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Paper Citation Record · LEDGER

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs

As of 7 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2507.21482.

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

pith.paper-citation-record.v1
2507.21482 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:47:45.362434Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

42 of 42 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved41
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4b2a1a1d-76d4-478b-957c-f0b28a76b0d1 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:42.797147Z digest=sha256:50c95ea9ba6a5a62a3586078f1859b0681381cef2a94b0fdc977e5e71a0c74c4

Observation 0941714d-f9d1-4c63-a82a-3a50a3c0f1df · outbound

This paper cites Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Deep Batch Active Learning by Diverse, Uncertain Gradient Lower Bounds

Reference 2

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-06T12:47:42.867009Z digest=sha256:845cd2e86ffd10d87c215fb148b9891d86b535b80ca21c625caf366ba3abcebc

Observation ae3c261c-8784-4f6e-99ba-7bda28ee84e1 · outbound

This paper cites An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs An Experimental Design Framework for Label-Efficient Supervised Finetuning of Large Language Models

Reference 3

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source=arxiv_source observed=2026-08-06T12:47:42.920123Z digest=sha256:ed489280aa1d7c56834d333319e864f611c2a03a1a7531c2d717c75da8a98e92

Observation 28346ea3-1fb3-4d53-9bcb-da400756e2dc · outbound

This paper cites Submodularity In Machine Learning and Artificial Intelligence.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Submodularity In Machine Learning and Artificial Intelligence

Reference 4

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source=arxiv_source observed=2026-08-06T12:47:43.011261Z digest=sha256:270b9951fb0feafad1e9344ca829ca859d882e5eeb742dba639b27bd8b4bc7b8

Observation 11e70aca-921c-4cd2-a5e6-a2252efd57f9 · outbound

This paper cites Data Diversity Matters for Robust Instruction Tuning.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Data Diversity Matters for Robust Instruction Tuning

Reference 5

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source=arxiv_source observed=2026-08-06T12:47:43.099798Z digest=sha256:3b2d1b102c9a7dbe9cbf0ff99e19b37eaec2444eb0aaefb38cd0e1c299ab75b7

Observation 78f9fddc-fb3a-4d01-9d84-eaf5b6dbb4c1 · outbound

This paper cites SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs SFT or RL? An Early Investigation into Training R1-Like Reasoning Large Vision-Language Models

Reference 6

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:43.134908Z digest=sha256:a83cba6898c9801e4dd5da331ae3ad1ad0e2a2c688ccf11e69a6f60dd38f06f2

Observation 3e635d56-97e3-42e6-abc7-9c6fdd5e79db · outbound

This paper cites AlpaGasus: Training A Better Alpaca with Fewer Data.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs AlpaGasus: Training A Better Alpaca with Fewer Data

Reference 7

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source=arxiv_source observed=2026-08-06T12:47:43.183614Z digest=sha256:96e78727c1f0c38eb2cb62b1bd8fdf6669e65835d6387efc524cc8ff5b2fab25

Observation 25261139-53da-4da3-ad3e-c4a15f48d298 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 8

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source=arxiv_source observed=2026-08-06T12:47:43.264059Z digest=sha256:058b58b72ae62ca0538ade00c198dce1790fbba78f3e1350c43634ae865361a8

Observation f09bde9f-80bb-42ff-b57a-a3e1065dc170 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.319543Z digest=sha256:e3e56d9055ebd202125b9f4545d5838611c8cf4df3df71df6f1b90a674bb9792

Observation a95737c2-ff48-4f42-ae82-28597335bc0e · outbound

This paper cites MoDS: Model-oriented Data Selection for Instruction Tuning.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs MoDS: Model-oriented Data Selection for Instruction Tuning

Reference 10

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source=arxiv_source observed=2026-08-06T12:47:43.389554Z digest=sha256:d6753ac81783923ed8e866f844aa74fc8955e61e0f1a4dc89565d8cd2639b796

Observation 3286c5e4-d871-49a2-a27c-220b03eac2bf · outbound

This paper cites Measuring Massive Multitask Language Understanding.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Measuring Massive Multitask Language Understanding

Reference 11

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source=arxiv_source observed=2026-08-06T12:47:43.449347Z digest=sha256:f1edeffb4e791115aa6543e5eba5b70745694e2accffae3bb6306b175b95c619

Observation b0c3a23e-8111-4f67-b32c-0d0d3323458d · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs LoRA: Low-Rank Adaptation of Large Language Models

Reference 12

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source=arxiv_source observed=2026-08-06T12:47:43.509926Z digest=sha256:6b945d60851cce9074749e098d66a25dc86314b05f1206aaf74e6ddc1631b466

Observation 5b4c75f5-68b9-4e18-9cc6-09033fc2cf0e · outbound

This paper cites Data-Efficient Finetuning Using Cross-Task Nearest Neighbors.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Data-Efficient Finetuning Using Cross-Task Nearest Neighbors

