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Paper Citation Record · LEDGER

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs

As of 10 August 2026, this Paper Citation Record lists 91 of 91 outbound references and 0 inbound Pith citation observations for arXiv:2608.03573.

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

pith.paper-citation-record.v1
2608.03573 v2

Coverage vector

measured 91 of 91 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T00:51:25.097330Z

measured 91 of 91 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 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

91 of 91 outbound references displayed

  • verified exact0
  • verified fuzzy18
  • unresolved72
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 68c54f4a-d5d9-41dc-9fc1-ea37fa6c5f7f · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 1

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unresolved
no resolver link, observed 2026-08-08T00:51:24.838386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.838386Z digest=sha256:1f5d4a461dff18ac48c86ef2f8159bc0a21e269e3b16b6aadcff584735863a00

Observation e540975b-3755-44ed-adb4-eee6f0b51777 · outbound

This paper cites 2025 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , eprint=

Reference 2

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unresolved
no resolver link, observed 2026-08-08T00:51:24.842437Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.842437Z digest=sha256:c3bca06d2cec9afc2ca3369928baed46d4515d14310a49eb2e46f3d1c9f43b4e

Observation 9172b590-a96a-47f1-b0b3-e0985bd86175 · outbound

This paper cites Notion Blog , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Notion Blog , year=

Reference 3

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unresolved
no resolver link, observed 2026-08-08T00:51:24.845618Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.845618Z digest=sha256:149b05ba16142cb4467b2e661f540ef739e54c9dc60bc0a90e3a45c083a1adaa

Observation 009d592c-9a2c-474c-8709-cd8e53b922cf · outbound

This paper cites Notion Blog , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Notion Blog , year=

Reference 4

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unresolved
no resolver link, observed 2026-08-08T00:51:24.848882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.848882Z digest=sha256:2d96a83861505cead538dfce141feb3b9ccb60e6101e333fd1890cfc0da3f7c3

Observation 68f17af8-7ccf-4e48-938b-cbb778f2c6c8 · outbound

This paper cites Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning

Reference 5

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unresolved
no resolver link, observed 2026-08-08T00:51:24.851939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.851939Z digest=sha256:e6cd276cb451ca5525843bd213ed027ec17cb9009e9ff7a8caf904f7eb21bc06

Observation 7da74fc9-5c31-4edd-9266-4f6cc37f89a6 · outbound

This paper cites GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs GLM-4.5: Agentic, Reasoning, and Coding (ARC) Foundation Models

Reference 6

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unresolved
no resolver link, observed 2026-08-08T00:51:24.855511Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.855511Z digest=sha256:c0d4954496e5dff8d7586085944df12aa14f1b7506761cc51dc0772f4afde4e6

Observation 9d050213-bfa5-414b-887d-78aa2ef677e4 · outbound

This paper cites 2025 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , eprint=

Reference 7

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unresolved
no resolver link, observed 2026-08-08T00:51:24.859031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.859031Z digest=sha256:6d6e4ba3a9d4695385c0a346f96be1b08c1853635984d519aa040aeed9d8e08d

Observation 270372db-3e7e-49ea-83bc-6355322e8c5a · outbound

This paper cites SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs SFT Memorizes, RL Generalizes: A Comparative Study of Foundation Model Post-training

Reference 8

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unresolved
no resolver link, observed 2026-08-08T00:51:24.862030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.862030Z digest=sha256:5abf269f0b66bc8877aa58ed6480af584e53b4013cec1d75c096cf55674b8adc

Observation bb7986a9-0f38-4aed-8526-47d14e2458cb · outbound

This paper cites RL Squeezes, SFT Expands: A Comparative Study of Reasoning LLMs.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs RL Squeezes, SFT Expands: A Comparative Study of Reasoning LLMs

Reference 9

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unresolved
no resolver link, observed 2026-08-08T00:51:24.865455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.865455Z digest=sha256:8d97db16067f54f1397b0badb1b81392766527507d3fc092fecde3d8f1e409a1

Observation 475e09fa-8e71-49f3-842f-6c38be11a240 · outbound

This paper cites How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs How Abilities in Large Language Models are Affected by Supervised Fine-tuning Data Composition

