Paper Citation Record · LEDGER

Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:2212.09689.

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

pith.paper-citation-record.v1
2212.09689 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 22 of 22 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 22 of 22 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:08:00.924421Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-24T09:14:16.521020Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
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malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 9663fafa-0bbc-44dd-9420-1a0b4a6141d9 · inbound

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning cites this paper.

The Flan Collection: Designing Data and Methods for Effective Instruction Tuning Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-24T09:14:16.525698Z

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.

Observation 15dcb8aa-1553-418e-9cda-7683dea844ba · inbound

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society cites this paper.

CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Society Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-14T01:40:53.808661Z

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.

Observation 36a40ddb-1269-4125-b718-0c50358a40fa · inbound

Instruction Tuning with GPT-4 cites this paper.

Instruction Tuning with GPT-4 Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 6

Resolution: metadata mismatch; arxiv_id, observed 2026-05-14T17:04:18.083553Z

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.

Observation dd414a57-296b-4518-8ec2-9c2b8ebe3637 · inbound

Otter: A Multi-Modal Model with In-Context Instruction Tuning cites this paper.

Otter: A Multi-Modal Model with In-Context Instruction Tuning Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:43:47.889854Z

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.

Observation 536ea4d5-c3c8-4951-93e7-d9cc04b4c75a · inbound

InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning cites this paper.

InstructBLIP: Towards General-purpose Vision-Language Models with Instruction Tuning Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:13:52.169100Z

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.

Observation d1a41769-3f41-4d2b-be46-747cea9f1f6c · inbound

QLoRA: Efficient Finetuning of Quantized LLMs cites this paper.

QLoRA: Efficient Finetuning of Quantized LLMs Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:29:53.869545Z

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.

Observation 5ca99a5b-d660-4738-8bb3-724b19995ebc · inbound

The False Promise of Imitating Proprietary LLMs cites this paper.

The False Promise of Imitating Proprietary LLMs Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 257

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:54:31.484970Z

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.

Observation c10bb012-c057-4b71-9780-514004942810 · inbound

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning cites this paper.

LoRA-FA: Efficient and Effective Low Rank Representation Fine-tuning Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-24T08:06:03.876259Z

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.

Observation ede3e933-4319-41bc-b8bc-a8ffa09ad65c · inbound

MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning cites this paper.

MiniGPT-v2: large language model as a unified interface for vision-language multi-task learning Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-16T07:13:08.903070Z

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.

Observation 9c88df7b-8560-497e-a806-0816a2ed83c7 · inbound

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling cites this paper.

Expanding Performance Boundaries of Open-Source Multimodal Models with Model, Data, and Test-Time Scaling Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 90

Resolution: verified exact; arxiv_id, observed 2026-05-10T13:23:57.839380Z

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.

Observation ea7da8c3-7085-4eef-a330-5cbaefed4778 · inbound

LongMagpie: A Self-synthesis Method for Generating Large-scale Long-context Instructions cites this paper.

LongMagpie: A Self-synthesis Method for Generating Large-scale Long-context Instructions Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T15:08:00.924421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 893df899-ab89-4c4f-9307-5cdd9138c26e · inbound

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework cites this paper.

Being Strong Progressively! Enhancing Knowledge Distillation of Large Language Models through a Curriculum Learning Framework Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T10:20:01.434515Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b1c196e5-ffb4-4c39-8fa2-122ff23dcb09 · inbound

No Data? No Problem: Synthesizing Security Graphs for Better Intrusion Detection cites this paper.

No Data? No Problem: Synthesizing Security Graphs for Better Intrusion Detection Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-19T10:42:15.293864Z

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.

Observation 8109c4af-8725-418c-b469-1345041d3055 · inbound

MoKA: Mixture of Kronecker Adapters cites this paper.

MoKA: Mixture of Kronecker Adapters Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T04:28:33.897425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cf14c80b-0438-4910-943c-e9bc0da2558f · inbound

LLaSO: A Foundational Framework for Reproducible Research in Large Language and Speech Model cites this paper.

LLaSO: A Foundational Framework for Reproducible Research in Large Language and Speech Model Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-05T17:56:52.313230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 180efc72-158e-4b47-a399-35af33c265eb · inbound

QZhou-Embedding Technical Report cites this paper.

QZhou-Embedding Technical Report Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-05T14:11:09.753283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d210e0ed-a79e-44f8-85ee-b24cc4105f2a · inbound

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:16:11.412195Z

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.

Observation c29b40b3-ec16-4e84-9e35-70a25e33c5b2 · inbound

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:21:19.152459Z

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.

Observation 9f4fbb63-1159-4023-8e09-2971928cb6a4 · inbound

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key cites this paper.

Can RL Teach Long-Horizon Reasoning to LLMs? Expressiveness Is Key Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:39:10.619148Z

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.

Observation dc4001bb-32c3-4ec8-b202-c3f446df359d · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 106

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:36:20.002928Z

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.

Observation a6ce53f3-8866-4eda-ab19-ace602c75501 · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 106

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:32:30.224833Z

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.

Observation d1cf0a35-86ec-498f-a221-b377c0d135f3 · inbound

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices cites this paper.

DECO: Sparse Mixture-of-Experts with Dense-Comparable Performance on End-Side Devices Unnatural Instructions: Tuning Language Models with (Almost) No Human Labor

Reference 106

Resolution: verified exact; arxiv_id, observed 2026-05-21T07:59:50.224569Z

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.