Reference 13

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:43.563797Z digest=sha256:b24e2753add43346972ab0f8af28c3b3d0e335816b1194f74793fe7ad23aecdb

Observation 3432d42b-454b-4adf-821a-f540b277661f · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.641186Z digest=sha256:f1cefe93c0930b6ad73c001f3d27493b3ade98101fe187cf9dd839d1e00ccae6

Observation 74f7130e-bac3-4a35-bb01-352ee49485f1 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.702379Z digest=sha256:9e8343fdd145cbf0dccd99fb76f5ae7bc94e32e4a6535ad44ba36b2eaefb1daa

Observation fe18394b-9268-4818-ab66-ef9fdf02e84d · outbound

This paper cites Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive Tasks.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Active Instruction Tuning: Improving Cross-Task Generalization by Training on Prompt Sensitive Tasks

Reference 16

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source=arxiv_source observed=2026-08-06T12:47:43.767768Z digest=sha256:e8dfe52f3a009434246a073afecc3f5da53e7f76cf11701d07a7767a43d9b881

Observation dde39cc2-beaa-4503-bc15-b1bc812a6c2e · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.812010Z digest=sha256:e99391d1fdaec67e288ca8a9eef7d41b69c927c87693ff2fd250410e9954c1e4

Observation 51a182ee-c167-4452-a97a-0ca4fa5ec4d9 · outbound

This paper cites Hashimoto.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Hashimoto

Reference 18

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source=arxiv_source observed=2026-08-06T12:47:43.864631Z digest=sha256:72eb63a41ea7ce8850a11919fb11760d4c9bd3819735041f4d8ece04c938248c

Observation 52929f99-87c0-4b09-a09f-3cbf48b5b619 · outbound

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

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs The Flan Collection: Designing Data and Methods for Effective Instruction Tuning

Reference 19

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source=arxiv_source observed=2026-08-06T12:47:43.919893Z digest=sha256:25837efbc5bbc7312165a97815bf18ca52098de12a4c1136f9c6df3a622c2bdb

Observation c875356a-639d-4f15-a67a-3c552dd640c3 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 20

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.953774Z digest=sha256:21a44e5a64416dd170550011b88c83aebed8e08415851134aebd0b2779ec8c56

Observation ab86cd08-f74c-4661-b2d7-7e21c501260e · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 21

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source=arxiv_source observed=2026-08-06T12:47:44.040700Z digest=sha256:aa745ef5a31a4fb3619c26af0c9424887510a7ab87d74907598510d4a970185a

Observation 94bc2933-ad03-45a2-8b74-d9ce1cddd4e4 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 22

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.078622Z digest=sha256:c6fe359c0bc89ae75f0538540613f5c80938f2b7d1babacdcd568efee7b53fe0

Observation ce417b8c-23ee-4b1f-8f5c-16da0c1d9a54 · outbound

This paper cites Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation

Reference 23

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source=arxiv_source observed=2026-08-06T12:47:44.173569Z digest=sha256:91974a7c2339e187b9e85dfba467020fa8219dff7113fafa221d43574c2219fe

Observation e133c5a4-11c3-4ada-8489-393489e952a5 · outbound

This paper cites Training language models to follow instructions with human feedback.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Training language models to follow instructions with human feedback

Reference 24

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source=arxiv_source observed=2026-08-06T12:47:44.271410Z digest=sha256:a32f2303cb7e351af47252699577926dce5e9e6b6598f3410fbe9ac854d7165a

Observation dad7c16c-6a39-4ac4-98de-16b4ad4dece7 · outbound

This paper cites Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unleashing the Power of Data Tsunami: A Comprehensive Survey on Data Assessment and Selection for Instruction Tuning of Language Models

Reference 25

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local_arxiv, observed 2026-08-06T12:47:45.791893Z

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.314157Z digest=sha256:9bc4a76acee43b137390668270c119f6493ff94a34280d575e32a1e64f752b50

Observation 148b4cdb-4a21-4bd2-98ad-24983ed79999 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 26

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No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.378217Z digest=sha256:a71d56368cc1e204e7105dfc588a878dcfbc390a2ed9c8b37eb9f20ad0ff759c

Observation 9b3e7c13-d878-416f-94a2-d64f40f1d424 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 27

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source=arxiv_source observed=2026-08-06T12:47:44.435370Z digest=sha256:e13c6f3165f0ffc885eb6d839de0c062a69d8a22a31f885b81d16a91df88ee01

Observation 34f75120-def0-434a-a097-2eb4d04dbaa2 · outbound

This paper cites Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Challenging BIG-Bench Tasks and Whether Chain-of-Thought Can Solve Them

Reference 28

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source=arxiv_source observed=2026-08-06T12:47:44.505705Z digest=sha256:7820b6bc05ebd6ae51e11ebd4d1821706f1b9f0c6fe80b1343c3bba9af235a32

