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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

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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=sha256:9031b83297a1af8682427b3b2d9e643dc482e29d5c88be0908266f8b09252d21

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:eb3c491d5d84a2d8058b3426ebeec2d8237fe535d6c459e18d06aa0563933dd5

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=sha256:4679dc4c4dd8c4fd06a0210c587007fe5b81b54f6c8ae9beb84a6ac47d17b8a1

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:e3d20ec606d0daf7dd7fc96eafe1a2827a9a4ef51c8e6bf074d62bae69114189

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=sha256:20abda1df8227482760b1d5de61611550f868a3af9fe0fc7f2d39b16a8f0c749

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=sha256:36323ae12f5a9a00f0a30fa762f24144cf429456b614d380c5310bb639d65558

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

Resolution
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=sha256:8410e0fa028291dbc6b32963275ea2794be3ab0d756b6f887f827495312b4d91

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=sha256:933dacdded0c95a7d2cf9111401ee9a6a5ce04bdf834ee8fe738e8433f50ebb5

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:ef87562e187d80d148ffebc4f4190fc104b279d94bbb2b91c1f69e524fc0ec48

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=sha256:5782097d6708f64089a951e6521b75389ab8664c744aba4cfd0bc398c4c46383

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:f2cc1dcf0c12c4eaa38e36984ddf9047500a0e5bd966db2547708ad7c5ac2787

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=sha256:6f091bf30f33997ed73b211e44557e4f15ffc428bde186bc45199a12537fb9a5

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:a5858444c9a975276deb2ad77d6250b9b1ab0b849676fbad8fddce6fcf6e3fb5

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=sha256:7e4826257354f0b6a2794dde8779cf610362e840f18d63916dad574de2a97b19

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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unresolved
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=sha256:0b4601711dbd87d8be779e7417bc306b18e569b8ffa78ab33673c862440df2d0

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=sha256:0fcc974e750012f942a97316e2c3d1831cf9452120c407f28fe4657785bfd839

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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unresolved
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:a257a3cac4eb9a11dd7920f98ed85a039baa5b3b47d70811f02edb9ce85f96ad

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=sha256:2ed831da095a50b1fae53d16f1dcb60bb6fb03b6ddb21f9c304688bcf152091b

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:b91394f9aff15f2e4d12f16413a7d30bba4f32401310b156da57a5a137f2e104

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:eec96c0005f09a4412ddf5f71c187b80192614ced32bbba1f404a1e25d9ac506

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=sha256:8befc05d8ccd57b8e66cf7e8a45c35b352f65e586ce66f6970d6f063b8f2f06d

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:f46f4e6369cb7652928e72ac047158ba567142f0d3874d87707a98cda27e9fd0

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=sha256:852a14775b8bbf0dfc726e140a89b6e4a74da2e89396c64563d615387292db0d

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=sha256:1b1cad03db0a88c36ad1a53141ba1ea8e16598f68e8b714b4abe758c9012672d

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:c5afdc2579471eac42e161bd86d2fb7d12c29ebd4a9f1679fd6e6db950fbf4ca

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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unresolved
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=sha256:2256813333a8d56cb2b9726afe97a43c5c3394f86a33c6757bc549c4f8a361bf

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:b4b6b81c5549ed8f4000ef8f028b3d96e330b81cea7bb2b3335bf12d50f18eae

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=sha256:2574e63977847cc16887a4eca05ef4b130f654f36b9dbbd271e2d8828907b3af

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=sha256:5eb17e3a5c60c577a84c54d2593f3dbc3556befda53cd0f10a5f0e64e8559c0b

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=sha256:3cca70d5f40b7407cdc6777d0ba43416118b4ac7a703c29ccea1c3e7d0a3aa74

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:b642820c66781da360a46147245f4a8a05127fcd087b5ce77d74a3f623a9ad06

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=sha256:20fb41286e8a0a548d1f1214a7881784908ce17b32625ed54e6856ff2459528b

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=sha256:277b881cb5908c7492fb948cec2563033225266df76d426c682ab8963e4020de

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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unresolved
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=sha256:24f971052368bb963a5c54023e20ad152629adb064b7f5bc2d588d5c324f7e12

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:c05a4e7b04ac8dc4df8a4fc040eb1cdd600e44d98b33a3fa25fc1eb1aab13aad

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:c4568d9c88dd30286af6abbd9e94d3c5f2d790362829bc9f5cdeb92e2c6f3714

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=sha256:2942f4977887ff8a82b551af1783559bd2f7eba2f435e11ef007a31b4f9400a4

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=sha256:7bee883a7145f34db176236579d3027236a73d38ee500d5610e7c41f21259d1e

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:e558630f91b18d43e6bf2b4b779395d56cd4ba5864543e2d6d568ef31d6ac8fc

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=sha256:1a93307ce23da3f2be62c45c4b9c2686964ffced84eb32c33cdd400fb6b10058

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=sha256:7410c93d00557b42f9c7b8eeeec3699a54def05dd105bdc9d8e7377f4ed7e207

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=sha256:21c30eb0f83f56918345b56f1a8b4c9106dae11a62c8020e8c9080bdcccb8799

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

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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:cbe4e0a2657448c2233aaedca2a6c20b8ab463bdad460cc4541bedaab9d26016

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

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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=sha256:317a6b76b91d5710790cf7e4186c415364b0cfc1e3406f9db26e3e2e58911002

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

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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=sha256:20ea10ab0bbe35721b6e00c6bd38da7defd4f2816b7fd36de7a4252778a1a304

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

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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=sha256:5c1f4c94cb8ac23ebcdb776ab6004c47615356a954059e074d1bb7b4226b7d00

