-record.v1
1909.09436 v3

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-12T16:06:20.777086Z

measured 126 of 126 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 100 of 186 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:18:18.282105Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

26 of 26 outbound references displayed

  • verified exact7
  • verified fuzzy1
  • unresolved17
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

422
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation e8fbc25a-1b44-42d9-aa25-0dc7ff2bbe5e · outbound

This paper cites The Adverse Effects of Code Duplication in Machine Learning Models of Code.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search The Adverse Effects of Code Duplication in Machine Learning Models of Code

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:06:20.843694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:5eb5fdbd5099a87573328baeed78ffe700a490de0a3f0cf7baeaa29b794c5de1

Observation 1c07b74e-39a3-4d98-8d4b-848f5dee59c1 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.893445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:57ae235437d7156c934fe75aa5f4306f811ca8cf064f21327091d2be0819257b

Observation 478491d0-04af-487f-9fc1-77873cf604d7 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.896331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:af77f890b91fe630445650fcea656e4f33f37a9a01160ba6285a09a2fc64ef1c

Observation 5c5cd0ef-7e04-4986-bb31-7e92039e5d9f · outbound

This paper cites code2seq: Generating Sequences from Structured Representations of Code.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search code2seq: Generating Sequences from Structured Representations of Code

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:06:20.836991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:b7a3016074d12be750724deaed1ccbff2ef7dcc97cae792962b5b788bab59558

Observation 655f4c85-919f-49b4-a2aa-de72ffdadf42 · outbound

This paper cites A parallel corpus of Python functions and documentation strings for automated code documentation and code generation.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search A parallel corpus of Python functions and documentation strings for automated code documentation and code generation

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:06:20.806141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:d5fa047d404141a98a26f1729ec5f7afd52af2cfa2920797138ee0c878bb8671

Observation 94cf4a5c-abdf-471f-88e3-6cfe93028226 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.899679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:5b11722db829cdde3654b500cd937ebb6534e65556e8d966449492c487f5c731

Observation f813163b-b8dc-440d-ad5b-1423fffca25b · outbound

This paper cites When Deep Learning Met Code Search.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search When Deep Learning Met Code Search

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:06:20.799494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:a8a38c55f7396e28a61bd8accfa6191c215d2067635fcc01cd61e18421d389f2

Observation ab27454a-59a2-4061-bec7-0eceb991e623 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.903902Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:5b9bb0c9e5a7fe3ce6556f4ecff2dce2061145825fa1cb36279ea5860b604ea1

Observation 71965753-68bf-46ad-9d5a-656f4cea75ba · outbound

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

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 9

Resolution
metadata mismatch
local_arxiv, observed 2026-05-12T16:06:20.811964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:cc67baf7db05d2032314d120cf31a46c38a3be2f3c988e1159b4a20b763f1d35

Observation 44f0d299-8bc1-4db0-99e6-0986a1e8c84d · outbound

This paper cites Structured Neural Summarization.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Structured Neural Summarization

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:06:20.831146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:b010a2cc3dd9494556a40bfa6d9acff657529a1e17321ff920f7660bb46e09e2

Observation 49e1111d-859c-4032-930e-0ec2c5201467 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.907027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:1b0b2f75720663d64231d7a8c4128f68f1f13cea54cbaf7752330d8a94ad9858

Observation e116053f-3a54-4152-8ce3-bdc77f187296 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.909993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:60f94c970c7ae8165e919ea4a4ede6ddb2b8ebf04565c60c5e0610bfae60c96d

Observation 326b1bf2-ced9-44f4-883f-552b1660e82d · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.912833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:7fb262a804c69fdfb0bf47070857a18face3df420db95a8a814428d14cf7d99d

Observation 2105ad0f-f4ae-4783-a4f0-852f3f069911 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 14

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.848330Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:43866d2aeeb18317918cb50853066b6b755da794830eb6c44ee2a32154138489

Observation e5ad2e0c-5e60-4c6f-a8a1-02cc4392adca · outbound

This paper cites Mapping Language to Code in Programmatic Context.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Mapping Language to Code in Programmatic Context

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:06:20.819524Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:c67dc030028c83ab18a42ee9214cc5a8a8a2c6311c419ff6524d5743edeae4eb

Observation ae20a6c2-c2c4-4a21-8790-286745953fdd · outbound

This paper cites Convolutional Neural Networks for Sentence Classification.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Convolutional Neural Networks for Sentence Classification

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:06:20.826002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:4d9899ea1a8356511350e18e78eec65be2c50d354c286140536f7d8df0c9900e

Observation be308919-9a1c-4d63-be2e-afe7592ea50a · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 17

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.851980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:975ecffd1f3bc707216e50c8eb996778f559d417aa0296d2cf572f3e6bc9448f

Observation 18ac5f94-1de8-4c0e-9cbc-a7c70fab269c · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 18

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.856130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:24af73d90a0aa1bb5af5648c7cf42cf5db1137322521e34a35bfe3df56113edb

Observation aaf76222-1656-4f5e-a387-dcb2347b87f7 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.859152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:1ffecdbc6cd3437aee5e51ff4b4c0385fe3001074ad78411d5400258c0b8d2ce

Observation 7d85de7b-2cdf-4ae4-b625-d2365db276b8 · outbound

This paper cites Manning, Prabhakar Raghavan, and Hinrich Schütze.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Manning, Prabhakar Raghavan, and Hinrich Schütze

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-05-12T16:06:20.862965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:92ce207f5467aa561399548e1161aff2dfb4ae335b733d4c688cd6a10fb2d9d3

Observation 6d4d386c-20b0-4970-b16d-5df0d9a7209c · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.866645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:bba4dd50bce9e823c35e56d285325f702c0f40e8f12c71a60535ec1aa3c7bb92

Observation 7f721442-25b4-4117-8c1f-312a2f3a6994 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 22

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.871705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:f88667c54243164e5a85abbfb137b3b5aa29a1f9dcb7156cc31c90060f1f445b

Observation 9bcb6e5c-4bcf-45b0-9e48-26ce925164b8 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 23

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.878499Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:f1f568f83ee250a8d4b9ed4d5edb809d99b5e14a0f299ac7469e5e4c0676088e

Observation 9cd3dda5-faf3-4a42-812c-ba2540e2f774 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 24

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.882515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:9ced5102ea9fbf24e0be0ea7af47100106ba49e20e74c6293d59d12f6b6fca3f

Observation 304a60a6-a47c-41c5-ba79-f901aba417ae · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.886047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:8bd9a91ffdb902b8728f56b9c6381b1364979d466b0e7918e89e810dc40fe28a

Observation edc88197-ca36-41f2-89ae-8452dc301d47 · outbound

This paper cites an unresolved cited work.

