Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T06:05:57.170198Z
Paper Citation Record · LEDGER
As of 18 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 0 inbound Pith citation observations for arXiv:2607.22039.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T06:05:57.170198Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
67 of 67 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 06df0665-ec5e-4d2c-9425-9ae16114aa68 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Advances in Neural Information Processing Systems , volume=
Reference 1
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Advances in Neural Information Processing Systems , volume=
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Merging by Matching Models in Task Parameter Subspaces
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Localizing Task Information for Improved Model Merging and Compression
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Editing Models with Task Arithmetic
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Proceedings of the 37th International Conference on Machine Learning , pages =
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Advances in Neural Information Processing Systems , volume=
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Observation d95b9602-bc6d-4bf9-a478-c70af074dc7d · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Advances in Neural Information Processing Systems , volume=
Reference 12
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Observation 36ad303a-b79b-4d0a-8c7a-dbc9a0f9ba00 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Stochastic Weight Averaging in Parallel: Large-Batch Training that Generalizes Well
Reference 13
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Observation 2e7ef861-5da1-4dbb-a1ae-de08a76279e6 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Averaging Weights Leads to Wider Optima and Better Generalization
Reference 14
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Observation 1ccd4d0a-8f7e-46c9-83fa-f71d8067c776 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2025 , eprint=
Reference 15
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Advances in neural information processing systems , volume=
Reference 16
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Reference 17
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Observation eba78512-6d08-45be-ac40-6aad70068da7 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Physics of Language Models: Part 3.1, Knowledge Storage and Extraction
Reference 18
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Observation f95dbf6d-fb09-494e-91e7-48e4c24f91b3 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning Process
Reference 19
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Observation 8410c22e-4d1f-4afb-8801-971b92b1665a · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Quantifying Generalization Complexity for Large Language Models
Reference 20
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Observation ada029d9-5956-4296-b492-854d8deec6a9 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs What Do Learning Dynamics Reveal About Generalization in
Reference 21
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Learning Dynamics of LLM Finetuning
Reference 22
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Observation 9c45545e-a2ef-40c8-9486-a68a0ee71104 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs LENSLLM: Unveiling Fine-Tuning Dynamics for LLM Selection
Reference 23
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Observation 0039bceb-7ca8-4543-810c-7dab9bbb038d · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs The Llama 3 Herd of Models
Reference 24
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Observation c5ab4e4f-956a-49c1-8193-2a5a81bcd3f6 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Qwen2 Technical Report
Reference 25
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Observation 13bda98a-2068-4c54-9b5b-2a6eff05ba0e · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 26
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Observation 860dfd0c-aa4f-437f-b169-48b90016f0d5 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Journal of Machine Learning Research , volume=
Reference 27
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Advances in Neural Information Processing Systems , volume=
Reference 28
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Observation 6c59b6a9-bcd0-4949-9abc-fa4a61093e0e · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Finetuned Language Models Are Zero-Shot Learners
Reference 29
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 30
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Observation 289fac9f-adec-40e9-bda5-d53a408cb475 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Advances in neural information processing systems , volume=
Reference 31
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Observation 393c9667-0dc0-40b9-a3c5-b2b3eb581052 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Back to Basics: Revisiting REINFORCE Style Optimization for Learning from Human Feedback in LLMs
Reference 32
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Observation 5ef39d0b-de10-4c80-8a42-7803ad3f8a02 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2025 , eprint=
Reference 33
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Observation b5a338d5-78b6-4df5-8d1f-c4f448739518 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs OpenMathInstruct-2: Accelerating
Reference 34
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Observation dfd607cb-0c88-4f38-8e07-97e40981afa2 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2024 , eprint=
Reference 35
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Observation ff3e786a-dbbe-4583-ba20-1f3a46ef4e31 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Forty-first International Conference on Machine Learning , year=
Reference 36
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Observation aee9eb66-a38e-442b-9d76-1377c3f3a86d · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2023 , eprint=
Reference 37
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Observation aefc9fb8-22aa-4dbd-a734-9a8300c869ae · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models , url =
Reference 38
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Observation 75ad2fbc-9d9d-425d-8b97-92aa5aa0f55e · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2025 , eprint=
Reference 39
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Observation 48f3d2d1-e1bb-4bd6-8c52-d857553e2209 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2025 , eprint=
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2025 , eprint=
Reference 41
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Observation 31a7bb4d-1880-4c07-8812-cdb6046d06c3 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2025 , eprint=
Reference 42
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Observation 9d250c81-b5a6-4022-8457-38e443c31451 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2022 , eprint=
Reference 43
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Training Verifiers to Solve Math Word Problems
Reference 44
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Observation 70ecba10-f1c2-4b66-af57-e1ee0195f5f5 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Measuring Mathematical Problem Solving With the MATH Dataset
Reference 45
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Observation 0990f357-14a0-4e75-9ded-59ffb584d99f · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs The Twelfth International Conference on Learning Representations , year=
Reference 46
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Observation 4f422ead-f77e-4181-8a04-ac6c9be17d8c · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Evaluating Large Language Models Trained on Code
Reference 47
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Observation 178880e9-0e33-4808-ac40-d6bd2bbb36ba · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Program Synthesis with Large Language Models
Reference 48
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Observation 27bedb12-c561-4d34-ae58-f2ff13ef687c · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs LiveBench: A Challenging, Contamination-Limited LLM Benchmark
Reference 49
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Observation a921cb4f-312a-485d-929e-12d7307e61a9 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Instruction-Following Evaluation for Large Language Models
Reference 50
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Observation a6e792da-d85f-4ec4-a1e1-f9b8abf76e23 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs On Memorization of Large Language Models in Logical Reasoning
Reference 51
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Cognition , volume=
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Deep Model Fusion: A Survey
Reference 53
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Harnessing Multiple Large Language Models: A Survey on LLM Ensemble
Reference 54
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Observation 33ec3258-ecfc-4de7-afad-2a9cd95bd552 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
Reference 55
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs 2024 , journal =
Reference 56
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs SIAM Journal on Control and Optimization , volume=
Reference 57
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Machine learning , volume=
Reference 58
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Observation e1d0c07b-05c0-4ab3-aa57-3f22d4103419 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Proximal Policy Optimization Algorithms
Reference 59
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Observation fb1e3dc4-9fbc-4a3a-ab7a-8b88034e80b2 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs arXiv preprint arXiv:2505.11711 , year=
Reference 60
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Observation 2c7d888f-4d85-4092-bf1f-e17bf16d2b21 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs RL's Razor: Why Online Reinforcement Learning Forgets Less
Reference 61
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Observation 9f4e1571-7c45-4938-975c-b37406cd49b7 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models
Reference 62
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs From Task-Specific Models to Unified Systems: A Review of Model Merging Approaches
Reference 63
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs IEEE Transactions on Audio, Speech and Language Processing , volume=
Reference 64
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Observation 7bd55e0c-8d90-4bf8-9b89-3332c8fa6972 · outbound
Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs A Survey of Large Language Models in Discipline-specific Research: Challenges, Methods and Opportunities
Reference 65
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs arXiv preprint arXiv:2510.02272 , year=
Reference 66
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Enough is as good as a feast: A Comprehensive Analysis of How Reinforcement Learning Mitigates Task Conflicts in LLMs Findings of the Association for Computational Linguistics: ACL 2024 , pages=
Reference 67
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No inbound Pith citation observations are available.