Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-21T17:40:10.135567Z
Paper Citation Record · LEDGER
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution
As of 23 August 2026, this Paper Citation Record lists 100 of 100 outbound references and 2 inbound Pith citation observations for arXiv:2512.05958.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-02T21:53:25.695298Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T05:05:56.861299Z
Reference resolution
100 of 100 outbound references displayed
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External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 817caaaf-fa48-49dc-bb0f-f217e478ba8c · outbound
This paper cites https://gist.ai/.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution https://gist.ai/
Reference 1
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a1ef407e-a8f3-4708-a5d2-23410ce5752c · outbound
This paper cites Geo: Generative engine optimization.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Geo: Generative engine optimization
Reference 2
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation e9f6e963-86e8-42e3-b7f8-d2a03bf354df · outbound
This paper cites Introducing pay per crawl: Enabling content owners to charge AI crawlers for access.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Introducing pay per crawl: Enabling content owners to charge AI crawlers for access
Reference 3
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation ae28303e-50ae-4769-b7b2-151aae50050a · outbound
This paper cites Will Google’s AI Overviews kill news sites as we know them?, 7.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Will Google’s AI Overviews kill news sites as we know them?, 7
Reference 4
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2b5fcc35-d517-410f-8dcf-f3d9493fc741 · outbound
This paper cites an unresolved cited work.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Unresolved cited work
Reference 5
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7cf2f6da-2112-4479-b5ff-8f70bffce66c · outbound
This paper cites Claude 3.5 Haiku.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Claude 3.5 Haiku
Reference 6
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 15499217-c0cd-4874-ba47-0ae6a29462b4 · outbound
This paper cites Introducing Claude 4.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Introducing Claude 4
Reference 7
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 67612fc8-651a-4d0e-9b47-258744ace3b8 · outbound
This paper cites Pricing.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Pricing
Reference 8
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 46d315ce-27e2-41ae-9f82-898a6885ef0f · outbound
This paper cites deterministic.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution deterministic
Reference 9
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4aa65d8d-785d-45bb-aa15-cc91ebd9786c · outbound
This paper cites A Turvey-Shapley Value Method for Distribution Network Cost Allocation.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution A Turvey-Shapley Value Method for Distribution Network Cost Allocation
Reference 10
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation aefa2d4b-d9c8-41fe-a25d-89955f94ea0d · outbound
This paper cites MS MARCO: A Human Generated MAchine Reading COmprehension Dataset.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution MS MARCO: A Human Generated MAchine Reading COmprehension Dataset
Reference 11
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bab8611d-5c85-4899-a065-9e8edb06493e · outbound
This paper cites Ads in Conversations.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Ads in Conversations
Reference 12
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b823db9c-6ecb-4032-a28c-e7d469eabe0f · outbound
This paper cites Anthropic PBC, No.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Anthropic PBC, No
Reference 13
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d0b91ef1-bccb-4033-9a7a-318102081cb1 · outbound
This paper cites Data-driven mechanism design: Jointly eliciting preferences and information.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Data-driven mechanism design: Jointly eliciting preferences and information
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.237819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0d82181e-0206-462d-858d-a96f42f3642b · outbound
This paper cites Google users are less likely to click on links when an AI summary appears in the results.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Google users are less likely to click on links when an AI summary appears in the results
Reference 15
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 63af827b-c8e3-4d81-9a18-63ce7bee1cc0 · outbound
This paper cites Generative Engine Optimization: How to Dominate AI Search.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Generative Engine Optimization: How to Dominate AI Search
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.260396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d4829e33-6467-4ef7-b17c-8f0548d2f30d · outbound
This paper cites Glass, Shang-Wen Li, and Wen tau Yih.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Glass, Shang-Wen Li, and Wen tau Yih
Reference 17
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b2850d75-7d79-4de2-ac52-9d22ececb266 · outbound
This paper cites Learning to Attribute with Attention.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Learning to Attribute with Attention
Reference 18
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.219731Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f489ee44-d058-41d2-b54f-241000b5d76c · outbound
This paper cites Contextcite: Attributing model generation to context.NeurIPS, 37:95764–95807.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Contextcite: Attributing model generation to context.NeurIPS, 37:95764–95807
