Paper Citation Record · LEDGER

How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2306.04751.

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

pith.paper-citation-record.v1
2306.04751 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 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 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:05:26.072736Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-18T06:38:37.167576Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

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 28828038-7abd-437c-90dd-d26c5eaf54c2 · inbound

Scaling Data-Constrained Language Models cites this paper.

Scaling Data-Constrained Language Models How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 123

Resolution: verified exact; arxiv_id, observed 2026-05-18T01:35:21.440167Z

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 91a72b80-c825-40b3-96f2-3af4b6dc3b3b · inbound

Large Language Models are not Fair Evaluators cites this paper.

Large Language Models are not Fair Evaluators How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 79

Resolution: verified exact; arxiv_id, observed 2026-05-17T12:10:42.412936Z

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 c4054626-5488-4272-9046-d0d7255c4bf2 · inbound

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena cites this paper.

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-10T18:52:59.124927Z

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 0fe4b084-b262-4c25-a394-02e20ccdea9c · inbound

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning cites this paper.

MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T23:46:39.512858Z

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 80c3f7a2-64b4-49b9-ac02-d647a8b88db8 · inbound

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection cites this paper.

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 141

Resolution: verified exact; arxiv_id, observed 2026-05-12T14:15:11.134533Z

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 72a95905-f221-497e-9e5c-f88af0db26c3 · inbound

Self-Rewarding Language Models cites this paper.

Self-Rewarding Language Models How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-13T12:01:42.385415Z

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 d898f310-0bcf-4557-831f-c2f49775447b · inbound

A Roadmap to Pluralistic Alignment cites this paper.

A Roadmap to Pluralistic Alignment How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 170

Resolution: verified exact; arxiv_id, observed 2026-05-16T14:37:53.560303Z

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 163e2d20-b45c-4457-abe8-dce966d99515 · inbound

Large Language Models: A Survey cites this paper.

Large Language Models: A Survey How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 70

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:22:55.050223Z

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 cf68a48c-92ff-4a5d-8228-7e14c9a1514f · inbound

ORPO: Monolithic Preference Optimization without Reference Model cites this paper.

ORPO: Monolithic Preference Optimization without Reference Model How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T09:34:04.711053Z

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 91513a9b-5923-4199-a15d-e09f58952e36 · inbound

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models cites this paper.

Inference Scaling Laws: An Empirical Analysis of Compute-Optimal Inference for Problem-Solving with Language Models How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 291

Resolution: verified exact; arxiv_id, observed 2026-05-18T06:38:37.170279Z

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 9b3e43d9-4873-4318-871d-78a4c845558a · inbound

Decomposing Elements of Problem Solving: What "Math" Does RL Teach? cites this paper.

Decomposing Elements of Problem Solving: What "Math" Does RL Teach? How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T13:05:26.072736Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66c8782a-b368-424d-8138-c3122c9b511d · inbound

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs cites this paper.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-06T12:47:44.789856Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a73cc95-c9ce-4d0c-a535-f8894b8213b0 · inbound

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M cites this paper.

Improving LLM Safety and Helpfulness using SFT and DPO: A Study on OPT-350M How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T19:48:22.658957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 780f6246-777e-46dc-bc03-d4afdfa69291 · inbound

PEFT-Factory: Unified Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models cites this paper.

PEFT-Factory: Unified Parameter-Efficient Fine-Tuning of Autoregressive Large Language Models How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 72

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T02:38:53.855497Z

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 ea83bfc2-937b-4abe-898d-68f7f85fbc0d · inbound

Let the Target Select for Itself: Data Selection via Target-Aligned Paths cites this paper.

Let the Target Select for Itself: Data Selection via Target-Aligned Paths How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-12T02:51:17.945367Z

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.