Reference 10

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no resolver link, observed 2026-08-08T00:51:24.868703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.868703Z digest=sha256:552a17cc630dc2680a2b273d9b91be1fc30c8e18f7e14d937a3f86005d2808dd

Observation a3b5cc92-d26b-49ef-b432-57eb6e5f6e2f · outbound

This paper cites 2025 , school=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , school=

Reference 11

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unresolved
no resolver link, observed 2026-08-08T00:51:24.871996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.871996Z digest=sha256:23cb2645604c5df1cd1b908b55d6ccc8e488730e3eefa449d6eb0750abd17a4c

Observation 96fabbca-42e0-4c5a-9bf6-ebb1ae74bcb1 · outbound

This paper cites Journal of Machine Learning Research , volume=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Journal of Machine Learning Research , volume=

Reference 12

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no resolver link, observed 2026-08-08T00:51:24.874964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.874964Z digest=sha256:55614fa5d8aa0dd80d591e582778eaa624482f821be7f39f7af103991f786936

Observation b0a38f5c-106b-452c-8fb9-329dc3164034 · outbound

This paper cites Forty-first International Conference on Machine Learning , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Forty-first International Conference on Machine Learning , year=

Reference 13

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unresolved
no resolver link, observed 2026-08-08T00:51:24.877955Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.877955Z digest=sha256:dea9f8f3aa08f40729e8192cd452c26000453deeef54c2d5c53d50ada35cdca2

Observation 711a6dea-54c6-46d2-8ce5-15955619d8de · outbound

This paper cites 2024 , journal =.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2024 , journal =

Reference 14

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unresolved
no resolver link, observed 2026-08-08T00:51:24.880970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.880970Z digest=sha256:583dcc4c2e85ce1524a687b1af6fcf79fcbfc8a83999ad4a77ef132b5dd86a1a

Observation b468e741-8353-48b7-be51-fbe16876cb46 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 15

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no resolver link, observed 2026-08-08T00:51:24.883937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.883937Z digest=sha256:ce03c5d48a2e2878a3a2dd9529b58806658e5ae413bd08709a57774146535481

Observation f7ac2037-c10d-42e2-a7b3-704cf0f240a7 · outbound

This paper cites arXiv preprint arXiv:2505.11711 , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv preprint arXiv:2505.11711 , year=

Reference 16

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no resolver link, observed 2026-08-08T00:51:24.887173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.887173Z digest=sha256:00afd663e9c6de54f93dcccbba5bfa53503a43cc67e1ab00f7de7cfb32ae2cd9

Observation f534c9f5-c07d-4188-a3af-c49375af7665 · outbound

This paper cites OpenAI o1 System Card.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs OpenAI o1 System Card

Reference 17

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no resolver link, observed 2026-08-08T00:51:24.889992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.889992Z digest=sha256:efe5dd57c5dff7a8d9927891f7cd1fbc73cb9bf4b0fa66dd7b6db454c25ba58b

Observation 45ef809b-2384-4458-82f2-a4e384dee59d · outbound

This paper cites arXiv preprint arXiv:2510.00553 , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv preprint arXiv:2510.00553 , year=

Reference 18

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unresolved
no resolver link, observed 2026-08-08T00:51:24.893127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.893127Z digest=sha256:49abd48a99124d0630308c693f430eee83f08699814406ec0be9a85076520d1c

Observation 234113de-6718-4f5b-9b69-bb659ea26ca7 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Advances in Neural Information Processing Systems , volume=

Reference 19

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unresolved
no resolver link, observed 2026-08-08T00:51:24.896219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.896219Z digest=sha256:93b720242f2bf2b4c3ea9c846703b8a99253b8948f174e78f55d400c6914e93c

Observation 11c81482-b16b-42cc-b5cf-e67d9efc2be1 · outbound

This paper cites RL's Razor: Why Online Reinforcement Learning Forgets Less.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs RL's Razor: Why Online Reinforcement Learning Forgets Less

Reference 20

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no resolver link, observed 2026-08-08T00:51:24.899233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.899233Z digest=sha256:a131073a88d604f49d85a46dddc21615be144daeb9d388f61253bf2ea156984f

Observation 71923b72-fb19-4cd1-aa22-2eb690f3c77a · outbound

This paper cites 2025 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , eprint=