CodeSearchNet Challenge: Evaluating the State of Semantic Code Search Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-05-12T16:06:20.889016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-12T16:06:20.777086Z digest=sha256:09bf0778e880cec2cfe1228c22ec4537b530014bb5054f0d6a8feb2e869701a2

Pith citing papers

Observation 14955081-cb65-4099-85e6-31b77630e422 · inbound

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

CodeBERT: A Pre-Trained Model for Programming and Natural Languages CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-05-13T21:04:26.307854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-13T21:04:26.198288Z digest=sha256:d9e7bcdf17345ccd333e8741621de0f387e18ae924961598809cba4b3b3b2008

Observation 2c362401-3a3c-4d41-89fd-2005c6f64c85 · inbound

GraphCodeBERT: Pre-training Code Representations with Data Flow cites this paper.

GraphCodeBERT: Pre-training Code Representations with Data Flow CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 8

Resolution
verified exact
local_arxiv, observed 2026-05-15T08:46:10.929161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T08:46:10.892060Z digest=sha256:901592ca91cdf9ab0e1f098f1a163a2a94893300cfb31d1cd693e1898afdb7d4

Observation 9f55b6bf-58bc-45c3-b994-bbd5fb320d6e · inbound

CodeBLEU: a Method for Automatic Evaluation of Code Synthesis cites this paper.

CodeBLEU: a Method for Automatic Evaluation of Code Synthesis CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 85

Resolution
verified exact
local_arxiv, observed 2026-05-14T20:01:14.584005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-14T20:01:14.492788Z digest=sha256:65eb4c4c789712929f28b7478befafdc608a290704fd0cfd94ee8bbcc76b5e09

Observation eb08b747-4ec5-427b-9001-37b5110b464a · inbound

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

CodeXGLUE: A Machine Learning Benchmark Dataset for Code Understanding and Generation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 36

Resolution
verified exact
local_arxiv, observed 2026-05-15T11:40:02.722550Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T11:40:02.535705Z digest=sha256:97087472efa25e2e2c2a13c8a790e30073a55ba5f30b301fa19f01a06362b66b

Observation 131b4939-865f-4b3e-b81c-abcd038a9229 · inbound

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation cites this paper.

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-05-15T11:23:26.384563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-15T11:23:26.272169Z digest=sha256:45a17d3bd2e2a296d3ff646a32f13068fdb60411c8c33f08c3b7206a6db151bd

Observation 2637c429-bd7d-4a01-8ddb-638363030508 · inbound

Text and Code Embeddings by Contrastive Pre-Training cites this paper.

Text and Code Embeddings by Contrastive Pre-Training CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-05-15T19:24:11.981764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:24:11.907204Z digest=sha256:2d9508cb78f54593cd870655b3dd957564d714ee80d660d7342c63c95903064f

Observation a0ede364-ac41-4b9d-93df-6cd2ea8b0be6 · inbound

InCoder: A Generative Model for Code Infilling and Synthesis cites this paper.

InCoder: A Generative Model for Code Infilling and Synthesis CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 14

Resolution
verified exact
local_arxiv, observed 2026-05-16T02:21:20.497139Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-16T02:21:20.438666Z digest=sha256:b1c106f2cbe1740cd132f73bb66ff4e7b81377b61003efb40d263dd0b30d3b25

Observation 25d69608-e8ce-4f50-ae92-f44946c11281 · inbound

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

StarCoder: may the source be with you! CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-12T16:06:20.913961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-10T23:32:59.517389Z digest=sha256:26acafdabee6347b77e1df2903e60bff4248241cc01a9ceb3c8d76bb62305d1b

Observation 3943fe3f-eb97-4a1d-8ed4-692d9e19ab55 · inbound

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

CodeT5+: Open Code Large Language Models for Code Understanding and Generation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-19T05:26:57.528413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T05:26:57.440959Z digest=sha256:a797432c6a992c24fa83a9a4d123f0ea4de25121e7f3706b91378f348e33b22d

Observation ac6dbffd-648c-4afb-a9a5-9a6d4cf580d1 · inbound

Towards General Text Embeddings with Multi-stage Contrastive Learning cites this paper.

Towards General Text Embeddings with Multi-stage Contrastive Learning CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 82

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arxiv_id, observed 2026-05-12T16:06:20.913961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-12T03:33:45.855974Z digest=sha256:0fbe599eae25269185c1c4003f5c2dc29cacfb565a2f4f04dfcbbe15872a17af

Observation 568c3d9d-0d7c-494b-84d0-82374d453727 · inbound

Retrieval-Augmented Generation for Large Language Models: A Survey cites this paper.

Retrieval-Augmented Generation for Large Language Models: A Survey CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 157

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local_arxiv, observed 2026-05-24T05:13:56.551645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-24T05:10:25.171044Z digest=sha256:d221b201e51d99d707ad7eefcf205b2253cedffbc256b5d0a0ccc148980b8c8e

Observation 7d8692ff-dbf8-4aed-b119-14672f898dd3 · inbound

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution cites this paper.

CRUXEval: A Benchmark for Code Reasoning, Understanding and Execution CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 3

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metadata mismatch
local_arxiv, observed 2026-05-14T20:57:16.365502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-14T20:57:16.327963Z digest=sha256:c7a25c06af2c576f87462c7963594d219982f9825cc66a907931377dd737ed74

Observation b02eee10-6482-4944-a7db-f0d3f869285c · inbound

Nomic Embed: Training a Reproducible Long Context Text Embedder cites this paper.

Nomic Embed: Training a Reproducible Long Context Text Embedder CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 22

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verified exact
local_arxiv, observed 2026-05-21T14:56:19.216423Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-21T14:56:19.122278Z digest=sha256:f4ded029a93515977ebdeee91f9cbd46eb690b733a46c60cad9caf5a30877aac

Observation db175739-e5eb-4aca-aef0-bc37482b7ec2 · inbound

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

LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 22

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metadata mismatch
arxiv_id, observed 2026-05-12T16:06:20.913961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-10T17:34:42.565806Z digest=sha256:d265aabe9aaa6e402f135536da56118355b9630f9d3008fa0a1116d2ea886c12

Observation 2dbf89d1-136d-49cf-a889-6de70677e94b · inbound

A Survey on Large Language Models for Code Generation cites this paper.

A Survey on Large Language Models for Code Generation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 112

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verified exact
local_arxiv, observed 2026-05-13T20:18:06.590687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-13T20:18:06.304134Z digest=sha256:523a385687613c5906051d6cec571af74a8232fc5f998681fa448df4147e04e4

Observation 5b059cc8-2015-4bf7-bf03-4e16e3e44d48 · inbound

Are Decoder-Only Large Language Models the Silver Bullet for Code Search? cites this paper.

