Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-03T22:23:31.201476Z
Paper Citation Record · LEDGER
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go
As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2511.10868.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
19 of 19 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved19
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 5b55f708-be09-44bb-9fec-07dcedf6e818 · outbound
This paper cites Mike Conover, Matt Hayes, Ankit Mathur, Jianwei Xie, Jun Wan, Sam Shah, Ali Ghodsi, Patrick Wendell, Matei Zaharia, and Reynold Xin.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Mike Conover, Matt Hayes, Ankit Mathur, Jianwei Xie, Jun Wan, Sam Shah, Ali Ghodsi, Patrick Wendell, Matei Zaharia, and Reynold Xin
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:29.198026Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0e1c081b-adf2-43e3-a8c4-0b3369fa0203 · outbound
This paper cites UltraFeedback: Boosting Language Models with Scaled AI Feedback.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go UltraFeedback: Boosting Language Models with Scaled AI Feedback
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:29.369869Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea6f2d8d-1743-45a0-94fc-302a58b7536e · outbound
This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Tulu 3: Pushing Frontiers in Open Language Model Post-Training
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:29.854689Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b2adf9b-2f62-49bf-9a7f-1ba414dd2e9e · outbound
This paper cites StarCoder: may the source be with you!.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go StarCoder: may the source be with you!
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:29.950798Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 908bab4d-3866-4610-8abb-ab33627ac629 · outbound
This paper cites The Flan Collection: Designing Data and Methods for Effective Instruction Tuning.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go The Flan Collection: Designing Data and Methods for Effective Instruction Tuning
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:30.099098Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation db5029aa-2415-47c3-957e-0d31e9c4b1fa · outbound
This paper cites StarCoder 2 and The Stack v2: The Next Generation.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go StarCoder 2 and The Stack v2: The Next Generation
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:30.172268Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c421f034-5fff-4282-a53f-1bd484c5630b · outbound
This paper cites CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go CodeGen: An Open Large Language Model for Code with Multi-Turn Program Synthesis
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:30.281906Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cf715578-8170-4fdd-8691-a01ea4334dda · outbound
This paper cites Spaceo.ai.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Spaceo.ai
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:30.416924Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a2595743-3fe7-4385-be8c-a48cc651f67f · outbound
This paper cites Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Rohan Taori, Ishaan Gulrajani, Tianyi Zhang, Yann Dubois, Xuechen Li, Carlos Guestrin, Percy Liang, and Tatsunori B
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:30.591761Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation efc6b96e-f9fc-44f1-8981-3a9c2a2394cf · outbound
This paper cites CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go CodeBenchGen: Creating Scalable Execution-based Code Generation Benchmarks
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:30.701196Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 64f1acf8-9509-461a-b27c-854699c08ace · outbound
This paper cites Instruction tuning for large language models: A survey.arXiv preprint arXiv:2308.10792,.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Instruction tuning for large language models: A survey.arXiv preprint arXiv:2308.10792,
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:30.834017Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1469f486-4021-4d8b-be53-a1ccd05ff185 · outbound
This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:30.982151Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc68c378-91d1-479d-9eea-b038cf308f2b · outbound
This paper cites linear" seed 42 logging_steps 100 save_steps 1000 save_strategy.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go linear" seed 42 logging_steps 100 save_steps 1000 save_strategy
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:31.135033Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9775ff5-3da7-4d85-9e66-f7764f7b42ab · outbound
This paper cites none" task_type.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go none" task_type
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:31.201476Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad6ae605-1634-45e9-87c4-053de515dde6 · outbound
This paper cites LoRA: Low-Rank Adaptation of Large Language Models.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go LoRA: Low-Rank Adaptation of Large Language Models
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:29.749107Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ef988659-74f5-4910-be78-244b43053340 · outbound
This paper cites Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Fine-Tuning or Fine-Failing? Debunking Performance Myths in Large Language Models
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:28.850280Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 627b8dbe-ed76-4ef9-ae44-c5e4352f74e2 · outbound
This paper cites Evaluating Large Language Models Trained on Code.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Evaluating Large Language Models Trained on Code
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:29.096871Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7144c996-c0d2-4c2e-99b2-26b1f8ddd319 · outbound
This paper cites Measuring the impact of early-2025 ai on experienced open-source developer productivity.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go Measuring the impact of early-2025 ai on experienced open-source developer productivity
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:28.972075Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6508bb85-1cd9-4206-8b67-05ba870c10c6 · outbound
This paper cites MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data.
Go-UT-Bench: A Fine-Tuning Dataset for LLM-Based Unit Test Generation in Go MedAlpaca -- An Open-Source Collection of Medical Conversational AI Models and Training Data
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T22:23:29.667827Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.