Reference 21

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unresolved
no resolver link, observed 2026-08-08T00:51:24.902409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.902409Z digest=sha256:f4d99ff9870bc763608a3b5457fb89d707a5a8cda7761385aa3084ae70ea120d

Observation f2c23186-5130-4f8c-af90-2984a31afaf1 · outbound

This paper cites 2013 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2013 , eprint=

Reference 22

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no resolver link, observed 2026-08-08T00:51:24.905310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.905310Z digest=sha256:d9a2c3fcba9bcccbbbf20bb9cc90b49357177da06b8ff339bd0b6d781e04d6d8

Observation 71140767-a30f-4303-83f9-ea0281e40b19 · outbound

This paper cites 2025 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , eprint=

Reference 23

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verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.960024Z

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.

source=arxiv_source observed=2026-08-08T00:51:24.908993Z digest=sha256:ba149688a34091d71017615edc3fae0156fe5c2d3500029283384b6fac2ad138

Observation e8335b22-ae85-4996-9a33-057bfcda0d32 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Advances in Neural Information Processing Systems , volume=

Reference 24

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no resolver link, observed 2026-08-08T00:51:24.911800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.911800Z digest=sha256:7d66d4f0875a45bdbe23ada81cb249c38b7120e5110a48cf13bb3a0be6ce1d96

Observation 19efbbe8-f5ee-48fc-945b-4efdc4e3cc93 · outbound

This paper cites Finding Skill Neurons in Pre-trained Transformer-based Language Models.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Finding Skill Neurons in Pre-trained Transformer-based Language Models

Reference 25

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no resolver link, observed 2026-08-08T00:51:24.914427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.914427Z digest=sha256:d8eda76eab469180c8db7ea5cfd1ada4d8b919e98721164093eaf7dc54da650d

Observation feda317e-f4f1-4c84-b724-c765eae22b4d · outbound

This paper cites RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs RedStar: Does Scaling Long-CoT Data Unlock Better Slow-Reasoning Systems?

Reference 26

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no resolver link, observed 2026-08-08T00:51:24.917563Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.917563Z digest=sha256:d11acf91054efa89e43f381139bdab78807b9d660f242b697f58cfcf3a9ae8a3

Observation 70b8ca03-76d2-45bd-b9b4-a146edd8dffa · outbound

This paper cites an unresolved cited work.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Unresolved cited work

Reference 27

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unresolved
no resolver link, observed 2026-08-08T00:51:24.920696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.920696Z digest=sha256:688363cb1799ed9b63f5c0369cd07ea92a17c59b9c5056ccb1f8e0eb6b9eaa0f

Observation 1b4f520d-f52f-43b1-bb3c-9ce02f0269af · outbound

This paper cites Group Sequence Policy Optimization.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Group Sequence Policy Optimization

Reference 28

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no resolver link, observed 2026-08-08T00:51:24.923464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.923464Z digest=sha256:6fc596a51a1787a2c06341bc242e7ca5ca104ba7171082aefa0e13c13ec225d6

Observation 16f87fda-c97a-430d-b473-60434b3e0f85 · outbound

This paper cites Advances in neural information processing systems , volume=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Advances in neural information processing systems , volume=

Reference 29

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unresolved
no resolver link, observed 2026-08-08T00:51:24.926486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.926486Z digest=sha256:cc9fb8ee37e390f9c6349ec54474c22e66f1387d0794423f2108a4ad5a2e2b9a

Observation b7ae546c-595f-4e1e-a732-6e2679834658 · outbound

This paper cites RL Is Neither a Panacea Nor a Mirage: Understanding Supervised vs. Reinforcement Learning Fine-Tuning for LLMs.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs RL Is Neither a Panacea Nor a Mirage: Understanding Supervised vs. Reinforcement Learning Fine-Tuning for LLMs

Reference 30

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unresolved
no resolver link, observed 2026-08-08T00:51:24.929359Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.929359Z digest=sha256:f740bf4ed052d35851a940e064a4342759c0c7fd12245bbef7b4ff15f7a8a0b9

Observation 6ee3b23d-47c9-4d05-9d9a-702c441e85fe · outbound

This paper cites an unresolved cited work.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Unresolved cited work