Are Decoder-Only Large Language Models the Silver Bullet for Code Search? CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 31

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verified exact
local_arxiv, observed 2026-05-23T18:43:19.196438Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-23T18:39:21.915976Z digest=sha256:9c0cbe525e6778720f4a871c7565d6ab7adfefac1d0d271fa27652dfe64054de

Observation 1fb5812b-a345-4dc9-bdf9-e01906c530cd · inbound

Large Language Models as Robust Data Generators in Software Analytics: Are We There Yet? cites this paper.

Large Language Models as Robust Data Generators in Software Analytics: Are We There Yet? CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 20

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no resolver link, observed 2026-08-12T19:37:58.378866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:37:58.378866Z digest=sha256:42f2a18281fda5973e4e0769cffe5a95d827761a00af38ecc320ff6e935ae3f9

Observation 38cd1af4-0d46-4eb3-955f-5f9a6b3f722c · inbound

CODECLEANER: Elevating Standards with A Robust Data Contamination Mitigation Toolkit cites this paper.

CODECLEANER: Elevating Standards with A Robust Data Contamination Mitigation Toolkit CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 74

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no resolver link, observed 2026-08-12T19:19:26.551871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T19:19:26.551871Z digest=sha256:3ec4161cac700afe99ced93411846b8f189fb2feaace40e3dc5341cbc2984975

Observation ac4430ba-cdbd-4e6e-8980-9e2769fb81b2 · inbound

CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval cites this paper.

CodeXEmbed: A Generalist Embedding Model Family for Multiligual and Multi-task Code Retrieval CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 13

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no resolver link, observed 2026-08-12T17:24:31.360631Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T17:24:31.360631Z digest=sha256:9de7db3b9ae64d274ae5b422fdbe2184a56f6c48d43c857da5f2eb6309e98ec7

Observation 1ba4343e-f7d6-4ef7-a847-1fdae5223305 · inbound

CodeSAM: Source Code Representation Learning by Infusing Self-Attention with Multi-Code-View Graphs cites this paper.

CodeSAM: Source Code Representation Learning by Infusing Self-Attention with Multi-Code-View Graphs CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 21

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no resolver link, observed 2026-08-12T15:10:33.077924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:10:33.077924Z digest=sha256:bd1d2277634a3f2716850666052ad0af14fc8c6e1cb4bd0af4d58b4a4eb0b3f5

Observation dd76dd02-9426-4b02-84a1-3f16e3c2a5bc · inbound

Isotropy Matters: Soft-ZCA Whitening of Embeddings for Semantic Code Search cites this paper.

Isotropy Matters: Soft-ZCA Whitening of Embeddings for Semantic Code Search CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 4

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no resolver link, observed 2026-08-12T12:03:02.767774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T12:03:02.767774Z digest=sha256:dbcdcb31362253b274f6460a499c2773fdeff390ef8e89bb095858d7a3354fc3

Observation 2300580e-4c56-46b8-856b-71617e7558d4 · inbound

FullStack Bench: Evaluating LLMs as Full Stack Coders cites this paper.

FullStack Bench: Evaluating LLMs as Full Stack Coders CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 33

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no resolver link, observed 2026-08-12T05:20:05.374768Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T05:20:05.374768Z digest=sha256:3d2a36ab33f2cdab9cbf1be35192b6ebf6a69bbb0fcdbdb010be36cfe459f2f2

Observation 63754435-80c6-4dfb-a5e8-2ddcde4108ed · inbound

CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking cites this paper.

CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 6

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no resolver link, observed 2026-08-12T04:49:20.642236Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:49:20.642236Z digest=sha256:a45866213c64a4264e44f04faf7c89d8ba3e1cb1606cd1b6899aed3f5eca20da

Observation f70aa45c-8f21-404e-8fd9-823244b061a4 · inbound

Evaluating and Aligning CodeLLMs on Human Preference cites this paper.

Evaluating and Aligning CodeLLMs on Human Preference CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 21

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no resolver link, observed 2026-08-11T20:53:15.240076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T20:53:15.240076Z digest=sha256:a191447af0614c23de50741fd0d4181c006940441a3470df3a28cd446ca4e122

Observation 84686803-55a8-4507-bdcf-4886fadb9d27 · inbound

MVD: A Multi-Lingual Software Vulnerability Detection Framework cites this paper.

MVD: A Multi-Lingual Software Vulnerability Detection Framework CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 34

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no resolver link, observed 2026-08-11T20:01:07.696836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:01:07.696836Z digest=sha256:8600576175b02fad6d105f80d06426d4d114f119b4d0a4cee690314b9076f686

Observation d855c302-64d9-4ef9-9edf-846367d2dbfe · inbound

Code LLMs: A Taxonomy-based Survey cites this paper.

Code LLMs: A Taxonomy-based Survey CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 34

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no resolver link, observed 2026-08-11T18:03:56.846027Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T18:03:56.846027Z digest=sha256:d219f0708f23b665199e87acf7ec440d34208e8d043438aa5e23e8df7ddadcea

Observation 55aca695-a089-4283-a9ad-cd515670426f · inbound

SECRET: Towards Scalable and Efficient Code Retrieval via Segmented Deep Hashing cites this paper.

SECRET: Towards Scalable and Efficient Code Retrieval via Segmented Deep Hashing CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 10

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no resolver link, observed 2026-08-11T14:46:16.440552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:46:16.440552Z digest=sha256:0597cdfcf51fa56360570cc08aedc084e5411e72ca1ef862b8356da207fbce96

Observation 8e92ca8e-73c7-479b-b797-440e81fd50a5 · inbound

Transducer Tuning: Efficient Model Adaptation for Software Tasks Using Code Property Graphs cites this paper.

Transducer Tuning: Efficient Model Adaptation for Software Tasks Using Code Property Graphs CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 18

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no resolver link, observed 2026-08-11T13:10:14.296969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T13:10:14.296969Z digest=sha256:40be834ad96fd23730019a274e13f468b63f5e8a02ad3158afec4e67cbd6ead7

Observation 329ac9b3-c258-43c1-a784-caa8be84840e · inbound

Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference cites this paper.

Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inference CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 147

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verified exact
local_arxiv, observed 2026-05-20T17:46:47.071451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-20T17:46:46.845424Z digest=sha256:e7f57d672daf11f9462e21e6ae7deab3f2223c54cf132c9c7b687624ab4cf8a9

Observation 5ed61953-af62-4782-a68e-76b59a19e4b4 · inbound

On the Compression of Language Models for Code: An Empirical Study on CodeBERT cites this paper.

On the Compression of Language Models for Code: An Empirical Study on CodeBERT CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 43

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no resolver link, observed 2026-08-11T12:53:58.465930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T12:53:58.465930Z digest=sha256:6744e33332e8ee2477a195c1e22093f33783a7b27d67dfc202cc41fbf52c94cf

Observation b9da37dc-5029-4396-8bd5-75f1b665c038 · inbound

Less is More: Towards Green Code Large Language Models via Unified Structural Pruning cites this paper.

