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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 8 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 2026-08-08T06:32:00.761636+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

Resolution
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:caa64dd37d6a743c26b10c8cbca38a2f34e3948de4c8a049d2be8a51b066af8b

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:e5a5153962a92fa10d5312b199572eca62a6fb518a26e992c48b902c6b834da1

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:f6756e0b4129fd3db0580dbc49776608d182061630493d8ef6a4c6a8ba1a46d3

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=sha256:249483d2651d918f90b9b6072b0bd61948207e6cfd27f8b3a5e00783c6610b93

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=sha256:5bdc119452d802e7d17f679ba1c9ffee4708ea54fdea1e96a33835166708de11

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=sha256:58b0b3be9a79d5a90d6f549e8950f792f516b6a7d1f4f970019af12ee6191e47

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:a44bc1a84125da53a05a267e72c1d806759f6968cc6e6d09964bdfd165fa9140

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=sha256:61390d4bf89f5d4b29de9bbc79df2016bc43238a0ff5fcc58280dc25f08bb942

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=sha256:91f2fb0e0456a359ecbcbde4de4ef71b89405c6cc2312c7c48657fb36137354d

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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unresolved
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=sha256:6668c76bc69ff06a08d79d37fe2911f3cf1d90ace657438db160687a4e3efeca

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:fe447ba921e893971d77c1f298f050f39f2936cfe8885e1bde28292f20161109

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:cd71acf907779b50d89999f8aab0ecbf620c3c06e0aabdd85df5b2ac35acafe1

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:d998e422407efc231a85643f47103a82edd1ddbbae081c4e489d84976d90f8a8

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=sha256:463a0b472c8b4633307f7217cb31993b77b9362ad87a84a18f3931f86c85df47

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=sha256:35ecbe9d26098de1cb8c07425ede7e96d0e8c908e36749842604c39244f2bd6a

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=sha256:1c739e12650ef70e8d01c2e24c32ed892c9202eeee0b6187907f2da8da68fd74

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=sha256:163852c4557f2b060c5a6699315b6ff6c3305fbb96b42eb03a3163da332155c2

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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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=sha256:2a9f5b7a5c0b705c4586d41377ea10cead88bf55ca8dfd6184c151be020fa2c0

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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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=sha256:5340ca5ac6d18c7665b687f00e7a08a3d75b2f75b53427d1e5bc0a6c01e39e8d

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:a34961b3c37e4298147a5791b698e92eec0027a810162158b582d62617018e3f

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:a38faa6a60fe7c5964e26048eff3ee1e00c21a2fe7b01b27edcceed6cc1ae3e9

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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unresolved
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:d2001216ed04c43bbfe488006e52c43d428ac450935b9abc4dfcd352c7e0d033

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

Resolution
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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:24.908993Z digest=sha256:29d9ae0a43f67d4ae20fd0ac38597e22bd236ae7f49d16dcbf05eadf10b1698b

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:d057891d0620c699046f04f6398192bd66ec38c7471db293cf72f3bd09855203

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:d281749219a43c884a0ceb1732db9b2dc0809fdfb61f120c28908febefa85ff1

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=sha256:1f9f5453fe3d362884b994622bc5b80be19465cf1f77d756e842eaa6521c9899

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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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:d3e43565052de294d7bccf7ee0aabd7525bb00fb213fcd61499db21106d32902

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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unresolved
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=sha256:523a77ef44ca28e0ff1973720df96f8a261608faa79f1c0ef379c4dfb8d253c2

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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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=sha256:50f2216db459634c269337112abef3b27aed37362c2e299a0029f3683073690a

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:f7dce1d581c44352be50e8b8f79e521e4aec978b754ce027e481692e09cf9c39

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:24.932337Z digest=sha256:0e9f1e7082f6d5d10971e6796490ce500ae8bb98690096c9131feb1bf4917677

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=sha256:5a9767651a88eb43a16ae50507945f3815be7d91ee53ae83691b38c409d4376f

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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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:a95be9794764ac4ba7980ced5ae45b039b2a98501641d997ed5a1f86964c4142

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=sha256:24cf381984f34b6506d1b38e99b3b35c492518980f62178dd18d8f83176623b5

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:24.943161Z digest=sha256:9679ee927956d835286e9dd9024d75025dd4ae517dcaf9c8b753b96a89605eab

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:24.945853Z digest=sha256:48b302bc18cfbe398d6f140b623d1ef0356e7d28244068f78b018df6cd718c5a

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=sha256:07a6c3d6576377b1c28cb2e97d3890596477efea8d66585e46dfe96ef30da464

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:b7fb368715f8b6aa3a92733f6492e7df85a5eca9602f1ec1f0872baaa7794d16

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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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=sha256:4f457a0052b687defc31e9cc0977b1c206462f8530a057883dd260c0da58b12b

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:fc3f222c2455cb40efe54e317cd36c3d170868c5bdfe6592e970dde859f54141

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=sha256:65318293c618dc7412dac31ccc14114749746a7c5723dc508f08be6472d65351

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:d3bb9442627c56a297c3bdecc271331d6888ac3fda8d7d9be4745f3ba3f13afd

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:ea217cf1b8ee7109c875e3b4ca0742c464be29e2e90810aecb25e27a741e70c2

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=sha256:2b043ff9e4b29b9b8e2b5e82111a0034d682b322e95f7acbec80b5b39d3a2ad9

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=sha256:5e8f1d775181f12f402e84b95bcb895ff213f64211d9499dd2d1d0b37235ca76

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:cf2e6d4d0b079f0fc66d2e6fc9f283516a334d913c19b06b5bcce27c954e1d27

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:ba7721283917b8185f9cffb7398ee7d5b7b6867a98341ba16d758ad846a7c746