Reference 31

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unresolved
raw_fallback, observed 2026-08-08T00:51:25.941163Z

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.

source=arxiv_source observed=2026-08-08T00:51:24.932337Z digest=sha256:860608cda34d1c14c4d4ab3c1d61d589fb333d82c8d30f5fac267e4a9e1486b6

Observation da7ea94d-8785-4431-b5ad-f5af98effe21 · outbound

This paper cites arXiv preprint arXiv:2508.11408 , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv preprint arXiv:2508.11408 , year=

Reference 32

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unresolved
no resolver link, observed 2026-08-08T00:51:24.934982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.934982Z digest=sha256:0211c435868a772e5e01403e0a03d38694f0f0b69ee80e4e051012fa213dcf97

Observation 66463944-db0e-4f81-8a74-1a8135b269ac · outbound

This paper cites SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs SRFT: A Single-Stage Method with Supervised and Reinforcement Fine-Tuning for Reasoning

Reference 33

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unresolved
no resolver link, observed 2026-08-08T00:51:24.937566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.937566Z digest=sha256:ff957443a0e07941a167f72a2d8e40736ec2b004d29adfb523c78c6ab021ab80

Observation 764de3c9-cf85-4936-97b8-d44c84de81e5 · outbound

This paper cites arXiv preprint arXiv:2507.14783 , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv preprint arXiv:2507.14783 , year=

Reference 34

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no resolver link, observed 2026-08-08T00:51:24.940643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.940643Z digest=sha256:05e304e2965643179e24358df2b1721400bbfba6adb66c6374dfc6622341ccd3

Observation 5880889f-ada6-4589-9536-bf1cd6f24903 · outbound

This paper cites an unresolved cited work.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Unresolved cited work

Reference 35

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unresolved
raw_fallback, observed 2026-08-08T00:51:25.933261Z

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.

source=arxiv_source observed=2026-08-08T00:51:24.943161Z digest=sha256:214d2a6670801c31c0f008d5d6765837ddda788c34c69bf4af97094dec7f704e

Observation f249f6e5-1491-4e43-a410-13aca663e1a2 · outbound

This paper cites Establishing Trustworthy LLM Evaluation via Shortcut Neuron Analysis.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Establishing Trustworthy LLM Evaluation via Shortcut Neuron Analysis

Reference 36

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metadata mismatch
local_arxiv, observed 2026-08-08T00:51:25.419952Z

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.

source=arxiv_source observed=2026-08-08T00:51:24.945853Z digest=sha256:68d7eedca82b4a9fcd611710204412b84099640b339f8c676f67cb37d8c5eab8

Observation 4d23f51b-9412-441b-8f52-eee04f5eb2d9 · outbound

This paper cites 2024 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2024 , eprint=

Reference 37

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unresolved
no resolver link, observed 2026-08-08T00:51:24.948610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.948610Z digest=sha256:41d96e6755efe715ef5c2e82cb54a9566c4a4032c356c6d331c03b126b20bf14

Observation 745e9d7f-2acd-4bb7-806e-e4293d9babc8 · outbound

This paper cites arXiv e-prints , pages=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv e-prints , pages=

Reference 38

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no resolver link, observed 2026-08-08T00:51:24.951367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.951367Z digest=sha256:8d0f7cfafacee49058db2937da278d03647b3f8906b0d1cd59140b2a53fbcbaf

Observation 24e4dbc1-7e97-4fd0-bd8f-3b58a041cdb2 · outbound

This paper cites Advances in neural information processing systems , volume=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Advances in neural information processing systems , volume=

Reference 39

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unresolved
no resolver link, observed 2026-08-08T00:51:24.954073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.954073Z digest=sha256:3a0d9b0cd1a0445fddf1ea35e63b1ec6af32119abceaf3bb588a45e29570cc44

Observation e190c4f2-4725-41c1-a6ff-9c092fa92250 · outbound

This paper cites When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs

Reference 40

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unresolved
no resolver link, observed 2026-08-08T00:51:24.956984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.956984Z digest=sha256:9c1c55bd3b904d8f3d61404ccce509349d59fe75d3d1cc6d9f195a56699e623a