Observation 0ac1991c-9ae9-486d-bad1-083c0a7e4b7f · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 29

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.559784Z digest=sha256:1a6db519dd36a72900809bee64c8ab23926bd56b602d9fe3f68468cb57bb32ab

Observation b4bc5d30-9b11-443e-ab3f-43e8c8154ceb · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 30

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source=arxiv_source observed=2026-08-06T12:47:44.630235Z digest=sha256:a0ac2c4dc3e84045e55240b853a7ec3c8935de29a92793d87ced36f77d47b82b

Observation 59b259ca-70f9-421e-ad49-60436b481861 · outbound

This paper cites Diversity Measurement and Subset Selection for Instruction Tuning Datasets.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Diversity Measurement and Subset Selection for Instruction Tuning Datasets

Reference 31

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source=arxiv_source observed=2026-08-06T12:47:44.723595Z digest=sha256:2dfbde9e8c6f94a2c9fb50159a419eb345f9a101bc1fa2c116b00f51c3fbc909

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

This paper cites How Far Can Camels Go? Exploring the State of Instruction Tuning on Open Resources.

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

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source=arxiv_source observed=2026-08-06T12:47:44.789856Z digest=sha256:2fbb8205c74c17b1e3b0f2c6f64c136c4a770a939be48cabc76bd382d713534f

Observation 1c878692-dbf2-4c51-81cd-4a1fb86153b9 · outbound

This paper cites Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks

Reference 33

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source=arxiv_source observed=2026-08-06T12:47:44.822605Z digest=sha256:332a23f40bc8f839df2e9a574363c57e45727814883a0b57b2fee2317b8a5c7c

Observation a3e73837-19b3-41a9-9a80-66e9871bef75 · outbound

This paper cites Finetuned Language Models Are Zero-Shot Learners.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Finetuned Language Models Are Zero-Shot Learners

Reference 34

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source=arxiv_source observed=2026-08-06T12:47:44.889686Z digest=sha256:0a97c8593943a9eea16376d80910d07ebe3f70d6d60e715bb898ab5fe84759d8

Observation da6a676c-1184-4484-947d-4c181e37d3d7 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.957942Z digest=sha256:e115ea71b225171170b01f1d938825e1c43c8be68e0e670e9074ed152da7dc71

Observation ba32fb04-4765-4419-b6c9-a9b52f55f416 · outbound

This paper cites Deep Active Learning in the Open World.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Deep Active Learning in the Open World

Reference 36

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source=arxiv_source observed=2026-08-06T12:47:45.020258Z digest=sha256:52a978431599507cafbddc3908694fbcf4462badcd4f21483f3885dcb9252ddf

Observation a10a354c-b8fd-4304-a321-6453702480d2 · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 37

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raw_fallback, observed 2026-08-06T12:47:46.228375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:45.080141Z digest=sha256:b8325ef5bbde19d92dc04edce285f225900b83f7210bc1f2554fc9c209bf7dac

Observation 40dc412e-3522-4334-a858-9f18bd9bc086 · outbound

This paper cites LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs LabelBench: A Comprehensive Framework for Benchmarking Adaptive Label-Efficient Learning

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T12:47:45.142282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:45.142282Z digest=sha256:5b50ea259156cddc4c9caad99e35f93341e86c79f69ac8b8e502857d722f517e

Observation a9502e75-5976-465e-9614-f63eea5b720e · outbound

This paper cites an unresolved cited work.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-06T12:47:46.203195Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-06T12:47:45.202485Z digest=sha256:4fc11d05c4efad9760e9cbe8fb6617000ba45644fc06e50fb9af2b4e2bfb2be8

Observation 76385086-f3ca-4677-8e77-289622e31e7f · outbound

This paper cites Bridging the Creativity Understanding Gap: Small-Scale Human Alignment Enables Expert-Level Humor Ranking in LLMs.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs Bridging the Creativity Understanding Gap: Small-Scale Human Alignment Enables Expert-Level Humor Ranking in LLMs

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-06T12:47:45.238625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:45.238625Z digest=sha256:c472de3763ad5a4864abac32822c0f7780e28e1ecc80e328bad2fd272b8202cb

Observation bbe76f94-f3b4-4540-8a37-3249c9e526b8 · outbound

This paper cites online" 'onlinestring :=.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs online" 'onlinestring :=

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T12:47:45.300103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:45.300103Z digest=sha256:421adff621cb344c8b595c01f9182f8dd8ea98e43b2d762a312455c45f3ada3d

Observation d3ecbf69-a2b8-4936-baab-a310dd366442 · outbound

This paper cites write newline.

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs write newline

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-06T12:47:45.362434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:45.362434Z digest=sha256:50c237a40591eeeedca86faced37ed0f0f53f013b0d750b3c8925b0bc896bcd0

Pith citing papers

No inbound Pith citation observations are available.