Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-02T18:14:56.831711Z
Paper Citation Record · LEDGER
AI Can Learn Scientific Taste
As of 5 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 7 inbound Pith citation observations for arXiv:2603.14473.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-02T12:22:54.748120Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T12:26:56.078325Z
Reference resolution
87 of 87 outbound references displayed
- verified exact3
- verified fuzzy0
- unresolved83
- parse uncertain0
- malformed identifier1
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation aa30e7de-a703-48fa-8915-996bc8540d87 · outbound
This paper cites Terri and g&d: celebrating 50 years of enlightened scientific judgment.Genes&Development, 37(1-2): 6–8, 2023.
AI Can Learn Scientific Taste Terri and g&d: celebrating 50 years of enlightened scientific judgment.Genes&Development, 37(1-2): 6–8, 2023
Reference 1
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:48.532861Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 73574b7f-1f2a-4de0-945c-f80db966cfad · outbound
This paper cites Mitchison.
AI Can Learn Scientific Taste Mitchison
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:48.602957Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 486cef4d-86c4-4966-9f0e-c5441720e3d8 · outbound
This paper cites Introducing deep research.
AI Can Learn Scientific Taste Introducing deep research
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:48.691062Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9b561094-430f-4b96-9703-f28df27b8e43 · outbound
This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.
AI Can Learn Scientific Taste Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:48.789010Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation add26b79-2c3a-4e75-9b4f-5366d74ab79c · outbound
This paper cites Deepresearcher: Scalingdeepresearchviareinforcementlearninginreal-worldenvironments.
AI Can Learn Scientific Taste Deepresearcher: Scalingdeepresearchviareinforcementlearninginreal-worldenvironments
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:48.876044Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb15951c-84a6-4d4b-b463-fb01b6b85007 · outbound
This paper cites WisPaper: Your AI Scholar Search Engine.
AI Can Learn Scientific Taste WisPaper: Your AI Scholar Search Engine
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:48.961158Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7600e99-0cc3-4450-8d8d-9dd589e3ad87 · outbound
This paper cites Codex, 2025.
AI Can Learn Scientific Taste Codex, 2025
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.025412Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c246d1f-3d52-4883-85ec-d2d49659dcfc · outbound
This paper cites Claude code, 2025.
AI Can Learn Scientific Taste Claude code, 2025
Reference 8
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.078415Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9f16d470-50c6-4034-98d6-c5adeb6435e3 · outbound
This paper cites Introducing fars, 2026.
AI Can Learn Scientific Taste Introducing fars, 2026
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.151555Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b65cdc1-e486-4209-a64b-7aecc7adba52 · outbound
This paper cites Agent Laboratory: Using LLM Agents as Research Assistants.
AI Can Learn Scientific Taste Agent Laboratory: Using LLM Agents as Research Assistants
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.199143Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8446e6af-8147-4d1d-a481-6e0ca4855a48 · outbound
This paper cites The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search.
AI Can Learn Scientific Taste The AI Scientist-v2: Workshop-Level Automated Scientific Discovery via Agentic Tree Search
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.294417Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6638573e-6ff0-498b-95ec-ff1aa89313e9 · outbound
This paper cites Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers.
AI Can Learn Scientific Taste Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.367455Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0ed6a4f8-d435-46e3-a8f4-50c19c7b8ac4 · outbound
This paper cites The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas.
AI Can Learn Scientific Taste The Ideation-Execution Gap: Execution Outcomes of LLM-Generated versus Human Research Ideas
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.432140Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f7843b11-7883-4304-9cff-d6da0377884c · outbound
This paper cites Of the Standard of Taste (1757), pages 145–154.
AI Can Learn Scientific Taste Of the Standard of Taste (1757), pages 145–154
Reference 14
- Resolution
- verified exact
- doi, observed 2026-08-02T18:18:26.235443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation d78cdd4b-b87f-44a2-a315-ec109b4be740 · outbound
This paper cites Art and Its Significance: An Anthology of Aesthetic Theory,Third Edition.
AI Can Learn Scientific Taste Art and Its Significance: An Anthology of Aesthetic Theory,Third Edition
Reference 15
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.598433Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c36f70b1-c418-4ed2-909f-bfb6ac8fd524 · outbound
This paper cites Quantifying long-term scientific impact.Science, 342 (6154):127–132, 2013.