Observation 7f05ed9c-ec62-4b30-9b7f-37ca7a45157a · outbound

This paper cites International Conference on Machine Learning , pages=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs International Conference on Machine Learning , pages=

Reference 41

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unresolved
no resolver link, observed 2026-08-08T00:51:24.959992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.959992Z digest=sha256:0bb4c80159dc991d1bec92704f0a09c2335500be126d442b7901eea4a88f7f7a

Observation a093eb83-067c-4172-a1a6-286c9091e8d5 · outbound

This paper cites Fine-Tuning Language Models from Human Preferences.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Fine-Tuning Language Models from Human Preferences

Reference 42

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unresolved
no resolver link, observed 2026-08-08T00:51:24.962646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.962646Z digest=sha256:28fdfb6e77df3eb593f0b16ea10c05df64463a60e795679c536a357389903630

Observation ea9057cc-3348-44d9-ba0d-a8fb64914c59 · outbound

This paper cites arXiv preprint arXiv:2510.23451 , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv preprint arXiv:2510.23451 , year=

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:24.965740Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.965740Z digest=sha256:3d735f657b7a7dd06c05add9faa3f28fa3a68ab4ea898edcf5bd7474d91c174b

Observation 7f808ad9-c7ac-4b19-b4f4-ff9731543c33 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:24.968486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.968486Z digest=sha256:409378b49b0128aecbb3771fd1a6f781ac4a4f0cef7ddcd0573986a8e7f0ae13

Observation 13da6049-b004-45c3-8c9a-93018bb1f1c4 · outbound

This paper cites Kimi K2: Open Agentic Intelligence.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Kimi K2: Open Agentic Intelligence

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:24.971347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.971347Z digest=sha256:bc5d3c81ec22dde2123c3794776ab1e8f5a7ced135eb919cf861e85e93184bb5

Observation 274a4626-4b3f-42e1-81e8-c4211dc99651 · outbound

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

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Finetuned Language Models Are Zero-Shot Learners

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:24.974293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.974293Z digest=sha256:3c21d4095edab73b01bb70e43d80365efeb5295cb5ce0720c1cdc6208fe9abe6

Observation 64744e12-324e-44ba-9f40-65a2bb6ec4be · outbound

This paper cites Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Does Math Reasoning Improve General LLM Capabilities? Understanding Transferability of LLM Reasoning

Reference 47

Resolution
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no resolver link, observed 2026-08-08T00:51:24.977379Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.977379Z digest=sha256:6c34e9ef72f551425c51a2ab2632df092b44f88c9a010acf97a4c2fae7f992a9

Observation cfa8e593-2751-444f-86c4-dd747e1b95de · outbound

This paper cites 2025 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , eprint=

Reference 48

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unresolved
no resolver link, observed 2026-08-08T00:51:24.980199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.980199Z digest=sha256:9e5aebbe79a84a31911eb818857346b0a971e72a2f42fba409975f44881a123a

Observation 9c809825-2207-4248-b986-1e64ec13d22c · outbound

This paper cites arXiv preprint arXiv:2510.19178 , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv preprint arXiv:2510.19178 , year=

Reference 49

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unresolved
no resolver link, observed 2026-08-08T00:51:24.983165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.983165Z digest=sha256:332e42cc9b115d6face78dddd6abe89030257225eb1d4528792f58ace4afadd5

Observation a2022819-1246-49c2-a20d-d370e0f34043 · outbound

This paper cites DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

Reference 50

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unresolved
no resolver link, observed 2026-08-08T00:51:24.985898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.985898Z digest=sha256:a786d8bba2a907eb611a807afe9b95d9392e5ab280fc13dd3a280840a086916d

Observation 71867253-54ed-464c-97bb-90248c9e3e5a · outbound

This paper cites RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments

Reference 51

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unresolved
no resolver link, observed 2026-08-08T00:51:24.989053Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.989053Z digest=sha256:66df38b52b3dc6b88796aac0eb5eb974ec8a6f5f1498c830b4bc9fc4fcd09cac

Observation a246913d-eed8-4d9d-95b8-df2f8c98ef22 · outbound

This paper cites 2025 , url =.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , url =

Reference 52

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no resolver link, observed 2026-08-08T00:51:24.991738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.991738Z digest=sha256:f9452bb944782c151a9aef5fb24afdeb106953eadf4b48e8263ede313a2e9bb9