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

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unresolved
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=sha256:310f039aa2a4e281b3b9b3571a76d0d0239b7993d86541af5f8b4559527aa88c

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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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=sha256:957692d643fe7b11fe3ca66630ec4b63369c85ca928a9e3f7dbeb74f8b1bc9f3

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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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:f7a316e0485690d6716b8497f6e2d4c66e10a921a32dffbb619b33c16ecb7d8c

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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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=sha256:18f501473eeedfff8faf233a385a85b69b9cf87878b1f5f6090606faedcc255c

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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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:bba066a0e86e658672f30e2220f9cc19da8e39fa6b54d52a7b7b31cbb132a50b

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:f609507999e0a96c008a6cf413fab78334951f6e45220e41399f159e9f6b3b86

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=sha256:24a894a3ff8618cc391f5500f94546fa65f2d5fdf2983e172c8fcd66b5d57b71

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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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=sha256:1295ef3fcb5aa6ef6f55c6dba5bbbf39ff8393e52b2a32290007d06465dddd62

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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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=sha256:89fe45527e1fbdc375ab138e2aa0118c55aae02808e0754768c5aa05967516cd

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

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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=sha256:9ec5c298bf65fb5ac16662e0f52b1c348ec547b15d0411c61ba74f9abcaf1ab1

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=sha256:43f121767f90155724782771f95dcef99ae5d27b973572c5c7609e283105d339

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=sha256:051756f936598de0cbaedbfd711eaf0942472cec924156e53db5f79672d17dd8

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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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=sha256:9e5c8ddb98221cbdb63fdc6bcaff91114ba949bfa12759fc2d17c4064e993a70

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

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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=sha256:36b496891f98fc65d6cfd7447668d96005c818662bb2699829e197a072ef7c1e

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=sha256:77a986a5cace99bbadb8a504e528e4d9d08cb5d15c35bfb6c7e3c2b65b2f476e

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:d7f64f988b52a63fa009d6861113d2992b369e40c5b828fa0b706580e7309eb6

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=sha256:0f89d26a6fdf5dc0dbfa7aefb0455776ad928022bb5ea546f82e9a8705e2e385

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:bb5d98a06cb0dac643026f4d15e8926f98e1851cb890f39c04f8f20c6baeb876

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

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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=sha256:4fcd001d05b63fdb4ed63c4265aeccb0176ca7dde069bff7a609cd9f34272e87

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=sha256:7a7c6fb39dd56edcfab978919a0fa65bc76b08e6ff110105f498a06408cd27ef

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=sha256:3979a7b6c6ba840e096ec389c9aaebed0a31ed8e0a5bee667a39a13f789f68b7

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:b4461dbb49b999ec122901f8203a7ffd7ba851e5a782e407ff86cbee77d0c98f

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

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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=sha256:4ca23b2dfb49042bc0c39d68fcef689ea09e2b5e8e99c1629800c42531f44e28

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:f3f62177b967c6231276686ec2bda3a295eeb645f4a85f76d0affa86646c8cb4

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

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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:ae4fd08101ddbabd1979d7b2f6f9b375f244a9d31cd188a064b6619e96112442

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:e6c3da3ac301edd2b48b66fec9eae03ed1b85c23c499392d34fbfb46aac8a8fe

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:e639d4e00f5a63fa6366dad3315ca2c0d92fe7bebbdf89f3a26002fbe82738ae

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:c263942c3dcf2eb58c532c33ca116aca1e9e244e54efc3e0adf206e256de30da

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=sha256:3bf13c4a72786465437f94dc516ec522f34806d244d37c7ffe37f1c189bc68dc

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=sha256:789c4aa118e03c006f89ee365045d67cbb27075df3b91e7c16951a7678aba5b6

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:f9b14b930655f2852328655da0142ac7ec2f1514b2ef0d679a0d77f4a3288e85

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=sha256:2c303c0d0866caf84d419408a640ec72d1db639bb40ac220b193e49245667aeb

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=sha256:036cc154d93d9f469a1c4a6e77589aba2d8a97d0cca7fc24a3b37ae98ada059e

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:c8f5404654214e615f2ba829eee199fac2367f2d87be310dd8656f61a10a25da

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=sha256:443fce1e31b87562ca9d334663c10cf92ebe034f8b7c0d38f4db34f1b29cf0ed

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:ee603947b1b988a53baad9b866fd5c6776edd1d4edae77f43de08060ffd01178

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:bd89a06f1fd7153a38351b5185349e07b4cec3b868e000ff0e69d50a5305ab67

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=sha256:88c04cee8a710ee4dc7ba0b4250ba88dd6a16d0495f8fb76b7e33fc554069791

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=sha256:8c6e12f912945f9aee1399b3f5259e992fbbae6a249f4a8fa06146a1bf95d613

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:c314d29f2466f8446e6c305dfec59915a25fa93686c6d823c480ab3849b471fd

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:d43b1c428f25891f1dcb553c5aeb4bdfc9f633e284255c38966c47a1fd76db2f

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=sha256:33adad0f5a3a0bdb35cb86e6d85a7378937c72907b855f8a8fec72194fe52a15

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=sha256:774b5b31a946b6cff2e6da0deccd8e14be23c90db649f0bba6f927017fa9af61

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=sha256:28d3febe42c2bcadb245ee37daf48048a170186b1429cd55d52c6c54191a8f51

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=sha256:444e202f04f20c90d47ddf95e1f8b2fdc5ee817f0152f5f1f536183948985314

Pith citing papers

No inbound Pith citation observations are available.