Reference 19
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 6fcf0cd5-64e6-46ad-a392-86d4fa8ff519 · outbound
This paper cites Overview of the trec 2020 deep learning track.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Overview of the trec 2020 deep learning track
Reference 20
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0a2e9aa7-8a36-4fba-891f-2bc79d586723 · outbound
This paper cites V oorhees.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution V oorhees
Reference 21
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 877e9447-565f-4055-89e6-241e3fce6f7c · outbound
This paper cites Perplexity in talks with top brands on ads model as it challenges google.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Perplexity in talks with top brands on ads model as it challenges google
Reference 22
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 431fde92-580d-4fc0-ae1f-dbb29656c6e4 · outbound
This paper cites an unresolved cited work.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Unresolved cited work
Reference 23
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation aa491a1f-5674-46fd-8f76-268d4c07db21 · outbound
This paper cites Google gemini: A multimodal ai model.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Google gemini: A multimodal ai model
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.687342Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b72d706e-c16e-4dd6-b08e-69bbf630ae85 · outbound
This paper cites Attention with Dependency Parsing Augmentation for Fine-Grained Attribution.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Attention with Dependency Parsing Augmentation for Fine-Grained Attribution
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.251226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 48174696-0edc-4f9d-ae48-0db10e9b9047 · outbound
This paper cites Auc- tions with llm summaries.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Auc- tions with llm summaries
Reference 26
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1a7464aa-50a3-4958-8266-10e65a8bd002 · outbound
This paper cites Mechanism design for large language models.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Mechanism design for large language models
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.713828Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 57e58688-c4a9-40e2-9ac1-a263f07f54e7 · outbound
This paper cites Ai is killing the web.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Ai is killing the web
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.811919Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a86cfb1e-1bb5-421c-8bdd-a4f6da624638 · outbound
This paper cites Online Advertisements with LLMs: Opportunities and Challenges.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Online Advertisements with LLMs: Opportunities and Challenges
Reference 29
- Resolution
- verified exact
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 04ad679c-ced2-40aa-a4e0-d58b9b48b76a · outbound
This paper cites Online advertisements with llms: Opportunities and challenges.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Online advertisements with llms: Opportunities and challenges
Reference 30
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4fa44a20-1b5e-4481-b045-622308acd00d · outbound
This paper cites Penske Media sues Google over AI summaries taking traffic.Axios, 9 2025.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Penske Media sues Google over AI summaries taking traffic.Axios, 9 2025
Reference 31
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d22ab1f8-a2bc-4393-844f-d04f8b1bb691 · outbound
This paper cites Data shapley: Equitable valuation of data for machine learning.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Data shapley: Equitable valuation of data for machine learning
Reference 32
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 40b46cf7-d629-493b-9e4f-6e4f602ce77a · outbound
This paper cites A Survey on LLM-as-a-Judge.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution A Survey on LLM-as-a-Judge
Reference 33
- Resolution
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 45bb71ab-37c1-465d-81b7-7499db9fcc71 · outbound
This paper cites RAG" Stands for “Royalties.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution RAG" Stands for “Royalties
Reference 34
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 37550eee-b028-4fcc-b88b-0bda8a33569b · outbound
This paper cites Realm: Retrieval-augmented language model pre-training.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Realm: Retrieval-augmented language model pre-training
Reference 35
- Resolution
- verified fuzzy
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 8e0fbcc0-a396-451c-b0f2-20728a7cbe7e · outbound
This paper cites Ad auctions for llms via retrieval augmented generation.NeurIPS, 37:18445– 18480.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Ad auctions for llms via retrieval augmented generation.NeurIPS, 37:18445– 18480
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.822679Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d5b69132-9536-4b0b-83e9-3cf6ecde7d06 · outbound
This paper cites A shapley value-based incentive mechanism in collaborative edge computing.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution A shapley value-based incentive mechanism in collaborative edge computing
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.648428Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 69b8c388-dbff-41e9-a072-04ae5184f443 · outbound
This paper cites LAQuer: Localized Attribution Queries in Content-grounded Generation.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution LAQuer: Localized Attribution Queries in Content-grounded Generation