Less is More: Towards Green Code Large Language Models via Unified Structural Pruning CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 25

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no resolver link, observed 2026-08-11T11:02:15.326800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T11:02:15.326800Z digest=sha256:a1ae58027243b0b9ce4dade21d0203ea192cd243bb9795853b28937ae1e7b6f4

Observation 8066b834-0615-45ac-b671-0dfa95a8bce0 · inbound

Analysis on LLMs Performance for Code Summarization cites this paper.

Analysis on LLMs Performance for Code Summarization CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 17

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no resolver link, observed 2026-08-11T05:50:08.004115Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T05:50:08.004115Z digest=sha256:8db53a183fca5beef464fa928a7559cad4d6badf4c374ffa5575fdad6a833655

Observation 391adf6e-fb81-479d-ae8d-55240e56ba7d · inbound

Jasper and Stella: distillation of SOTA embedding models cites this paper.

Jasper and Stella: distillation of SOTA embedding models CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 51

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no resolver link, observed 2026-08-11T01:03:28.263240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T01:03:28.263240Z digest=sha256:3b3fdd1f92f69aa481e7f516c038db009907c3578017035b6a81e87dfa6aa8be

Observation 07a9d5dc-c06f-4b2d-86cc-9eea165e48e4 · inbound

Fortran2CPP: Automating Fortran-to-C++ Translation using LLMs via Multi-Turn Dialogue and Dual-Agent Integration cites this paper.

Fortran2CPP: Automating Fortran-to-C++ Translation using LLMs via Multi-Turn Dialogue and Dual-Agent Integration CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 18

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unresolved
no resolver link, observed 2026-08-10T23:56:14.422567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T23:56:14.422567Z digest=sha256:9cf8bd5cf5ee3ea61d192164e815391f39489dc436bfcf115e006c5f25aec578

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

How to Select Pre-Trained Code Models for Reuse? A Learning Perspective cites this paper.

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

Reference 21

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T21:51:45.694835Z digest=sha256:5d188bb3860aed7a2b9cdabf95273afe24b214010251ed722b2a328fe97442c4

Observation c4ddbccf-89c9-4067-80c8-56cabe0b1d71 · inbound

Do LLMs Provide Links to Code Similar to what they Generate? A Study with Gemini and Bing CoPilot cites this paper.

Do LLMs Provide Links to Code Similar to what they Generate? A Study with Gemini and Bing CoPilot CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 27

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no resolver link, observed 2026-08-10T17:31:10.790873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T17:31:10.790873Z digest=sha256:a0ee23ff636ba1bb31f8459a12f2e05fa37e4d2de904a3e2e08873deab949b66

Observation a5253471-b7b8-4cfc-b4af-b49f392346b8 · inbound

An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities cites this paper.

An Empirical Study of Retrieval-Augmented Code Generation: Challenges and Opportunities CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 30

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no resolver link, observed 2026-08-10T15:43:03.145273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T15:43:03.145273Z digest=sha256:37a2b8556706abc4bec6d175d29b0a8ad265accfbe337af193da05bd37358c27

Observation f871214b-c528-4dfe-b059-b8b2affd699c · inbound

From Critique to Clarity: A Pathway to Faithful and Personalized Code Explanations with Large Language Models cites this paper.

From Critique to Clarity: A Pathway to Faithful and Personalized Code Explanations with Large Language Models CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 19

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no resolver link, observed 2026-08-11T20:21:28.895014Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:21:28.895014Z digest=sha256:131127e98b3c6b457818d61d2822b784c5d044b5a9b34c89614bf1b204aa1a9d

Observation 874131be-8b18-4953-9786-ef3147dfb170 · inbound

PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing cites this paper.

PATCH: Empowering Large Language Model with Programmer-Intent Guidance and Collaborative-Behavior Simulation for Automatic Bug Fixing CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 26

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unresolved
no resolver link, observed 2026-08-10T13:45:43.968465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T13:45:43.968465Z digest=sha256:3c09624a1671f88466a6ef3a9fb28bbb24223b52b207a7b12b00d4eefc9b330c

Observation 1dcbe305-c2c4-45e2-98f0-227d5f15336f · inbound

ToolFactory: Automating Tool Generation by Leveraging LLM to Understand REST API Documentations cites this paper.

ToolFactory: Automating Tool Generation by Leveraging LLM to Understand REST API Documentations CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 20

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no resolver link, observed 2026-08-10T05:34:42.350961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T05:34:42.350961Z digest=sha256:7b0251df4fb3ad46001c060ad6ce0632e3e27e0184bd66e0686497e9e95ce046

Observation ed6cd2db-b28a-467c-8e0d-bcbd375bafff · inbound

CoDocBench: A Dataset for Code-Documentation Alignment in Software Maintenance cites this paper.

CoDocBench: A Dataset for Code-Documentation Alignment in Software Maintenance CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 11

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unresolved
no resolver link, observed 2026-08-09T18:44:57.355785Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T18:44:57.355785Z digest=sha256:6f25162736e96657b87a723b16f9b5d21e113c12cada3f18f16acba7bd36c47e

Observation c892b406-42e5-427c-a679-ecf38765516f · inbound

Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign cites this paper.

Robust and Secure Code Watermarking for Large Language Models via ML/Crypto Codesign CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 9

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no resolver link, observed 2026-08-09T13:32:18.645244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:32:18.645244Z digest=sha256:5fc1f03397f09e294f8d0ba7cee2990b08334ae89462e9df3cb019b23624bc59

Observation c26123df-1a84-42d3-95db-02e822694b7b · inbound

AsserT5: Test Assertion Generation Using a Fine-Tuned Code Language Model cites this paper.

AsserT5: Test Assertion Generation Using a Fine-Tuned Code Language Model CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 2019

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no resolver link, observed 2026-08-09T11:26:46.002885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T11:26:46.002885Z digest=sha256:490eabffa0c6fa1db1e4f390319970d551f4bf7d12b03e08771bff61f74d56e7

Observation 87149c85-5917-4938-8692-7ca34d6f2f51 · inbound

Exploring the Security Threats of Knowledge Base Poisoning in Retrieval-Augmented Code Generation cites this paper.

Exploring the Security Threats of Knowledge Base Poisoning in Retrieval-Augmented Code Generation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 29

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no resolver link, observed 2026-08-09T05:31:14.314196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T05:31:14.314196Z digest=sha256:6e39bb183bf451d4b77621f9bcb0e4de1a9d6fd2a500317823d3fbe99ba46ebb

Observation cc199193-66b6-482e-be04-863e10348b9d · inbound

Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering cites this paper.

