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Paper Citation Record · LEDGER

FullStack Bench: Evaluating LLMs as Full Stack Coders

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 23 inbound Pith citation observations for arXiv:2412.00535.

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

pith.paper-citation-record.v1
2412.00535 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 23 of 23 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T12:37:25.734725Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 36a40ee4-029d-4743-aa5e-5805644c6875 · inbound

Multi-Agent Collaboration for Multilingual Code Instruction Tuning cites this paper.

Multi-Agent Collaboration for Multilingual Code Instruction Tuning FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 15

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no resolver link, observed 2026-08-08T12:37:25.734725Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T12:37:25.734725Z digest=sha256:223bf57c3eddd39bf3042a571a7978d65f6b0a556f1bc9341dc6bcdc6ab52218

Observation 4e36ea01-a816-479b-8e55-e5e83f090ed0 · inbound

Seed-Coder: Let the Code Model Curate Data for Itself cites this paper.

Seed-Coder: Let the Code Model Curate Data for Itself FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 36

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no resolver link, observed 2026-08-07T11:04:56.816308Z

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source=arxiv_source observed=2026-08-07T11:04:56.816308Z digest=sha256:5b27cfd7ca24dd0168b094e75af9d14581712659106813292054467a55bd04aa

Observation 3685dfb9-cbbf-440f-81cb-00da98b0e11c · inbound

CodeContests+: High-Quality Test Case Generation for Competitive Programming cites this paper.

CodeContests+: High-Quality Test Case Generation for Competitive Programming FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 4

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no resolver link, observed 2026-08-07T10:16:52.892806Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-07T10:16:52.892806Z digest=sha256:f50a8795e6b81c3b36dbd802b131f6fe2d50b92f9e365e6616e7e9f1f83ca379

Observation 4e68e30d-277c-49e1-95bf-b374a7ea367d · inbound

AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length cites this paper.

AdaptiveLLM: A Framework for Selecting Optimal Cost-Efficient LLM for Code-Generation Based on CoT Length FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 33

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no resolver link, observed 2026-08-07T04:30:43.658947Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:30:43.658947Z digest=sha256:72a5d6958715707a5ac228bf989da4bd7c33facf8dd11062fe0e25527237456d

Observation bc990494-3d29-4615-ba53-57ab17dee1af · inbound

Turning the Tide: Repository-based Code Reflection cites this paper.

Turning the Tide: Repository-based Code Reflection FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 23

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no resolver link, observed 2026-08-06T17:51:13.610216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:51:13.610216Z digest=sha256:d8b19e3ae1cade42a03e95367b128b529252539ebd0c627201913ed7bce71c2d

Observation cc06240c-ddf5-42b5-bc80-efc8a971c01d · inbound

IFEvalCode: Controlled Code Generation cites this paper.

IFEvalCode: Controlled Code Generation FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 40

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no resolver link, observed 2026-08-06T11:44:34.021098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:44:34.021098Z digest=sha256:de21a8f416a87f9d93779efb8ab9b4f2e2ed04196b0d80fbaac8cd6a3610fcb0

Observation 06a31577-b3b6-41d8-a96b-58f6ee127d9c · inbound

WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent cites this paper.

WebWatcher: Breaking New Frontier of Vision-Language Deep Research Agent FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 8

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verified exact
arxiv_id, observed 2026-05-15T18:56:23.902839Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T18:56:23.817544Z digest=sha256:abd4d2c1e00dfe0639d0bea7a97590f204d53e3cc9c4cd735e4e3743324e351e

Observation 691aaab4-f958-4149-b143-d5c85afa298b · inbound

Vibration-Based Energy Metric for Restoring Needle Alignment in Autonomous Robotic Ultrasound cites this paper.

Vibration-Based Energy Metric for Restoring Needle Alignment in Autonomous Robotic Ultrasound FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 40

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no resolver link, observed 2026-08-05T22:28:15.505496Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:28:15.505496Z digest=sha256:4b928797465760d678680b09c8183dc0bb28a4ee0a0bb47856292b916aa2436e

Observation 84d01275-a476-432f-adc0-7b9059005a7f · inbound

Dream-Coder 7B: An Open Diffusion Language Model for Code cites this paper.

Dream-Coder 7B: An Open Diffusion Language Model for Code FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 36

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no resolver link, observed 2026-08-05T12:56:35.116898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T12:56:35.116898Z digest=sha256:e9a5505dbf6e42f7e8fa49804334e20860111cd984e2f1aa171b6ce84bed00f9

Observation 2078eff1-5f64-449f-ac54-1769f309f2dc · inbound

UniCode: Augmenting Evaluation for Code Reasoning cites this paper.

UniCode: Augmenting Evaluation for Code Reasoning FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 2025

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no resolver link, observed 2026-08-04T09:39:47.399871Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T09:39:47.399871Z digest=sha256:edf6ff29d5944b8a29aaae5732a4150b687b37b5817e6327067ca6bcfc5a81d0

Observation 6d7713cf-1c96-4680-9b4b-8991009a3ea7 · inbound

SCALER:Synthetic Scalable Adaptive Learning Environment for Reasoning cites this paper.

SCALER:Synthetic Scalable Adaptive Learning Environment for Reasoning FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 2

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arxiv_id, observed 2026-05-16T16:28:05.743083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-16T16:24:04.132572Z digest=sha256:e886ce4d082603571ed15a9d9191cb5d71b005cdcb23a1894d210c0c6ccd990c

Observation 3ea0ae09-9371-4ef4-aeb6-37c6c3c4553a · inbound

CharTool: Tool-Integrated Visual Reasoning for Chart Understanding cites this paper.