Observation 6296a290-b359-4605-b99c-cf693850f86e · outbound

This paper cites 2025 , url =.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , url =

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.903509Z

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.

source=arxiv_source observed=2026-08-08T00:51:24.994352Z digest=sha256:49ff572ca48219a65bc573179bc15cff168bb12527a59c5b621ab6f21ab005ff

Observation 6420f249-30c8-4e0e-ac34-9ca34ea51e94 · outbound

This paper cites Qwen3 Technical Report.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Qwen3 Technical Report

Reference 54

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unresolved
no resolver link, observed 2026-08-08T00:51:24.997044Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.997044Z digest=sha256:cfbea9edd66473b700887791b62a5259c10a214cd7d6efda788a26c39259a47b

Observation 76f66b0a-8911-4d14-9334-55a992341558 · outbound

This paper cites DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs DeepDistill: Enhancing LLM Reasoning Capabilities via Large-Scale Difficulty-Graded Data Training

Reference 55

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no resolver link, observed 2026-08-08T00:51:24.999803Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:24.999803Z digest=sha256:a63b05e5ba17ffc76e0c36601a84097328093d5e0b3af107405214e060a7f75c

Observation df3ba475-cc66-4b8a-9ffb-891e6bf26385 · outbound

This paper cites 2024 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2024 , eprint=

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.002728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.002728Z digest=sha256:a97ebad00746d6113cc1fdc1ca6057644c0212e6815c75aed36b3c9eb1fba8b5

Observation 8c329527-5d4b-4c46-a22d-af845ac75ecb · outbound

This paper cites 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) , pages=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE) , pages=

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.892013Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.005420Z digest=sha256:d1d7765763f2a71bf29eebe6d8847bed5456833a184f0c704da86cf43a872abd

Observation 9361a7d4-2b63-4187-9363-1051be6d3c82 · outbound

This paper cites Let's Verify Step by Step.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Let's Verify Step by Step

Reference 58

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unresolved
no resolver link, observed 2026-08-08T00:51:25.008147Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.008147Z digest=sha256:3c46f87b12cef834c103c8da75e5799385a89b08a4721ad6eeae7ca748e43344

Observation 9a48c120-3fd5-4099-a059-871c5e3a22a5 · outbound

This paper cites 2021 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2021 , eprint=

Reference 59

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unresolved
no resolver link, observed 2026-08-08T00:51:25.011091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.011091Z digest=sha256:326a43443b315616a8464465c51f3ae5f28c763e35d7d9023dcee089776ab8cf

Observation efdddd95-982f-4daf-9c61-14879811b92e · outbound

This paper cites 2023 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2023 , eprint=

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.014006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.014006Z digest=sha256:72bfa4eaadad8642340534d7ef49e4121b5872bc119ebd48820433d688fee12a

Observation daab03e9-76d4-4b8a-a62f-0f4be1d86bee · outbound

This paper cites 2024 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2024 , eprint=

Reference 61

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unresolved
no resolver link, observed 2026-08-08T00:51:25.017043Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.017043Z digest=sha256:4ef93e214b717377d078c8ea22d4e4ac46d62cded1d07622564622991c6d2185

Observation 5b6c23ea-e248-4b6e-bd5c-d74225384034 · outbound

This paper cites 2021 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2021 , eprint=

Reference 62

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unresolved
no resolver link, observed 2026-08-08T00:51:25.019902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.019902Z digest=sha256:2822278b4e81740b8a1633e964b8500d36eb8ad5e20344c99e8cade6afd5e092

Observation d1c45c70-a3fa-41a4-b4bc-aa80d8848f8f · outbound

This paper cites 2023 , version =.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2023 , version =

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.869420Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.022641Z digest=sha256:455c3a07fdb87040451d32709c2e322004ac87dcff0baaa5e7bea9794cf4a8f6

Observation f778c1ea-d242-4c17-a6bb-f44267396d80 · outbound

This paper cites Proximal Policy Optimization Algorithms.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Proximal Policy Optimization Algorithms

Reference 64

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unresolved
no resolver link, observed 2026-08-08T00:51:25.025149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.025149Z digest=sha256:bbb1af6eee649a67ea4cf03cf961898fee39b768a4114fed103892bd9b0bc11e