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.215595Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a2593213-6ccd-4648-a612-ea1b7e9e4983 · outbound
This paper cites Datamodels: Understanding predictions with data and data with predictions.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Datamodels: Understanding predictions with data and data with predictions
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.646032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 167f43a2-2eed-4c92-b988-a376da0fcbfe · outbound
This paper cites Atlas: Few-shot learning with retrieval augmented language models.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Atlas: Few-shot learning with retrieval augmented language models
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.767961Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f9f82a69-0a9d-490b-80a2-ddf1e35172c5 · outbound
This paper cites Virtual machine power accounting with shapley value.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Virtual machine power accounting with shapley value
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.755242Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b136b4a6-d580-48ad-8fee-8dc101ece480 · outbound
This paper cites an unresolved cited work.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Unresolved cited work
Reference 42
- Resolution
- unresolved
- raw_fallback, observed 2026-05-21T17:40:26.700181Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation b2ee82f6-0aad-4c6f-8d43-52d86e2b56f3 · outbound
This paper cites Colbert: Efficient and effective passage search via contextualized late interaction over bert.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Colbert: Efficient and effective passage search via contextualized late interaction over bert
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.814691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3e773cc2-05a2-484a-9f12-27570a4d1533 · outbound
This paper cites Engaging the many-hands prob- lem of generative-ai outputs: A framework for attributing credit.AI and Ethics.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Engaging the many-hands prob- lem of generative-ai outputs: A framework for attributing credit.AI and Ethics
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.757725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 34f85726-2a26-44b5-97da-10aceb923f09 · outbound
This paper cites Understanding black-box predictions via influence functions.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Understanding black-box predictions via influence functions
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.752437Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bcdb50a3-4151-48fb-9a2c-c583470d82df · outbound
This paper cites The impact of llms on sponsored search: Evidence from google’s bert.USC Marshall School of Business Research Paper Sponsored by iORB.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution The impact of llms on sponsored search: Evidence from google’s bert.USC Marshall School of Business Research Paper Sponsored by iORB
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.778443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bf110d09-aeef-4f45-a022-0ee80e5a841e · outbound
This paper cites How to Correctly Report LLM-as-a-Judge Evaluations.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution How to Correctly Report LLM-as-a-Judge Evaluations
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-06-02T03:04:02.584259Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4a18f8bb-58d6-47b6-83eb-854b9702087c · outbound
This paper cites Grade: Generating multi-hop qa and fine-grained difficulty matrix for rag evaluation.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Grade: Generating multi-hop qa and fine-grained difficulty matrix for rag evaluation
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.735570Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1af68438-7fc0-4229-bc0e-9029bc544056 · outbound
This paper cites Retrieval-augmented generation for knowledge-intensive nlp tasks.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Retrieval-augmented generation for knowledge-intensive nlp tasks
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.737888Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7f203e6b-a43a-440e-98a7-9585e2dfaeef · outbound
This paper cites Llm whisperer: An inconspicuous attack to bias llm responses.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Llm whisperer: An inconspicuous attack to bias llm responses
Reference 50
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.775441Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 45a28dd4-e466-4b6a-9303-e6791aaa9c1c · outbound
This paper cites Attribot: A bag of tricks for efficiently approximating leave-one-out context attribution.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Attribot: A bag of tricks for efficiently approximating leave-one-out context attribution
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.770507Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation e674b769-cb55-4bf7-99ab-a31474648967 · outbound
This paper cites Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.786375Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 01831593-b05e-4f3e-a5a2-745f7e73c50b · outbound
This paper cites Real-time Ad retrieval via LLM-generative Commercial Intention for Sponsored Search Advertising.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Real-time Ad retrieval via LLM-generative Commercial Intention for Sponsored Search Advertising
Reference 53
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.241325Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c2b83c4c-951d-488c-8e4a-dda316142993 · outbound