CharTool: Tool-Integrated Visual Reasoning for Chart Understanding FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 6

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arxiv_id, observed 2026-05-13T20:08:12.681617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T20:07:23.153064Z digest=sha256:45d5baa19d793270a358e6f3920e7ed2a79e36a01bcb11a4acd7825402ef024b

Observation 1d632ded-40aa-4766-a353-f0309625ad76 · inbound

InCoder-32B-Thinking: Industrial Code World Model for Thinking cites this paper.

InCoder-32B-Thinking: Industrial Code World Model for Thinking FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 26

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metadata mismatch
arxiv_id, observed 2026-05-13T18:58:08.705577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T18:56:31.975626Z digest=sha256:c41918372f52736cbc3c46b224569e07d339d18dc92c9ce51cffa7a6eff0acc8

Observation d20db14b-b003-45d1-a46d-1714cf89a392 · inbound

GeoBrowse: A Geolocation Benchmark for Agentic Tool Use with Expert-Annotated Reasoning Traces cites this paper.

GeoBrowse: A Geolocation Benchmark for Agentic Tool Use with Expert-Annotated Reasoning Traces FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 6

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metadata mismatch
arxiv_id, observed 2026-05-13T17:33:02.359854Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-13T17:31:08.575993Z digest=sha256:ebc2be3302212024b31ad47075b8fd020e5b0e30630ce2e562d50a7b9356a82d

Observation 6ea69460-01e2-4c41-a164-69ea5768da40 · inbound

SWE-WebDevBench: Evaluating Coding Agent Application Platforms as Virtual Software Agencies cites this paper.

SWE-WebDevBench: Evaluating Coding Agent Application Platforms as Virtual Software Agencies FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 12

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arxiv_id, observed 2026-05-11T18:16:08.964076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T16:24:49.710882Z digest=sha256:c8eb828b988ad578bb51c960525c2a6593081aadbdb6d396aafbda433cc28213

Observation 711bdc2f-7f5b-4f60-a1e0-2f4d27955f21 · inbound

Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization cites this paper.

Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 14

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arxiv_id, observed 2026-05-14T19:27:52.265134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T19:24:05.375951Z digest=sha256:26565d60d3b5c7a92e4342285ce191f60c3109dd526db5becafc0c3b9a5a77c5

Observation 45947a59-3b54-4b42-8481-4ef33ceb4fbe · inbound

Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization cites this paper.

Multi-Objective and Mixed-Reward Reinforcement Learning via Reward-Decorrelated Policy Optimization FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 15

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metadata mismatch
arxiv_id, observed 2026-05-14T19:27:51.248601Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-14T19:24:05.375951Z digest=sha256:37def4ac01ee9a3f36412c3f2e2d851d713fb12cf6c536079ebbad6075a73edb

Observation 2b27823f-fdf5-4492-9a77-6ad80320d633 · inbound

Efficient Agentic Reasoning Through Self-Regulated Simulative Planning cites this paper.

Efficient Agentic Reasoning Through Self-Regulated Simulative Planning FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 16

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arxiv_id, observed 2026-05-22T06:34:40.962219Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T06:33:36.846345Z digest=sha256:368aed257f60941ea919718faa08fb2ccfc1d37a804ac06fe4d056a2f99dbc53

Observation 76f0cbe1-a7f7-4592-a315-fb39d240f6d6 · inbound

Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning cites this paper.

Spreadsheet-RL: Advancing Large Language Model Agents on Realistic Spreadsheet Tasks via Reinforcement Learning FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 3

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arxiv_id, observed 2026-05-22T05:44:38.479911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-22T05:44:12.807291Z digest=sha256:953f9add92da0a6ddbb60b69c0ff1cbdb6e1db9d6fd1b39c1837b52af6ef6ee5

Observation 7bb56558-e906-442b-a332-b3fcc8b46601 · inbound

MONA: Muon Optimizer with Nesterov Acceleration for Scalable Language Model Training cites this paper.

MONA: Muon Optimizer with Nesterov Acceleration for Scalable Language Model Training FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 9

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arxiv_id, observed 2026-06-29T19:23:54.161758Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-29T19:15:49.229099Z digest=sha256:22fd7abbe79ad858fb6019aadb748ed474264ea98274ccc080e12278be0119d6

Observation ffa1d5e4-05c8-44ec-80ad-3116e8cad077 · inbound

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale cites this paper.

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 188

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arxiv_id, observed 2026-07-02T22:17:25.583378Z

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-07-02T22:10:59.568675Z digest=sha256:748c2bbef18914fb1e6d3a8a782ab1826e25df5a835150bedc42cc7fda657012

Observation 84725537-852c-47a6-b27d-5ac3754f5fe3 · inbound

Towards Reliable C-to-Rust Translation with Rule-Guided Reasoning and Reinforcement Learning cites this paper.

Towards Reliable C-to-Rust Translation with Rule-Guided Reasoning and Reinforcement Learning FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 6

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no resolver link, observed 2026-08-01T11:14:59.621613Z

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source=pdf_text observed=2026-08-01T11:14:59.621613Z digest=sha256:dc60f3a9aa63c955fc1520b963165db512fb254c90ce955024dcbdbab4874773

Observation 00da7b69-8be1-4464-ae4f-fdaf423434fb · inbound

SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD cites this paper.

SLAI T-Rex: Full-Parameter Post-training of the DeepSeek-V4 Family on Ascend SuperPOD FullStack Bench: Evaluating LLMs as Full Stack Coders

Reference 45

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no resolver link, observed 2026-08-01T10:42:39.936078Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T10:42:39.936078Z digest=sha256:a6d35cc15b2cfdd7c2f0620b6b984b01ca187b9a06909b906645a1fc9882f3a1