Can LLMs Replace Human Evaluators? An Empirical Study of LLM-as-a-Judge in Software Engineering CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 19

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no resolver link, observed 2026-08-08T16:31:38.563930Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:31:38.563930Z digest=sha256:53d61c1dcc82d7c5e3f1d0b5dc9de13d20befa75ff74936d26f14e41d48d001c

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

SnipGen: A Mining Repository Framework for Evaluating LLMs for Code cites this paper.

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

Reference 40

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

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source=pdf_text observed=2026-08-08T14:01:12.434210Z digest=sha256:7ec0fde05ac28dca126b44bd738580c25a45803e936e555ea733d7c650ce8ec2

Observation b366d66b-5dd5-4bbd-948c-f5e6e3dc1c6c · inbound

Repository-level Code Search with Neural Retrieval Methods cites this paper.

Repository-level Code Search with Neural Retrieval Methods CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 10

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no resolver link, observed 2026-08-08T13:58:16.389807Z

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source=arxiv_source observed=2026-08-08T13:58:16.389807Z digest=sha256:071d0cbe92a6c5df430a6832cf4cbf0d5dd8a600e60f5da8d1dd876d3e06ce3f

Observation bcaf0942-ce36-47db-8fac-509df62862e6 · inbound

URECA: The Chain of Two Minimum Set Cover Problems exists behind Adaptation to Shifts in Semantic Code Search cites this paper.

URECA: The Chain of Two Minimum Set Cover Problems exists behind Adaptation to Shifts in Semantic Code Search CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 19

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no resolver link, observed 2026-08-08T12:39:57.598956Z

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source=arxiv_source observed=2026-08-08T12:39:57.598956Z digest=sha256:f6982ab48a816dc04e63f7aab3f0b89fd673ae3ae1cb19974ce80bcb6056a274

Observation d1d8fd07-1f5f-44e7-9cc4-cc152547b7c0 · inbound

O1 Embedder: Let Retrievers Think Before Action cites this paper.

O1 Embedder: Let Retrievers Think Before Action CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 19

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no resolver link, observed 2026-08-08T12:25:12.213140Z

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source=pdf_text observed=2026-08-08T12:25:12.213140Z digest=sha256:e3967c63568b9b8a2f4910e85b650e137b52717fee1a1c586380e5ca58237a5f

Observation d0af0e2a-b1c1-4f19-a2b1-1ee1465c1539 · inbound

SoK: Where to Fuzz? Assessing Target Selection Methods in Directed Fuzzing cites this paper.

SoK: Where to Fuzz? Assessing Target Selection Methods in Directed Fuzzing CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 35

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no resolver link, observed 2026-08-08T05:33:13.641530Z

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source=pdf_text observed=2026-08-08T05:33:13.641530Z digest=sha256:4861b01e465eb864bfd94ae93c35849585c4a5d16c202da341f9686896b68c41

Observation c50de6ca-89ef-4ea9-ae5d-8c3094ee1c86 · inbound

XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants cites this paper.

XOXO: Stealthy Cross-Origin Context Poisoning Attacks against AI Coding Assistants CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 33

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verified exact
local_arxiv, observed 2026-05-22T23:57:17.130890Z

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No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-22T23:55:14.887237Z digest=sha256:d9745723602ba64d9b259b520b255f3a522837364926a8fe43931d9cc06feda0

Observation bcf96b3d-9cfe-40c7-894e-0f717e4ba87a · inbound

FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents cites this paper.

FreshStack: Building Realistic Benchmarks for Evaluating Retrieval on Technical Documents CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 2019

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source=pdf_text observed=2026-08-16T12:18:18.282105Z digest=sha256:717e9291b4ff3e5435c79865d89ffa05e15aff778c2dce61ab063f31b655883b

Observation 0786a368-1a34-4a48-8308-661c1ad82e6c · inbound

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models cites this paper.

PEFT A2Z: Parameter-Efficient Fine-Tuning Survey for Large Language and Vision Models CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 261

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source=pdf_text observed=2026-08-16T11:59:48.695312Z digest=sha256:8996c9590faf2fb1e1c12a3dbf97170ef31faaa8e687ab223d5ff72896e329db

Observation 02d2c2b0-525c-4149-b0cf-38bd749029c0 · inbound

Manipulating Multimodal Agents via Cross-Modal Prompt Injection cites this paper.

Manipulating Multimodal Agents via Cross-Modal Prompt Injection CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 84

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no resolver link, observed 2026-08-16T11:55:40.263866Z

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source=pdf_text observed=2026-08-16T11:55:40.263866Z digest=sha256:cadb715f3a20d59fcdf58ac202766d616b548da9661dd7f09327d0dcdf987a49

Observation df1f6389-ca26-42ab-8f44-c67ae4231edf · inbound

APIRAT: Integrating Multi-source API Knowledge for Enhanced Code Translation with LLMs cites this paper.

APIRAT: Integrating Multi-source API Knowledge for Enhanced Code Translation with LLMs CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 20

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no resolver link, observed 2026-08-16T11:42:52.304759Z

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source=pdf_text observed=2026-08-16T11:42:52.304759Z digest=sha256:69d45733e486156c71fc209af0415bfa5e6a703caefbb5a076749f84e495750c

Observation d60b6306-bc4a-4faf-808f-efa57de17709 · inbound

OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research cites this paper.

OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 27

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verified exact
arxiv_id, observed 2026-05-12T16:06:20.913961Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-22T19:20:54.644575Z digest=sha256:2a6481bfddeab87499ddfae1f8f1f952e803017eb79f70f384cd22768783a387

Observation f0dba07e-3e53-4194-a745-35ebacdab582 · inbound

Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection cites this paper.

Give LLMs a Security Course: Securing Retrieval-Augmented Code Generation via Knowledge Injection CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 16

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no resolver link, observed 2026-08-16T11:08:52.692568Z

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source=pdf_text observed=2026-08-16T11:08:52.692568Z digest=sha256:155eb5e4b97c4f953937b8ec637d384a82b50892ad14828aafc9f028b1103013

Observation 14f5b1cc-8b51-460e-92ec-eed59feb1340 · inbound

Towards Leveraging Large Language Model Summaries for Topic Modeling in Source Code cites this paper.

Towards Leveraging Large Language Model Summaries for Topic Modeling in Source Code CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 10

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no resolver link, observed 2026-08-16T10:43:53.454277Z

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source=pdf_text observed=2026-08-16T10:43:53.454277Z digest=sha256:428016ef5f882b05443c26f7bd94998d61cf18fe72b0c8204bfbaa5488e28b73

Observation 60c59456-382c-4e81-8a2b-454e9aa32f1d · inbound

NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation cites this paper.

NoEsis: Differentially Private Knowledge Transfer in Modular LLM Adaptation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 11

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no resolver link, observed 2026-08-16T10:29:42.041592Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T10:29:42.041592Z digest=sha256:fdad91742b2701336aeeb07cd29cbfe1b3a158b9f91fc29d105b6fe44dca2707

Observation b6259bdb-2115-4062-b06a-2fc6ca8e662e · inbound

Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks cites this paper.