This paper cites G-eval: Nlg evaluation using gpt-4 with better human alignment.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution G-eval: Nlg evaluation using gpt-4 with better human alignment
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.763244Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 72491c91-d709-4791-abe1-6d2c05b6a1c7 · outbound
This paper cites A unified approach to interpreting model predictions.NeurIPS, 30.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution A unified approach to interpreting model predictions.NeurIPS, 30
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.750102Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a82a5796-e3bf-4727-8643-63f1927f2d44 · outbound
This paper cites an unresolved cited work.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Unresolved cited work
Reference 56
- Resolution
- unresolved
- raw_fallback, observed 2026-05-21T17:40:26.731042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 19fd8fa9-6819-47a4-ad67-c43c95040285 · outbound
This paper cites On cooperative settlement between content, transit and eyeball internet service providers.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution On cooperative settlement between content, transit and eyeball internet service providers
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.733309Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c7a6fbc6-37eb-4b72-aae6-094ada42e1b7 · outbound
This paper cites Efficient computation of the shapley value for game-theoretic network centrality.Journal of Artificial Intelligence Research, 46:607–650.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Efficient computation of the shapley value for game-theoretic network centrality.Journal of Artificial Intelligence Research, 46:607–650
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.797020Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5b03e723-b3b2-4e5b-9f9b-04b19c3d4696 · outbound
This paper cites In- centivizing peer-assisted services: A fluid shapley value approach.SIGMETRICS.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution In- centivizing peer-assisted services: A fluid shapley value approach.SIGMETRICS
Reference 59
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.831866Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation ce423af9-9c83-4987-8521-ec5e290fdc9c · outbound
This paper cites Sampling permutations for shapley value estimation.Journal of Machine Learning Research, 23(43):1–46.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Sampling permutations for shapley value estimation.Journal of Machine Learning Research, 23(43):1–46
Reference 60
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.728991Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7c7ce2cb-cd97-40ef-9555-8e94abc49461 · outbound
This paper cites Sponsored question answering.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Sponsored question answering
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.745172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 9f63c5af-7cb7-41d3-9c42-c7d35471c008 · outbound
This paper cites Source Attribution in Retrieval-Augmented Generation.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Source Attribution in Retrieval-Augmented Generation
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.230222Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 9259a03e-167f-4348-ad3f-6a41fc78fca8 · outbound
This paper cites Adversarial Search Engine Optimization for Large Language Models.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Adversarial Search Engine Optimization for Large Language Models
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.248051Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 4456b524-e294-46c1-8581-5417f5371dca · outbound
This paper cites Chegg sues Google for hurting traffic as it considers alternatives.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Chegg sues Google for hurting traffic as it considers alternatives
Reference 64
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.819947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 55c8a5b4-bae2-43b6-b516-bb3442c78ac5 · outbound
This paper cites Introducing GPT-4.1 in the API.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Introducing GPT-4.1 in the API
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.659192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 67fb7061-7d55-4a93-b787-129b1d465671 · outbound
This paper cites Pricing.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Pricing
Reference 66
- Resolution
- parse uncertain
- raw_fallback, observed 2026-05-21T17:40:26.747481Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 56f139f7-8170-4e26-b5c3-ff122432a1c7 · outbound
This paper cites Llm visibility: Ai search statistics.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Llm visibility: Ai search statistics
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.802453Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5875d451-2cd0-4f41-bead-2281b94936c9 · outbound
This paper cites Llm evaluators recognize and favor their own generations.Advances in Neural Information Processing Systems, 37:68772–68802.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Llm evaluators recognize and favor their own generations.Advances in Neural Information Processing Systems, 37:68772–68802
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.651216Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 115ebab1-e813-4bf2-a615-1320a9ac656c · outbound
This paper cites TRAK: Attributing model behavior at scale.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution TRAK: Attributing model behavior at scale
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.689692Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 867b6314-c74f-452c-b767-a985ee1bb220 · outbound