AI Can Learn Scientific Taste Quantifying long-term scientific impact.Science, 342 (6154):127–132, 2013
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.680966Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7224cace-c6d2-41bc-8c6f-a9dd33e4afec · outbound
This paper cites Science of science.Science, 359(6379):eaao0185, 2018.
AI Can Learn Scientific Taste Science of science.Science, 359(6379):eaao0185, 2018
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.844525Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f423c084-1aae-4047-82a9-ee19963d9dc0 · outbound
This paper cites WorldPM: Scaling Human Preference Modeling.
AI Can Learn Scientific Taste WorldPM: Scaling Human Preference Modeling
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:49.961366Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 742eaa18-f719-4be0-a12c-487e3911df7e · outbound
This paper cites Training language models to follow instructions with human feedback, 2022.
AI Can Learn Scientific Taste Training language models to follow instructions with human feedback, 2022
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.048360Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 52ee92da-1809-4755-ba1f-5d6550cc5792 · outbound
This paper cites Learning to summarize from human feedback.
AI Can Learn Scientific Taste Learning to summarize from human feedback
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.175829Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ad7b4d95-86db-494a-8959-c9d62fcc80f7 · outbound
This paper cites RewardBench: Evaluating Reward Models for Language Modeling.
AI Can Learn Scientific Taste RewardBench: Evaluating Reward Models for Language Modeling
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.265339Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 637b1400-4ceb-4add-9383-c99153db5a94 · outbound
This paper cites RMB: Comprehensively Benchmarking Reward Models in LLM Alignment.
AI Can Learn Scientific Taste RMB: Comprehensively Benchmarking Reward Models in LLM Alignment
Reference 22
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.350098Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a625218-dee7-4b6e-b395-3d97d857f5b3 · outbound
This paper cites Reward Reasoning Model.
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.408504Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 96c41a9b-a9ec-4d22-90da-f7537d07d22a · outbound
This paper cites Generative Reward Models.
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.501246Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c7d4f224-5240-4e36-9678-c6d1c821e4b8 · outbound
This paper cites Generative Verifiers: Reward Modeling as Next-Token Prediction.
AI Can Learn Scientific Taste Generative Verifiers: Reward Modeling as Next-Token Prediction
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.591229Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5fb40137-eb2e-4911-9368-a7062d89f522 · outbound
This paper cites Inference-time scaling for generalist reward modeling.arXivpreprintarXiv:2504.02495, 2025.
AI Can Learn Scientific Taste Inference-time scaling for generalist reward modeling.arXivpreprintarXiv:2504.02495, 2025
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.748252Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bb171096-79ff-4530-849e-11c7c51eb651 · outbound
This paper cites Rm-r1: Reward modeling as reasoning.arXivpreprintarXiv:2505.02387, 2025.
AI Can Learn Scientific Taste Rm-r1: Reward modeling as reasoning.arXivpreprintarXiv:2505.02387, 2025
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.859885Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7934e8df-2ad5-455e-a2b7-39bab09110fe · outbound
This paper cites Unified Reward Model for Multimodal Understanding and Generation.
AI Can Learn Scientific Taste Unified Reward Model for Multimodal Understanding and Generation
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:50.987523Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9ebd7cf7-402f-4ae3-ad92-f5b84a077bff · outbound
This paper cites Unified multimodal chain-of-thought reward model through reinforcement fine-tuning.arXivpreprintarXiv:2505.03318, 2025.
AI Can Learn Scientific Taste Unified multimodal chain-of-thought reward model through reinforcement fine-tuning.arXivpreprintarXiv:2505.03318, 2025
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:51.105310Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a2af4170-0608-41fa-b6d5-052232e8526e · outbound
This paper cites an unresolved cited work.
AI Can Learn Scientific Taste Unresolved cited work
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:51.189005Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d02969f7-5561-4d8a-b174-5e09a40e5e6d · outbound
This paper cites Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning.
AI Can Learn Scientific Taste Pref-GRPO: Pairwise Preference Reward-based GRPO for Stable Text-to-Image Reinforcement Learning
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:51.516571Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1be7ff5-937a-4181-995b-018431ef1d16 · outbound
This paper cites The invisible leash: Why rlvr may or may not escape its origin.arXivpreprintarXiv:2507.14843, 2025.
AI Can Learn Scientific Taste The invisible leash: Why rlvr may or may not escape its origin.arXivpreprintarXiv:2507.14843, 2025
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:51.674929Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 555b72e9-5ddc-4114-a8cf-283019d8d507 · outbound
This paper cites Group Sequence Policy Optimization.