Observation 2f8860d8-de94-47b4-ac83-0f576c4dc1db · outbound

This paper cites SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.027810Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.027810Z digest=sha256:1aba298f5a82e5c924759b64c2a51b2b4dde14d3fd97233a89607699f9ee733c

Observation 5c7924ec-49e9-472d-8b0d-ef809e3e2859 · outbound

This paper cites 2025 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , eprint=

Reference 66

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unresolved
no resolver link, observed 2026-08-08T00:51:25.030741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.030741Z digest=sha256:ff4f01f882c24a41424665754c71c426ddbe9266e3dc1e7b54820d16d85e1f39

Observation d846356e-fef5-4e2c-bb81-dcab8bd5d115 · outbound

This paper cites 2021 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2021 , eprint=

Reference 67

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unresolved
no resolver link, observed 2026-08-08T00:51:25.033447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.033447Z digest=sha256:2f0d4dd116de9ad592432019f78956e4beaff720f1c65385eddc807ed15a8db2

Observation 95efbe3e-738e-4301-8e88-cf35352831ed · outbound

This paper cites 2018 , publisher=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2018 , publisher=

Reference 68

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unresolved
no resolver link, observed 2026-08-08T00:51:25.036133Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.036133Z digest=sha256:4a7928f81b8602363d8babffa50d7f0bab7dacfa7f31017660c1f68e124757f7

Observation a82567e2-1149-4f66-9bd1-8d6940c54fab · outbound

This paper cites arXiv preprint arXiv:2511.08567 , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs arXiv preprint arXiv:2511.08567 , year=

Reference 69

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.038958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.038958Z digest=sha256:d73dffbab89dc0533917257740e37e563157607ed21192e4ed353aa0afdcf88b

Observation 992b03f0-173e-4f22-af7c-5828a9d78df8 · outbound

This paper cites 2023 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2023 , eprint=

Reference 70

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unresolved
no resolver link, observed 2026-08-08T00:51:25.041478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.041478Z digest=sha256:5cc3014b6ca9f773bc150d7235204d4f859cfa7159e04f4dc2ea21a208d5befd

Observation c2ae80be-b48c-4a30-8693-dbf3e39bd428 · outbound

This paper cites Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.044392Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.044392Z digest=sha256:ffd49c693bd69809336cb6fb9b9b198dd7d893d7c613aec105043a37c15b3f1f

Observation 6ff86dea-41c1-47b1-9ea2-89aaca1fd3c3 · outbound

This paper cites Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Revisiting Reinforcement Learning for LLM Reasoning from A Cross-Domain Perspective

Reference 72

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.047158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.047158Z digest=sha256:85ef985be7b9a0272bee2750c17b701ed2dc9485ca8bd47cceaabbd82ed42d57

Observation e66d5eb6-190b-4889-a7df-0d3c10249ede · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs The Fourteenth International Conference on Learning Representations , year=

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.845486Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.050015Z digest=sha256:71ad7f6845eea67cee0961f73a1c15cd2df26ef98a1aab9cf8747e2a493c098e

Observation 89566f01-e99a-4fe2-aa09-d5807c6082a6 · outbound

This paper cites Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.837858Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.052625Z digest=sha256:8d5651bc017ca075cf934d8c258dafd2a3f0f3f8189a352f227ccf7416e95d3e

Observation 975416e0-961b-4e25-9587-d5bfc019080c · outbound

This paper cites Forty-second International Conference on Machine Learning , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Forty-second International Conference on Machine Learning , year=

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.829860Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.055253Z digest=sha256:8a27756f9f00bdbb85b59c6e33fabb6e1c6a3cd880db305562965e011b2a6441

Observation 47e5bb23-9f6d-4127-b083-cd1a1cf26d76 · outbound

This paper cites International conference on machine learning , pages=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs International conference on machine learning , pages=

Reference 76

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.058003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.058003Z digest=sha256:3fd0d84441806babfd4c6442172dbe4d2dd5c42bfcc5f481ace5d248b584a60b

Observation 556712b3-94f1-45aa-b5fb-6909f09cefe5 · outbound

This paper cites Editing Models with Task Arithmetic.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Editing Models with Task Arithmetic