This paper cites News publisher files class action antitrust suit against Google, citing AI’s harms to their bottom line, 12 2023.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution News publisher files class action antitrust suit against Google, citing AI’s harms to their bottom line, 12 2023
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.709291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2e46b0f0-a5c5-4595-8a64-85cbb9463916 · outbound
This paper cites Perplexity AI.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Perplexity AI
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.691644Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 9bbf5ee3-032f-425d-93ee-0dc3c76c29cb · outbound
This paper cites Anthropic to pay $1.5 billion to settle authors’ copyright lawsuit.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Anthropic to pay $1.5 billion to settle authors’ copyright lawsuit
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.673628Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7e187d93-f7c4-4a0c-835c-835fec8bfeff · outbound
This paper cites Esti- mating training data influence by tracing gradient descent.Advances in Neural Information Processing Systems, 33:19920–19930.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Esti- mating training data influence by tracing gradient descent.Advances in Neural Information Processing Systems, 33:19920–19930
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.664141Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation bdcbe430-8fe5-4289-888b-f2dc67548911 · outbound
This paper cites Model internals- based answer attribution for trustworthy retrieval-augmented generation.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Model internals- based answer attribution for trustworthy retrieval-augmented generation
Reference 74
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.702456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation ce6c4a32-f8fc-476e-9b24-1f0d01af0171 · outbound
This paper cites why should i trust you?.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution why should i trust you?
Reference 75
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.704745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation c866f80f-1e16-44e7-8bb7-7309e9d45468 · outbound
This paper cites Ai overviews: How are publishers adapting to the rise of clickless search?.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Ai overviews: How are publishers adapting to the rise of clickless search?
Reference 76
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.693868Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 70b8dc04-be19-4315-a168-5032f51251e8 · outbound
This paper cites The butterfly effect of altering prompts: How small changes and jailbreaks affect large language model performance.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution The butterfly effect of altering prompts: How small changes and jailbreaks affect large language model performance
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.638040Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 5d3cea7a-d91d-4ed6-bcca-ac985142ac96 · outbound
This paper cites ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction
Reference 78
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.254151Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f657d05d-c1fc-49fb-9f24-e8c89aa45bb2 · outbound
This paper cites A value for n-person games.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution A value for n-person games
Reference 79
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.653195Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation f769ebae-e4da-4c84-b678-f181923fdcc2 · outbound
This paper cites Princeton University Press Princeton.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Princeton University Press Princeton
Reference 80
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.696083Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation ee40c656-0025-476d-a07e-06ef37c314e9 · outbound
This paper cites A shapley-value mechanism for band- width on demand between datacenters.IEEE Transactions on Cloud Computing, 6(1):19–32.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution A shapley-value mechanism for band- width on demand between datacenters.IEEE Transactions on Cloud Computing, 6(1):19–32
Reference 81
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.799536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 0f877532-05b6-4d2e-a50a-f2dd523971f0 · outbound
This paper cites https://www.similarweb.com/.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution https://www.similarweb.com/
Reference 82
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.726773Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation aa94b14b-7c10-45b6-849e-7b2ff32605e3 · outbound
This paper cites Consumer reliance on ai search results signals new era of marketing.Bain & Company.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Consumer reliance on ai search results signals new era of marketing.Bain & Company
Reference 83
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.783548Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 8f5047c1-5fc1-4709-9f1b-1f93e9113913 · outbound
This paper cites Goodbye Clicks, Hello AI: Zero-Click Search Redefines Marketing.Bain & Company, 2 2025.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Goodbye Clicks, Hello AI: Zero-Click Search Redefines Marketing.Bain & Company, 2 2025
Reference 84
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.791914Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation d418e56f-2ee3-4b21-8e39-509a3881e21d · outbound
