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Paper Citation Record · LEDGER

Improving Task Diversity in Label Efficient Supervised Finetuning of LLMs

As of 17 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 2026-08-17T06:30:58.91139+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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:42.797147Z digest=sha256:a938aa0c6582c21cfc5275e3308e94b779c985b208d81ee0a6fe9b164dd91f8e

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

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:42.867009Z digest=sha256:746dcd8f60109c4fc63bc6727f432ae0d5dc8657d12e004b6978d2a00638a29d

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=sha256:6fd663a79878c8e7f5c1fb5621411b434a3dddd2249a32305759528da1f80275

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:d3e6b425fce4c44216cbd37de1cfbc574864e6ff27359a842d9cd704437c50e8

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:b246855331895dff390db54bf890ff783bc467bf98718115ccf08d1ff4e554ca

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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source=arxiv_source observed=2026-08-06T12:47:43.134908Z digest=sha256:0d0a17b360d887f48ba88c88f139282b7ba0c52cb20773c59ebbdf142cc5805e

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=sha256:6550a2c007cada1cc0b2cead2a36da352cca24007ae1c379404a94b767d5664d

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=sha256:5a2e2e39811ab7313b8acb6f6fcf14efae8140f8ffa37d9654a70e728dde5101

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.319543Z digest=sha256:b0c096b25e71222700e66575aecc4e97fc391e60c559e5b6c665ea4eee9a60d8

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=sha256:17658328c697148909b9fc7e792bf72c1dd25af6950b6a8ace8125c65b1ab698

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=sha256:066bdb83b637aaebef6632372f28805f558bd6e4300fe9e3b797b34a0d4a1160

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=sha256:88c734a6fd9ff40bca09d48e810ebc4d643437ac9b0402625abdcf5bc3d33d96

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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source=arxiv_source observed=2026-08-06T12:47:43.563797Z digest=sha256:a75cc0e874e5d96e574174e4269275fb1794aa6fac04cf9f068ff4d47245930e

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.641186Z digest=sha256:a6c9655acc2c4379a6b50916a379f5a203b0c9223a005dc8060e3b5afef3052a

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.702379Z digest=sha256:f55865f7aef43fe4269105447b293efd91ff4018d39571fc6a3e553e16b3e842

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=sha256:45420e2dc740db61db8758b0a8fa3b5b0435c3a0c4a5a547ef3520aedfad4870

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.812010Z digest=sha256:107bffaf4b376ab9c311d6a60a5df2dde9da1942330a2b0dcee177b016e824b4

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=sha256:2909e43968bbd957354b13f2b176115c624f7de97a2085fe87ce71c0ef62c3a1

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=sha256:528a1141f519fd4eb4dd5c3d6397af1664a1f4de6b616414e3e91a64f22365c4

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:43.953774Z digest=sha256:cbca7f2339c0f169e831f626838946bd8c1181b9e320734259973a1ef7958a24

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:ca2c7cdc118b74b992f9824c57cb2273efcab756c714133be31f20a19f075627

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.078622Z digest=sha256:bd08ad21521f2f90c7e195ce09e24b2abe21066177e12e5bdc188b51004afe27

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=sha256:05982ad601167e208d964d999a322d9abcbabba40a38057a0a87ebea053993ba

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=sha256:616f8581cfe712e7fab27667815361e770224220099a750a88f548ce41cea7eb

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

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.314157Z digest=sha256:20827bbfa84b7475bfa2c531882d4666a527ddf83e84662a4beb0c96eea00a3a

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.378217Z digest=sha256:256b8f0e82f7041d33e202df6dab11993dbde0e72c97464a74ab005c4bef688b

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=sha256:103e313a8e5b65076930728c55759bf6101ef784ad68ba5265cff235e786f641

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=sha256:3c2ec8c531eb42ca8915b7bf3b41574994dd52b2a5edb903d355e04f9f1d7aad

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.559784Z digest=sha256:c09da46c3ee717186b7fe88d58ea5bd49f94cad4011052139fd0f74a11aa16bb

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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no resolver link, observed 2026-08-06T12:47:44.630235Z

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source=arxiv_source observed=2026-08-06T12:47:44.630235Z digest=sha256:9989ae3cf3fe0a7e77a47c1f8e03ca3deeb86b9120c3dfa12b63a8e1e471bbba

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=sha256:444ad69cc37918f6bb1e56726d23f3e73f5023dd63bc1c17e4e52f7740fd5f4c

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:bb2ea6968e5732b9535e9d8c8686c67144cfe3f1c8c090c44dfde6ca91639a12

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:aae2c6fcfcc168c792c49b18cd5f6b91b89e9dcc7e601e5d04a321b1ae69cbb9

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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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T12:47:44.889686Z digest=sha256:45cdd67e55ffdbd16c43f69a888ad6ede49ed697e807a131cad59f0ebce04b41

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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raw_fallback, observed 2026-08-06T12:47:46.249149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:44.957942Z digest=sha256:200e4d15b04fd939d8ed9262ab86e4633f0280ae2a219487209d28f04d998d07

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:df4824e3fca75db456f2312f11f068034d586d18eabb53169d9cf122786d5a9d

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:45.080141Z digest=sha256:2ed732c44fada4b5e7c0588a8c5ceeb86dadcd4882afaea35dcdea2b0efa562d

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=sha256:0bf9abecb860616fe4e081300669781220a95a593e5ac24a2f1919c230c0e932

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 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-06T12:47:45.202485Z digest=sha256:986b6efb1e63edd9777cbf54a47082135e07f252143f1ad293335aab6be8522e

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=sha256:933300370f810460fa82c3143580cd6aa961a8be3b27814248cae3f57a416729

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=sha256:42aa30518677eaf3ef8baf14a55bc45ea7a60c974162ecbb42bf10baa33d7e1a

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=sha256:50a4624fe0add0247d3e2a4e3896a99d0b32749839f5910e3e4d553a45489b34

Pith citing papers

No inbound Pith citation observations are available.