AI Can Learn Scientific Taste Group Sequence Policy Optimization
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:51.821816Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a38bf8d-64e5-441c-9ca9-f3154437f372 · outbound
This paper cites Self-foveate: Enhancing diversity and difficulty of synthesized instructions from unsupervised text via multi-level foveation, 2026.
AI Can Learn Scientific Taste Self-foveate: Enhancing diversity and difficulty of synthesized instructions from unsupervised text via multi-level foveation, 2026
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:51.949946Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dafb56fd-1cf3-443b-b9c6-aa13158e2dd6 · outbound
This paper cites Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies.
AI Can Learn Scientific Taste Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.088803Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4118b16a-0b55-44a3-a83a-f8d953c886b1 · outbound
This paper cites MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering.
AI Can Learn Scientific Taste MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.244321Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 728fce13-cfcb-49f5-8a4c-6568be3cf373 · outbound
This paper cites The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery.
AI Can Learn Scientific Taste The AI Scientist: Towards Fully Automated Open-Ended Scientific Discovery
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.398892Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 15a31f7b-fee0-46f2-84ba-1cae8434da87 · outbound
This paper cites AI4Research: A Survey of Artificial Intelligence for Scientific Research.
AI Can Learn Scientific Taste AI4Research: A Survey of Artificial Intelligence for Scientific Research
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.495524Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 91f09421-4b1b-4fed-815c-797f2910204f · outbound
This paper cites Deepscientist: Advancing frontier-pushing scientific findings progressively.arXivpreprintarXiv:2509.26603, 2025.
AI Can Learn Scientific Taste Deepscientist: Advancing frontier-pushing scientific findings progressively.arXivpreprintarXiv:2509.26603, 2025
Reference 39
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.577237Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4b2f50ca-a395-40e0-a2bc-b7404b9dc5b4 · outbound
This paper cites Innovatorbench: Evaluatingagents’abilitytoconductinnovativellmresearch.
AI Can Learn Scientific Taste Innovatorbench: Evaluatingagents’abilitytoconductinnovativellmresearch
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.654560Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 37ab2b6e-165e-4793-8da3-e07c19432fd2 · outbound
This paper cites Can LLMs generate novel research ideas? a large-scale human study with 100+ NLP researchers, 2024.
AI Can Learn Scientific Taste Can LLMs generate novel research ideas? a large-scale human study with 100+ NLP researchers, 2024
Reference 41
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.736008Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation bf3375ff-b829-43ce-b2ae-5e58086c3bf9 · outbound
This paper cites Agentreview: Exploring peer review dynamics with llm agents.
AI Can Learn Scientific Taste Agentreview: Exploring peer review dynamics with llm agents
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.820112Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 44812474-fdc2-4e34-a6d2-64cd6f32c43e · outbound
This paper cites MARG: Multi-Agent Review Generation for Scientific Papers.
AI Can Learn Scientific Taste MARG: Multi-Agent Review Generation for Scientific Papers
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.904473Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4343c64e-12f3-4553-97a2-793a7247ea5b · outbound
This paper cites aixiv: A next-generation open access ecosystem for scientific discovery generated by ai scientists.
AI Can Learn Scientific Taste aixiv: A next-generation open access ecosystem for scientific discovery generated by ai scientists
Reference 44
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:52.989697Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a3918ab-d13c-4650-876a-f1a42743f415 · outbound
This paper cites Can large language models provide useful feedback on research papers? a large-scale empirical analysis.NEJMAI, 1(8):AIoa2400196, 2024.
AI Can Learn Scientific Taste Can large language models provide useful feedback on research papers? a large-scale empirical analysis.NEJMAI, 1(8):AIoa2400196, 2024
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.061200Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b734ef6d-3fbd-4960-9c61-1ededdf2b517 · outbound
This paper cites Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025.
AI Can Learn Scientific Taste Can LLM feedback enhance review quality? A randomized study of 20K reviews at ICLR 2025
Reference 46
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.155809Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 68aed043-79a1-4416-8ca0-6fa9fa14357c · outbound
This paper cites Towards an AI co-scientist.
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.215246Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ec086ed3-3bea-4ea6-98cc-29cdc32f9199 · outbound
This paper cites Deepreview: Improving llm-based paper review with human-likedeepthinkingprocess.