This paper cites On economic heavy hitters: Shapley value analysis of 95th-percentile pricing.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution On economic heavy hitters: Shapley value analysis of 95th-percentile pricing
Reference 85
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.809092Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 7b6c4f21-2928-428c-9a01-5ec1446bbed3 · outbound
This paper cites Microsoft Corporation et al.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Microsoft Corporation et al
Reference 86
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.825591Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 19cec4dc-8dc1-4269-aa1e-f5ab3ad479ca · outbound
This paper cites Musique: Multihop questions via single-hop question composition.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Musique: Multihop questions via single-hop question composition
Reference 87
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.829095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 8f729105-4e8b-42e9-867c-ef7471d51895 · outbound
This paper cites An Economic Solution to Copyright Challenges of Generative AI.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution An Economic Solution to Copyright Challenges of Generative AI
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:40:26.234171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation cea2bb4d-008e-4076-8fe9-15928cf90c73 · outbound
This paper cites Wang, Prateek Mittal, Dawn Song, and Ruoxi Jia.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Wang, Prateek Mittal, Dawn Song, and Ruoxi Jia
Reference 89
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.724775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 6f8e9ada-6bd8-4c8c-b94d-0d97dd165bde · outbound
This paper cites Tracllm: A generic framework for attributing long context llms.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Tracllm: A generic framework for attributing long context llms
Reference 90
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.698073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3f3b6685-8364-4bbc-8d91-facf2c007c7e · outbound
This paper cites How to interpret spearman and Kendall correlation coefficients.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution How to interpret spearman and Kendall correlation coefficients
Reference 91
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.657278Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 18944334-e4a0-47ad-b70f-156693103a2c · outbound
This paper cites Wang, and Jian Du.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Wang, and Jian Du
Reference 92
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.655262Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1d21897f-05e3-41e0-a7c6-dd62f6562569 · outbound
This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering
Reference 93
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-21T17:40:26.223574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 1ec6a292-36ae-403b-8c2a-1f77e2203d94 · outbound
This paper cites John Wiley & Sons, Inc.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution John Wiley & Sons, Inc
Reference 94
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.681351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3c0a72b7-7838-4a86-a118-12be51358e8b · outbound
This paper cites If we assume X, then Y.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution If we assume X, then Y
Reference 95
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.789005Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 09faf3df-023b-4240-a2a6-2c40d98fde2c · outbound
This paper cites Do NOT remove anything that is required for correctness.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Do NOT remove anything that is required for correctness
Reference 96
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.683840Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation a1eb9d6c-f521-4cf0-acd7-d449096fc5a0 · outbound
This paper cites an unresolved cited work.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Unresolved cited work
Reference 97
- Resolution
- unresolved
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Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2a0a6b16-6713-4c37-ae04-ffe32584bd6c · outbound
This paper cites an unresolved cited work.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Unresolved cited work
Reference 98
- Resolution
- unresolved
- raw_fallback, observed 2026-05-21T17:40:26.716088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 3ec45253-1802-4f4d-91ba-dad1b4181c1e · outbound
This paper cites Keep each reasoning step separate.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution Keep each reasoning step separate
Reference 99
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.707022Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 2d856c50-0ba8-44c3-9666-b6413adbf7f7 · outbound
This paper cites keypoint dis- tillation.
MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution keypoint dis- tillation
Reference 100
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-21T17:40:26.780933Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Pith citing papers
Observation 719ad747-8669-4c1f-b302-b89cfef2fc96 · inbound
TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning cites this paper.
TRUE: A Trustworthy Unified Explanation Framework for Large Language Model Reasoning MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution
Reference 7
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24b62eae-1970-4698-b87e-0d18c7e52fe0 · inbound
In-Context Credit Assignment via the Core cites this paper.
In-Context Credit Assignment via the Core MaxShapley: Towards Incentive-compatible Generative Search with Fair Context Attribution
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T02:04:48.497166Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.