Large Language Models are Qualified Benchmark Builders: Rebuilding Pre-Training Datasets for Advancing Code Intelligence Tasks CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 21

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no resolver link, observed 2026-08-16T05:58:12.844339Z

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source=pdf_text observed=2026-08-16T05:58:12.844339Z digest=sha256:88095571503516fb2e7921d4c2b00640d7ad919acb62edfd5c597ddb5a2bdb01

Observation 92f10961-c884-4716-83fa-574ae8acf9b0 · inbound

Do Automatic Comment Generation Techniques Fall Short? Exploring the Influence of Method Dependencies on Code Understanding cites this paper.

Do Automatic Comment Generation Techniques Fall Short? Exploring the Influence of Method Dependencies on Code Understanding CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 31

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no resolver link, observed 2026-08-16T05:56:23.569292Z

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source=pdf_text observed=2026-08-16T05:56:23.569292Z digest=sha256:50aee3473f5138be23f9688ce3788f261d4963b0f81fa712f2e6116e7df3f1c3

Observation fc532ecc-4d5c-45f8-9d6f-f56e8ab8c9a6 · inbound

Evaluate-and-Purify: Fortifying Code Language Models Against Adversarial Attacks Using LLM-as-a-Judge cites this paper.

Evaluate-and-Purify: Fortifying Code Language Models Against Adversarial Attacks Using LLM-as-a-Judge CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 46

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no resolver link, observed 2026-08-16T05:50:50.714395Z

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source=pdf_text observed=2026-08-16T05:50:50.714395Z digest=sha256:7425a46da68f678b05c1d75991ce7afeee6edf191bf687bd4ffdf51c22ededa2

Observation fb54b52a-a98f-443a-a167-05b192aff17a · inbound

A Systematic Literature Review of Parameter-Efficient Fine-Tuning for Large Code Models cites this paper.

A Systematic Literature Review of Parameter-Efficient Fine-Tuning for Large Code Models CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 52

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no resolver link, observed 2026-08-16T05:21:42.830889Z

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source=pdf_text observed=2026-08-16T05:21:42.830889Z digest=sha256:ce8868d5d571c01644a410d69eb9d68a66d2519c9401019e86c290365bd5ecfe

Observation f68bf273-44c1-4a31-a78a-ead406336720 · inbound

Enhancing Code Generation via Bidirectional Comment-Level Mutual Grounding cites this paper.

Enhancing Code Generation via Bidirectional Comment-Level Mutual Grounding CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 45

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no resolver link, observed 2026-08-15T22:13:36.586866Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T22:13:36.586866Z digest=sha256:e631588cb900fc1dd0d87e72b3066d5efd32a163482da816aecf7bdad251e7b2

Observation eed41e64-a4dc-4718-820d-54caf16d6cfb · inbound

StRuCom: A Novel Dataset of Structured Code Comments in Russian cites this paper.

StRuCom: A Novel Dataset of Structured Code Comments in Russian CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 6

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no resolver link, observed 2026-08-15T21:02:12.665278Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:02:12.665278Z digest=sha256:9c2abccc52486f81a01626da56b990c91de29ea150894840ff1d7d38bbfbf227

Observation 73a8df0a-5cf1-4c13-9953-c4e767422f6f · inbound

Towards A Generalist Code Embedding Model Based On Massive Data Synthesis cites this paper.

Towards A Generalist Code Embedding Model Based On Massive Data Synthesis CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 1

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no resolver link, observed 2026-08-15T20:34:54.202180Z

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source=pdf_text observed=2026-08-15T20:34:54.202180Z digest=sha256:64038129ed3a272f49814d0154c9f7c0a3f0b69881231cd900d5eada58374791

Observation 5c1460ed-6ce4-4380-a1a1-dfff35bcb320 · inbound

Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding cites this paper.

Sense and Sensitivity: Examining the Influence of Semantic Recall on Long Context Code Understanding CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 23

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no resolver link, observed 2026-08-15T20:20:16.434778Z

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source=arxiv_source observed=2026-08-15T20:20:16.434778Z digest=sha256:343107468132e04173cd4c98d550e435dc24d450b91fb92a2c62de559c0718bd

Observation 611668b2-2cec-4f05-b435-5b1e3d72fcea · inbound

Towards a Science of Causal Interpretability in Deep Learning for Software Engineering cites this paper.

Towards a Science of Causal Interpretability in Deep Learning for Software Engineering CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 116

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no resolver link, observed 2026-08-07T15:29:55.419047Z

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source=arxiv_source observed=2026-08-07T15:29:55.419047Z digest=sha256:e4e5dfdfa78b6a2c8d1a8f7d3e55dc19596f11bbead2a4fe961daf00a5d2cd32

Observation c11fe372-5d09-4561-ab36-f82ac7164a1f · inbound

An Efficient Private GPT Never Autoregressively Decodes cites this paper.

An Efficient Private GPT Never Autoregressively Decodes CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 23

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no resolver link, observed 2026-08-07T15:32:15.949174Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:32:15.949174Z digest=sha256:9b177a348a743e719c2221fb31f3a6c8aee739aeef68eea94db6249f4b126570

Observation d79d3976-efc8-4b30-837f-304985b0a209 · inbound

MIRB: Mathematical Information Retrieval Benchmark cites this paper.

MIRB: Mathematical Information Retrieval Benchmark CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 10

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no resolver link, observed 2026-08-07T15:19:54.356557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:19:54.356557Z digest=sha256:b763e3ef34f7e5987958c8f356a27f6fe0b5f41e98761da0d2d153d13382c08f

Observation 67d1dbf6-1f19-4cdd-8c86-1eae747eee0c · inbound

A Survey of LLM $\times$ DATA cites this paper.

A Survey of LLM $\times$ DATA CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 181

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no resolver link, observed 2026-08-07T14:33:13.192081Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T14:33:13.192081Z digest=sha256:c73bce1ee0f40200346376eb3a1696b7943aaa806a56fd8e911f7a1d7f07213e

Observation 6a377a99-4e54-4e68-841b-da142064a173 · inbound

CIDRe: A Reference-Free Multi-Aspect Criterion for Code Comment Quality Measurement cites this paper.

CIDRe: A Reference-Free Multi-Aspect Criterion for Code Comment Quality Measurement CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 9

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no resolver link, observed 2026-08-07T14:11:47.759804Z

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source=arxiv_source observed=2026-08-07T14:11:47.759804Z digest=sha256:da568128282aa3f9ca0518ab64776fe28790387764934ca33a47f057272404b1

Observation 058f41d1-e4e2-4a83-b3b0-f63badda4c3b · inbound

A Tool for Generating Exceptional Behavior Tests With Large Language Models cites this paper.