AI Can Learn Scientific Taste Deepreview: Improving llm-based paper review with human-likedeepthinkingprocess
Reference 48
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.279500Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 70348e42-c923-439b-9f3c-b69bc1eb0b84 · outbound
This paper cites CycleResearcher: Improving Automated Research via Automated Review.
AI Can Learn Scientific Taste CycleResearcher: Improving Automated Research via Automated Review
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.359988Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ae654f7d-b650-458f-87a8-c152a2eb46c8 · outbound
This paper cites Opennovelty: An llm-powered agentic system for verifiable scholarly novelty assessment, 2026.
AI Can Learn Scientific Taste Opennovelty: An llm-powered agentic system for verifiable scholarly novelty assessment, 2026
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.451733Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 40e2e86f-2a58-48f7-b032-5a1285f05ce1 · outbound
This paper cites Training a helpful and harmless assistant with reinforcement learning from human feedback,.
AI Can Learn Scientific Taste Training a helpful and harmless assistant with reinforcement learning from human feedback,
Reference 51
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.537013Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5a67efdf-2bc2-4537-a37f-9402ca10ddaa · outbound
This paper cites DeepSeek-R1: Incentivizing reasoning capability in LLMs via reinforcement learning, 2025.
AI Can Learn Scientific Taste DeepSeek-R1: Incentivizing reasoning capability in LLMs via reinforcement learning, 2025
Reference 52
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.677276Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 678487eb-4d75-429f-96cc-8945cf8ff22f · outbound
This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.
AI Can Learn Scientific Taste Tulu 3: Pushing Frontiers in Open Language Model Post-Training
Reference 53
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.750125Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ebf9e8d2-fff3-459b-ba96-1963f759456a · outbound
This paper cites Game-rl: Synthesizing multimodal verifiable game data to boost vlms’ general reasoning, 2025.
AI Can Learn Scientific Taste Game-rl: Synthesizing multimodal verifiable game data to boost vlms’ general reasoning, 2025
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.813576Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0263f3fc-7d10-4160-a451-83f4a4b1b014 · outbound
This paper cites Exploring the compositional deficiency of large language models in mathematical reasoning, 2024.
AI Can Learn Scientific Taste Exploring the compositional deficiency of large language models in mathematical reasoning, 2024
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.866621Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cb0d2230-cf79-47a1-9020-8a22e116072e · outbound
This paper cites From words to worth: Newborn article impact prediction with llm.
AI Can Learn Scientific Taste From words to worth: Newborn article impact prediction with llm
Reference 56
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.925020Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1489dc2c-5ab3-40ac-9e49-7aec947c24c5 · outbound
This paper cites Naipv2: Debiased pairwise learning for efficient paper quality estimation, 2025.
AI Can Learn Scientific Taste Naipv2: Debiased pairwise learning for efficient paper quality estimation, 2025
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.976380Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e658038d-c390-4a66-aced-80b2bd4a4030 · outbound
This paper cites ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking.
AI Can Learn Scientific Taste ArenaRL: Scaling RL for Open-Ended Agents via Tournament-based Relative Ranking
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.048082Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b12daa5-3eb9-41c1-89b8-cdcb18c6bb43 · outbound
This paper cites Qwen2.5 Technical Report.
Reference 59
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- unresolved
- no resolver link, observed 2026-08-02T18:14:54.158971Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 003c2018-de66-421e-a3d4-430c2025eda7 · outbound
This paper cites Qwen3 Technical Report.
Reference 60
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- unresolved
- no resolver link, observed 2026-08-02T18:14:54.234945Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 773ae30c-f911-4934-97fe-517343800d7a · outbound
This paper cites The Llama 3 Herd of Models.
Reference 61
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.341650Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3aaee713-1b19-4cdd-bdad-d1e9b66717db · outbound
This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.
AI Can Learn Scientific Taste Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Reference 62
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.419502Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e8128d5-93ef-485c-8298-ea6fa87d21a6 · outbound
This paper cites SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning.
AI Can Learn Scientific Taste SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning
Reference 63
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.470711Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d708b6ee-f5db-4601-b1fe-fad1af42af51 · outbound
This paper cites DianJin-R1: Evaluating and Enhancing Financial Reasoning in Large Language Models.
AI Can Learn Scientific Taste DianJin-R1: Evaluating and Enhancing Financial Reasoning in Large Language Models
Reference 64
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.543326Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f44f5df8-ac25-45ac-9c26-8ba6bfa81712 · outbound
This paper cites rStar2-Agent: Agentic Reasoning Technical Report.