Reference 77

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.060648Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.060648Z digest=sha256:3b4db064c815426e6579d0ee0389e1658fcf2f1c91429f441438b9949202fdbc

Observation f8209ebf-a8f4-45fe-9f2e-50e7deaccfbf · outbound

This paper cites Forty-first International Conference on Machine Learning , year=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Forty-first International Conference on Machine Learning , year=

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.063688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.063688Z digest=sha256:56b777dee6e86fa151582b7f624e10e50da100a1b7f32c4c5684ef39718eb87b

Observation 9ffd96e5-6234-4689-84bd-408099ee5923 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Advances in Neural Information Processing Systems , volume=

Reference 79

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.066306Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.066306Z digest=sha256:c488c9bf3ef276ab6ea6409619d96166ffb444acf7c350a3ff13c09ae0dc2376

Observation 1912973d-21a4-4e46-8168-a210dc0e8dfc · outbound

This paper cites Dataless Knowledge Fusion by Merging Weights of Language Models.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs Dataless Knowledge Fusion by Merging Weights of Language Models

Reference 80

Resolution
unresolved
no resolver link, observed 2026-08-08T00:51:25.068937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T00:51:25.068937Z digest=sha256:512ee04163ef0dc2b16eb1dc3df67d47ac1e22442258b078869f150021bd1028

Observation caf44552-0cef-4061-bad3-19aaea3ae23a · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.810348Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.071815Z digest=sha256:8deff1b22e8e28714c20f846531652294a38952a340f7cfd5efe0af3199c7ece

Observation ddd4fee7-4ce1-4dc2-a313-a8d2c9ee7221 · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.802733Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.074482Z digest=sha256:b9c4653913f4d0900c82b854df0b646b5b58dc2126a908428a9bc7a6cade4372

Observation 39cc38b0-c77e-4038-accc-df121c4630b7 · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.794796Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.077067Z digest=sha256:a065edfba84accaadf05dc630c7a32181f7eddeed6887510e9f7f6a69380239a

Observation 6b056ef3-3e89-4599-a46b-8c5d3df82a23 · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.786970Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.079487Z digest=sha256:0feec8c3b4500966fceed57ca3ba3274181ada057ada45d0497e8e0136257f31

Observation 82ccedf0-eeb8-4730-a59e-b833c30585a2 · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.778971Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.082053Z digest=sha256:bf93dcae969e959714227b67571e1920c069fcce4ec3ed839aa6da014cd18445

Observation 678625fb-776c-4013-88ad-7afa773708d4 · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.770980Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.084604Z digest=sha256:43fd0627c71d3294382a59dedce8462848fbb94335d67c25d59be062c1a05a56

Observation abf48d9c-71d8-4055-b9e7-41899d946b6f · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.762900Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.087330Z digest=sha256:d6a9c696780ea286e0282155ac5227e7603734f37f1a7ad27b5982da98e52000

Observation 10ddd987-57c6-4940-a2b7-328d30167c99 · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.754873Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.089778Z digest=sha256:ac4469caa9ad3add70f87e26884380a244b34fc29fa6f36065b3b7268fb44292

Observation 22fc5538-5170-4c1d-b216-5e3ca146df99 · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.747135Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.092301Z digest=sha256:3298239a6eac18120743ab7d96f2e0607b54bb185048577c495b55a1b8130e82

Observation 7478ca43-fb12-4840-ba87-a003ba3c8dff · outbound

This paper cites 2025 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2025 , eprint=

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.739308Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.094778Z digest=sha256:65d7cae1ff3af884128613169af7513c765d9e9d292ce59cce81c7bb89edf334

Observation f4b5e2d6-d10d-4199-969d-945f04036517 · outbound

This paper cites 2026 , eprint=.

SFT Conflicts, RL Coexists: A Theoretical and Empirical Analysis of Multi-Task Learning for LLMs 2026 , eprint=

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T00:51:25.730046Z

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.

source=arxiv_source observed=2026-08-08T00:51:25.097330Z digest=sha256:4a10b8cb7659ccfb710a17b56298540afdd861f6b6c074a0c2237f4cd9045393

Pith citing papers

No inbound Pith citation observations are available.