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:c0f294f68b0c2c901937a446e3884e49b55ffc0d70edfcc2020986ee4814c328

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=sha256:4a0c5e8ca2451343975284d6fed8af5d93ebeb0db33a46851094e0d83ac7780e

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

Resolution
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=sha256:069f4cdd58c4995616c1f119371465a4ffe0e7348ef64efffa8e014845180e96

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=sha256:4d6012f4e9c6a5c50c010fa0845ed28745a142f28b413f29a0a381bffbc1b67a

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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unresolved
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=sha256:38db6bf26cd1f3ec5cca6de3dfd51cfdaf42ac5779cd70855befdab7f124b8e9

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:24.994352Z digest=sha256:c3ac82f0df4cc2a642b3eb8d73e467b25c7b4ed71dbc691e8edd8707fd16f0f1

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=sha256:8cc2f6274472a2dfadcbbe32d926aa6ee39f20353ec1606523213a7d544e481d

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

Resolution
unresolved
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=sha256:47e10769dfb0b28afe127466f0b6072d8f29f88c3aa6d5c9610752ec3a860f70

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=sha256:04ac38d365c26c9be736f671852d607dc3838310dbe8f1fee270bfa26f8e2314

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.005420Z digest=sha256:402f820b6545c723d60b56e5b516ae3c5c6720390ba500a67c89cc2125a4b783

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

Resolution
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:a1718fedebf377925b4b226b962a6991a5472182460bfcb56cf9f95b0a179535

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=sha256:249fbd61e6fec8ed1ad6e8683ae7d01595627c47fbf4787df925155745942cca

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=sha256:24e60031ca18948582aca2bc666ac4185c95245a9aa99c27a1b44d49be0fa5aa

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:a3bba22d9abe16dc38e5453f8445d96d32684dfd705e997e6038a3fa3111f1b9

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

Resolution
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:ced8f3130c18614cdc3635c83fa094cd68222ac6d6a8cce592645509d8afce79

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.022641Z digest=sha256:296f196dee0535aaa6e3cf2e33ac8d6b3b49174000dac1ad638aa630fb5a414b

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=sha256:77d7e389f2c1a1d751bae2a164aedb86c90572178985a4275f115b53affdb0bb

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=sha256:3a95e9ffa89796c4d446d02b3ff629152eaf478cfffd2ae3a4e732cb9f97a2ab

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=sha256:05de07cb67c3c90727c0af185396a224113edca137834c8002e7c2838db222be

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

Resolution
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=sha256:7db504b28a2972a415aa926dafbeb282d13bf4c26bd76e09c54b4fa150e2eb3e

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:fcab3ead8eb59341e488d0431faddd9f711fe1b7f49bb42d9afc09dba440f100

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=sha256:83604b0397d921d67bc9f289ed74e5095a34753651f040985a624eda967f9703

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:ad48ed34db07956bb2d77d18d90ac12b416c89f2a136a5fa95565e072aa50ac6

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=sha256:0c3a2fde44b516fe20caea6e03c93022275fdd4e5572f9f46c3775d274cef557

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:f330194a439668f1615fa7fc55c363f512bb0c806e5d05dd7edb5ece47e34b15

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.050015Z digest=sha256:7e83074edb6bcae1ead6487bc6594decfdb5f70d2ceda470f0382b9223341649

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.052625Z digest=sha256:665cd1829eea402faf6428eb60e9a3af8cdeb2c15de3b17f7837625389522f11

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.055253Z digest=sha256:ef5e9d72d15695a058daaae6fb08b132c26e20d2114054f52efa3e0d944ee0a2

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=sha256:8cfa373018871f6c1767e984785fc446234a9dc34791f19f40ba3d2b336bd0c2

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=sha256:187be35ce53ed7aeb8c16e27a3846a6d5b1e63d0d6e2c0ab74dee768b13e1387

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:c2e41f790831f578f4d8ded0d5424fb72d06dc5192850d763bd28d33bd0bc2dd

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:cec4936e8cbc4d8521ff884420d91ae558833741dace639afb29a301ef0544ae

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=sha256:8f1cc31c87734783415033686b58ebc1ddd725d11414701120cd358e21a5da1d

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.071815Z digest=sha256:e0a2af41f5c0623a3afb574e30880cbd32c31327079c2312f5bd8f9d1d7ec40d

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.074482Z digest=sha256:3325da1b4025508b3ae003a65bfaac69226cc3cc4345b62257d948d0bf8ebea4

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.077067Z digest=sha256:cdd66af8d7422e286741c3f88d3fb4ff57defffd8669e4a98567b9e788c0e157

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.079487Z digest=sha256:f2cbe120a87342d4d0e9436013090aea42b844dd74c8e6273989d6cbf4d8df93

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.082053Z digest=sha256:48196285e081ddd88846c34b92305877e6081ea36cd38023c87803a0eb7d6d49

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.084604Z digest=sha256:29e8f4fd3a437259eb2d1728bc3b433162479440702381a747dee169c45576f0

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.087330Z digest=sha256:a500e38ed77c50e12e90f7ef1912d57f2ed2bd82adf7effabeee60c157e23929

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.089778Z digest=sha256:1409ab5486e331635a1686f144fd764b5543eb397434f1a183e01cc5b17d3cfe

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.092301Z digest=sha256:02b37a8ef136144b95dadc38667c8c267dc882cc0aced81103e2aae9a1c2ce8c

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.094778Z digest=sha256:a8c712f93d70139bed74549948dab571ee3930b977e0027635ffd4b92c705441

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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-08T00:51:25.097330Z digest=sha256:4bce95655e9e8d09863ecf2d0fcb9440aef9ff1ec3da149f639a67fcc10c954b

Pith citing papers

No inbound Pith citation observations are available.