AI Can Learn Scientific Taste rStar2-Agent: Agentic Reasoning Technical Report
Reference 65
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.599326Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7ba993eb-7cce-4f29-87bb-a105448036be · outbound
This paper cites STRUCTSENSE: A Task-Agnostic Agentic Framework for Structured Information Extraction with Human-In-The-Loop Evaluation and Benchmarking.
AI Can Learn Scientific Taste STRUCTSENSE: A Task-Agnostic Agentic Framework for Structured Information Extraction with Human-In-The-Loop Evaluation and Benchmarking
Reference 66
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.642462Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 252988a3-7c68-4428-97a4-94cc3161bb16 · outbound
This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.
AI Can Learn Scientific Taste Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities
Reference 67
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.699629Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14721a90-bfdf-49cd-98a5-ca1d30a30522 · outbound
This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.
AI Can Learn Scientific Taste Kimi k1.5: Scaling Reinforcement Learning with LLMs
Reference 68
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.758883Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1a1e9a9-e753-42cf-abaf-ab2cbac433f5 · outbound
This paper cites Formally Verified Neurosymbolic Trajectory Learning via Tensor-based Linear Temporal Logic on Finite Traces.
AI Can Learn Scientific Taste Formally Verified Neurosymbolic Trajectory Learning via Tensor-based Linear Temporal Logic on Finite Traces
Reference 69
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:54.850851Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b10d94e5-e47a-474a-b802-19ffcb38953f · outbound
This paper cites The Logic of Graph Neural Networks.
AI Can Learn Scientific Taste The Logic of Graph Neural Networks
Reference 70
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- unresolved
- no resolver link, observed 2026-08-02T18:14:54.923885Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 402ef6a6-a0dc-456d-acfa-e43d8cc935a6 · outbound
This paper cites Corpus based amharic sentiment lexicon generation.
AI Can Learn Scientific Taste Corpus based amharic sentiment lexicon generation
Reference 71
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:55.023714Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57c1077d-03d1-41b2-a1f4-7497c7997aca · outbound
This paper cites Erratum: Orientation dynamics of asymmetric rotors using random phase wave functions [phys.
AI Can Learn Scientific Taste Erratum: Orientation dynamics of asymmetric rotors using random phase wave functions [phys
Reference 72
- Resolution
- verified exact
- doi, observed 2026-08-02T18:18:26.009631Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 09657480-a4e7-4de4-a379-89f22938e418 · outbound
This paper cites The theory of variational hybrid quantum-classical algorithms.NewJournal ofPhysics, 18(2):023023, February 2016.
AI Can Learn Scientific Taste The theory of variational hybrid quantum-classical algorithms.NewJournal ofPhysics, 18(2):023023, February 2016
Reference 73
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- unresolved
- no resolver link, observed 2026-08-02T18:14:55.079855Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6fe225d9-96e0-49bd-815b-7a2be35587ac · outbound
This paper cites Identifying boosted objects with n-subjettiness.Journal of High EnergyPhysics, 2011(3), March 2011.
AI Can Learn Scientific Taste Identifying boosted objects with n-subjettiness.Journal of High EnergyPhysics, 2011(3), March 2011
Reference 74
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- unresolved
- no resolver link, observed 2026-08-02T18:14:55.156276Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 14fdd794-430c-4295-954c-179be09554d9 · outbound
This paper cites One-side forward-backward asymmetry at the lhc.PhysicalReview D, 83(1), January 2011.
AI Can Learn Scientific Taste One-side forward-backward asymmetry at the lhc.PhysicalReview D, 83(1), January 2011
Reference 75
- Resolution
- verified exact
- doi, observed 2026-08-02T18:18:25.722478Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 9440c505-1608-4a6a-97e1-54932f0d41e3 · outbound
This paper cites PU-Net: Point Cloud Upsampling Network.
AI Can Learn Scientific Taste PU-Net: Point Cloud Upsampling Network
Reference 76
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:55.528037Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 954c7d53-0ae5-436d-89b1-35ffd6010438 · outbound
This paper cites Open3D: A Modern Library for 3D Data Processing.
AI Can Learn Scientific Taste Open3D: A Modern Library for 3D Data Processing
Reference 77
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:55.747300Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4fef7fd0-648f-45d0-9e96-3e15e33e0aa6 · outbound
This paper cites OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning.