A Tool for Generating Exceptional Behavior Tests With Large Language Models CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 19

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no resolver link, observed 2026-08-07T13:04:27.440835Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:04:27.440835Z digest=sha256:becbc503025b850191bcac06a3a85016492c74f2df294d79dda1546431af276c

Observation f934d323-e63e-4150-8523-98ce954d9ee5 · inbound

MGS3: A Multi-Granularity Self-Supervised Code Search Framework cites this paper.

MGS3: A Multi-Granularity Self-Supervised Code Search Framework CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 18

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no resolver link, observed 2026-08-07T12:33:43.695337Z

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source=pdf_text observed=2026-08-07T12:33:43.695337Z digest=sha256:7aa04ee837cc60706e78c62fd94d81c79070fb3638b1028733091b0677a7fe93

Observation cc0ba0af-2606-4880-90e6-0d66ad91a272 · inbound

CoRet: Improved Retriever for Code Editing cites this paper.

CoRet: Improved Retriever for Code Editing CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 20

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no resolver link, observed 2026-08-07T12:35:31.713877Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:31.713877Z digest=sha256:21b4cd2d4e9022b059073b7a2b4db3edd95d38ddfd64a76e55b77fa3d7896cdb

Observation c12fddc4-2bc5-43e5-8bee-84548098ab65 · inbound

SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner cites this paper.

SWE-Flow: Synthesizing Software Engineering Data in a Test-Driven Manner CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 19

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no resolver link, observed 2026-08-07T05:01:08.548148Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T05:01:08.548148Z digest=sha256:6ae255e8221b94de78fc0c52e190ff005a49711fd37fff74322c0d5d948cc0bb

Observation ce7e5cf6-e3f7-499d-9077-57e661abdd0e · inbound

CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval cites this paper.

CoQuIR: A Comprehensive Benchmark for Code Quality-Aware Information Retrieval CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 6

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no resolver link, observed 2026-08-07T12:07:58.505494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:07:58.505494Z digest=sha256:f20a6ebeffad2ce20920de74be2becffbbb5563d4f43baeb2029ffe6e9b9aa41

Observation dafd21dc-f738-410e-97b4-5b77dfd5d23a · inbound

Retrieval-Augmented Code Review Comment Generation cites this paper.

Retrieval-Augmented Code Review Comment Generation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 33

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no resolver link, observed 2026-08-07T04:08:50.394269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:08:50.394269Z digest=sha256:eb5e1e7b90c4a76b9b5356bdf371fd78ac4772a11ed1eb387c387458e8ee0411

Observation 49fc3705-dcc3-453c-87fa-2a390c94392d · inbound

jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval cites this paper.

jina-embeddings-v4: Universal Embeddings for Multimodal Multilingual Retrieval CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 2014

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unresolved
no resolver link, observed 2026-08-15T18:45:06.016396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:45:06.016396Z digest=sha256:b454c76d3682d4914d26706e342291157a48272d0e3cca8f819a1c2a019edaec

Observation f143abdf-a967-4650-8d4c-19ca6c5b6128 · inbound

SACL: Understanding and Combating Textual Bias in Code Retrieval with Semantic-Augmented Reranking and Localization cites this paper.

SACL: Understanding and Combating Textual Bias in Code Retrieval with Semantic-Augmented Reranking and Localization CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 10

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unresolved
no resolver link, observed 2026-08-06T23:02:57.386422Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:02:57.386422Z digest=sha256:cbed1b1ec7d6e6c7347edeffd7c91fbd5589539b471d595324a97e894b0c4a91

Observation fa6140d2-40a0-4d56-8d62-912e8b48fcf2 · inbound

Towards Generalized and Stealthy Watermarking for Generative Code Models cites this paper.

Towards Generalized and Stealthy Watermarking for Generative Code Models CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 11

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no resolver link, observed 2026-08-06T22:45:36.181770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:45:36.181770Z digest=sha256:6cbe011c7fdae5d16284674c57960752b16f358c6027ec6c8bb09782e003fa04

Observation 4988dce1-0097-4c2b-b895-fb597322cf0c · inbound

RAILS: Retrieval-Augmented Intelligence for Learning Software Development cites this paper.

RAILS: Retrieval-Augmented Intelligence for Learning Software Development CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 13

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no resolver link, observed 2026-08-06T22:04:05.138133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:04:05.138133Z digest=sha256:8d848e437ab8f11b1a0d9d73ebe0d073b950169f5d917cb793a8832bdb1cc704

Observation cee5eb1a-b55b-4378-9698-a2880ae8456f · inbound

SWE-Bench-CL: Continual Learning for Coding Agents cites this paper.

SWE-Bench-CL: Continual Learning for Coding Agents CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 10

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no resolver link, observed 2026-08-07T04:07:56.382752Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:07:56.382752Z digest=sha256:10c0ceba3d0a844ae10c855663b33611c25781cee55a5f21713d381aee58cec9

Observation ef3d8242-3353-44f5-84f6-ecb54d547386 · inbound

Structural Code Search using Natural Language Queries cites this paper.

Structural Code Search using Natural Language Queries CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 9

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unresolved
no resolver link, observed 2026-08-06T20:42:34.184568Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:42:34.184568Z digest=sha256:8d25f7b2abadc6acfbf21c9849f379d3668b939b2a1f7b84da4a477fd0914535

Observation a885932a-c481-429c-a065-c8b4ff2331ac · inbound

A Comparative Study of Specialized LLMs as Dense Retrievers cites this paper.

A Comparative Study of Specialized LLMs as Dense Retrievers CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 16

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no resolver link, observed 2026-08-06T20:02:17.511259Z

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source=pdf_text observed=2026-08-06T20:02:17.511259Z digest=sha256:a87cc06810a2b205d5f0cb645a49c7f539090811bfa8401730f5251e77f51b9d

Observation 1ba7efa5-5fe7-4b44-81bc-f4ac3228ad93 · inbound

Seamlessly Integrating Tree-Based Positional Embeddings into Transformer Models for Source Code Representation cites this paper.

Seamlessly Integrating Tree-Based Positional Embeddings into Transformer Models for Source Code Representation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 11

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no resolver link, observed 2026-08-06T20:01:50.130759Z

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source=arxiv_source observed=2026-08-06T20:01:50.130759Z digest=sha256:5d1e3662050c564c4064a908b284627bbf5efc0ea2265e2b97c8928e195400d1

Observation c5b144ab-d113-4f5c-8af7-35cf9db15e74 · inbound

From Requirements to Code: Understanding Developer Practices in LLM-Assisted Software Engineering cites this paper.

From Requirements to Code: Understanding Developer Practices in LLM-Assisted Software Engineering CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 26

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no resolver link, observed 2026-08-06T18:42:19.747905Z

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source=pdf_text observed=2026-08-06T18:42:19.747905Z digest=sha256:762f250ec90dbd32c24ab3fba945978f49a490a912b5a8a94e8d77df550c2a35

Observation e246626b-9c9a-4bcf-991d-41a018edafa1 · inbound

Enhancing RLHF with Human Gaze Modeling cites this paper.

Enhancing RLHF with Human Gaze Modeling CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 24

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unresolved
no resolver link, observed 2026-08-06T18:11:17.047310Z

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source=arxiv_source observed=2026-08-06T18:11:17.047310Z digest=sha256:a390b6451996bc51688b0b3a137af5e9dadf66fce18be210967867515691fb6f

Observation 53e68fd3-e6f0-4d6e-9df2-f987ed40ae76 · inbound

MT4DP: Data Poisoning Attack Detection for DL-based Code Search Models via Metamorphic Testing cites this paper.

MT4DP: Data Poisoning Attack Detection for DL-based Code Search Models via Metamorphic Testing CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 23

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unresolved
no resolver link, observed 2026-08-06T17:25:37.249401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:25:37.249401Z digest=sha256:c859f10490fb3866bd5008dac6172421ee6de76b0d8966a31b9862b93dfec913

Observation 330f4929-eddc-4cf2-a488-3cb4fc69c008 · inbound

Fine-Tuning Code Language Models to Detect Cross-Language Bugs cites this paper.

Fine-Tuning Code Language Models to Detect Cross-Language Bugs CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 31

Resolution
verified exact
local_arxiv, observed 2026-05-19T02:42:56.393622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T02:42:12.245477Z digest=sha256:4713fc101855539b218e2baced25740129745d2773fed0a05efa7c948f802be8

Observation 1ebae983-08dd-431a-be8a-b27de22b6b95 · inbound

CodableLLM: Automating Decompiled and Source Code Mapping for LLM Dataset Generation cites this paper.

CodableLLM: Automating Decompiled and Source Code Mapping for LLM Dataset Generation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 6

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unresolved
no resolver link, observed 2026-08-06T20:45:43.630296Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:45:43.630296Z digest=sha256:85d6d2c02479bd46a0df170579c6cd0beb2f30f03a43fa43a6a70ee5db1634b6

Observation 9a20110b-ec7e-47e6-8196-5418bc134652 · inbound

How Quantization Impacts Privacy Risk on LLMs for Code? cites this paper.

How Quantization Impacts Privacy Risk on LLMs for Code? CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 23

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unresolved
no resolver link, observed 2026-08-06T10:26:17.926757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:26:17.926757Z digest=sha256:26fcee004428863d127d72ea51efbd48350e01f1dd9fd499d66151f2ef04ddb4

Observation cd2997ae-e995-4001-9542-bdebbcce5780 · inbound

Model Compression vs. Adversarial Robustness: An Empirical Study on Language Models for Code cites this paper.

Model Compression vs. Adversarial Robustness: An Empirical Study on Language Models for Code CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 43

Resolution
metadata mismatch
local_arxiv, observed 2026-05-19T00:01:55.823592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-19T00:01:42.228190Z digest=sha256:122a22aff1d4742bfaff4e272e91520b8293bdb536d15bbedb50231ad80dc518

Observation 907f0696-4e5d-4744-9f4d-3626ae5c7409 · inbound

LinkAnchor: An Autonomous LLM-Based Agent for Issue-to-Commit Link Recovery cites this paper.

LinkAnchor: An Autonomous LLM-Based Agent for Issue-to-Commit Link Recovery CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 57

Resolution
verified exact
local_arxiv, observed 2026-05-18T22:41:53.103247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-18T22:41:25.159850Z digest=sha256:971bf879193173c268d6192f7973ca60341de9af8cdd9af0d132c8840e7a22e2

Observation 0c1ccc95-dd68-46fa-b3b1-a255eaff3fe6 · inbound

LinkAnchor: An Autonomous LLM-Based Agent for Issue-to-Commit Link Recovery cites this paper.

LinkAnchor: An Autonomous LLM-Based Agent for Issue-to-Commit Link Recovery CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 57

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unresolved
no resolver link, observed 2026-08-05T19:40:21.585950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:40:21.585950Z digest=sha256:0621d026882791aaa1e4b5b3032d410f005d13d38f48bdb8222d1db54af8a399

Observation 634fdc06-d7f5-47fc-9a32-b602d598dd97 · inbound

Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning cites this paper.

Improving Code Understanding in Large Language Models through Concept-Aware Consistency Learning CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 25

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unresolved
no resolver link, observed 2026-08-15T17:22:46.300575Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T17:22:46.300575Z digest=sha256:a393a884efbf30efb76493dd99297cf8d880d8e5975a984099a5898563e89763

Observation efb61932-4c0f-46fb-b18e-0e239c824788 · inbound

SEAL: Structure and Element Aware Learning to Improve Long Structured Document Retrieval cites this paper.

SEAL: Structure and Element Aware Learning to Improve Long Structured Document Retrieval CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 14

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unresolved
no resolver link, observed 2026-08-05T14:54:06.719330Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T14:54:06.719330Z digest=sha256:b5c0e69a7b00007a86a3eba7ce4478734fa640aa22f7fb0befd604628ec4e27e

Observation 0295d9ae-0cfd-4dbd-a56b-b343c1b59938 · inbound

Efficient Code Embeddings from Code Generation Models cites this paper.

Efficient Code Embeddings from Code Generation Models CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 11

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no resolver link, observed 2026-08-05T14:28:58.666932Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T14:28:58.666932Z digest=sha256:df3b797938fb9449faeaef7621774dd916ebebaaca26a90487d86013d42934ef

Observation 5daf47cf-8bf7-4643-b075-770b689ebc52 · inbound

Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity cites this paper.

Human-Written vs. AI-Generated Code: A Large-Scale Study of Defects, Vulnerabilities, and Complexity CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 40

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no resolver link, observed 2026-08-05T14:09:57.785549Z

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source=pdf_text observed=2026-08-05T14:09:57.785549Z digest=sha256:01c4293ab49f48b9f45c409d7a34c88a31315f53320b1484a7551dfb2afba35b

Observation 702cb528-46b6-493f-9359-ecd3a3bb79fc · inbound

Beyond the Surface: A Solution-Aware Retrieval Model for Competition-level Code Generation cites this paper.

Beyond the Surface: A Solution-Aware Retrieval Model for Competition-level Code Generation CodeSearchNet Challenge: Evaluating the State of Semantic Code Search

Reference 4

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no resolver link, observed 2026-08-05T12:56:33.015798Z

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source=arxiv_source observed=2026-08-05T12:56:33.015798Z digest=sha256:579d8ea68d5505417d69e9fdf4b6894b27e0e1af0fb004d80a642e54f386c356