AI Can Learn Scientific Taste OpenCIL: Benchmarking Out-of-Distribution Detection in Class-Incremental Learning
Reference 78
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:55.922965Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3c25ee16-49c5-423a-b43c-b6ed891803f1 · outbound
This paper cites YOLOv11: An Overview of the Key Architectural Enhancements.
AI Can Learn Scientific Taste YOLOv11: An Overview of the Key Architectural Enhancements
Reference 79
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:56.158782Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0e2e83d6-4626-4df0-b180-046c56fafda8 · outbound
This paper cites Jukebox: A Generative Model for Music.
AI Can Learn Scientific Taste Jukebox: A Generative Model for Music
Reference 80
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:56.225201Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 371f6d9d-30ef-44ed-a8d6-af533d666ec6 · outbound
This paper cites Neural mos prediction for synthesized speech using multi-task learning with spoofing detection and spoofing type classification, 2020.
AI Can Learn Scientific Taste Neural mos prediction for synthesized speech using multi-task learning with spoofing detection and spoofing type classification, 2020
Reference 81
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:56.324784Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4a993af3-263f-4814-9eb9-63f035d009f0 · outbound
This paper cites On purity and applications to coderived and singularity categories.
AI Can Learn Scientific Taste On purity and applications to coderived and singularity categories
Reference 82
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:56.391179Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2c370ac4-b88b-4a24-a256-d279c5738aee · outbound
This paper cites Yoneda lemma for complete Segal spaces.
AI Can Learn Scientific Taste Yoneda lemma for complete Segal spaces
Reference 83
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:56.452452Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6e723178-f096-4e0a-8c44-d47d0b5d872c · outbound
This paper cites On purity and applications to coderived and singularity categories.
AI Can Learn Scientific Taste On purity and applications to coderived and singularity categories
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:56.831711Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 99fcec53-fb22-4823-8d4f-d525e772e683 · outbound
This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.
AI Can Learn Scientific Taste Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback
Reference 2022
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:53.610990Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4f41c409-a810-438e-9c71-131097211151 · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
AI Can Learn Scientific Taste DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T18:14:51.347634Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ca65411-195a-4c1d-b491-e89633e46c99 · outbound
This paper cites invisible leash.
AI Can Learn Scientific Taste invisible leash
Reference 2025
- Resolution
- malformed identifier
- no resolver link, observed 2026-08-02T18:14:56.647589Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
Observation b8ec8b61-7544-4f39-8497-3da0c267ca1b · inbound
GIANTS: Generative Insight Anticipation from Scientific Literature cites this paper.
GIANTS: Generative Insight Anticipation from Scientific Literature AI Can Learn Scientific Taste
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-07-16T02:22:35.377592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 0104882c-363b-4505-ad2d-ed8c3ce5532c · inbound
ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration cites this paper.
ARIS: Autonomous Research via Adversarial Multi-Agent Collaboration AI Can Learn Scientific Taste
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-07-16T02:22:35.377592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation fbeb01da-cf0b-480d-a8fd-a3e45794a547 · inbound
FAME: Forecasting Academic Impact via Continuous-Time Manifold Evolution cites this paper.
FAME: Forecasting Academic Impact via Continuous-Time Manifold Evolution AI Can Learn Scientific Taste
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-07-16T02:22:35.377592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2fca9695-7b9d-478b-a9a9-425a662a176a · inbound
GraphReview: Scientific Paper Evaluation via LLM-Based Graph Message Passing cites this paper.
GraphReview: Scientific Paper Evaluation via LLM-Based Graph Message Passing AI Can Learn Scientific Taste
Reference 6
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-16T02:22:35.377592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 19489b27-40ac-4a3a-80df-cd8b3e818ed4 · inbound
SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones? cites this paper.
SoundnessBench: Can Your AI Scientist Really Tell Good Research Ideas from Bad Ones? AI Can Learn Scientific Taste
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-07-16T02:22:35.377592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 4481f05a-e7e7-4e07-ae5e-b1081c30cbf9 · inbound
ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment cites this paper.
ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment AI Can Learn Scientific Taste
Reference 4
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-16T02:22:35.377592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 32ed8270-80ed-4115-a273-c3744a7a637c · inbound
Measuring the Gap Between Human and LLM Research Ideas cites this paper.
Measuring the Gap Between Human and LLM Research Ideas AI Can Learn Scientific Taste
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-07-16T02:22:35.377592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.