Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T19:31:58.491532Z
Paper Citation Record · LEDGER
As of 9 August 2026, this Paper Citation Record lists 63 of 63 outbound references and 0 inbound Pith citation observations for arXiv:2607.04389.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T19:31:58.491532Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
63 of 63 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 80f544e5-6b27-4710-96f9-7482b70a38db · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models
Reference 1
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Observation 4cad8154-657c-4887-b5ca-0383b3fc0392 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms RouterDC: Query-based router by dual contrastive learning for assembling large language models
Reference 2
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Observation a5750fe5-467e-4bf2-9b03-e662cbbb22e9 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Gonzalez, M Waleed Kadous, and Ion Stoica
Reference 3
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Observation f5298e4d-22fd-4f33-8671-314a573eb3b0 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms IRT-router: Effective and interpretable multi-LLM routing via item response theory
Reference 4
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Observation 34fc3310-a3f9-4a3e-88d3-3d11ffb0fbd3 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Unresolved cited work
Reference 5
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Observation 6b6b67f3-361b-4640-b09f-e41923cbdac1 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Self-Consistency Improves Chain of Thought Reasoning in Language Models
Reference 6
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Observation 2e93d527-f6cd-4803-86f2-af56142c0205 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Improving Factuality and Reasoning in Language Models through Multiagent Debate
Reference 7
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Observation 1a85fe3f-d8d8-423b-948c-1ba0cd9f2529 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Debate or vote: Which yields better decisions in multi-agent large language models? InThe Thirty-ninth Annual Conference on Neural Information Processing Systems, 2025
Reference 8
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Observation c5eb0e99-7d97-4751-85f0-406f44991341 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Scalable best-of-n selection for large language models via self-certainty
Reference 9
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Observation 72d19912-9fad-46a5-80cc-79dc7b18e0d4 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Pack of LLMs: Model fusion at test-time via perplexity optimization
Reference 10
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Observation a099ca00-3b01-4e42-9df5-ec3093f17fd6 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Lambert, John Langford, Jennifer Wortman, Yiling Chen, Daniel Reeves, Yoav Shoham, and David M
Reference 11
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Observation 56419d11-a884-425a-a5ff-dcf74bb16019 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Lambert, John Langford, Jennifer Wortman Vaughan, Yiling Chen, Daniel M
Reference 12
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Observation 1f656b1b-811f-4447-a560-e90edec982a5 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Devanur, David M
Reference 13
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Observation 0a7e1272-29ff-42d9-8626-dc7763eb00ab · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Pennock, and Jennifer Wortman Vaughan
Reference 14
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Observation 3c72ebea-e59f-4b30-b6ad-119bcd3aa81e · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Harnessing Multiple Large Language Models: A Survey on LLM Ensemble
Reference 15
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Observation 19e7ec67-eb45-419f-a14b-7180b7d5221e · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms More agents is all you need.Transactions on Machine Learning Research, 2024
Reference 16
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Observation 8f596e64-fcb1-48f6-a0b9-d209a2096924 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Breaking the ceiling of the LLM community by treating token generation as a classification for ensembling
Reference 17
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Observation 03b2724d-b34b-4f09-8add-d75add9ca66f · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Language Models (Mostly) Know What They Know
Reference 18
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Observation 9249db28-de6a-4cb1-a9b0-a1a8f21a04d3 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms The internal state of an LLM knows when it’s lying
Reference 19
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Observation 96ace5ba-f525-4fbc-ae77-93d844a328e8 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Enhancing uncertainty estimation in LLMs with expectation of aggregated internal belief.Proceedings of the AAAI Conference on Artificial Intelligence, 40(40):34043–34051, Mar
Reference 20
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Observation 2a8098d3-57db-4305-bc22-a35a74ec689a · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Large language model routing with benchmark datasets
Reference 21
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Observation 5c820063-5ad4-4a98-9341-a86ad005d1c6 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Solving math word problems with process- and outcome-based feedback
Reference 22
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Observation 6e04e1d2-2ba4-4531-bd53-313b7d90db67 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms LLM-blender: Ensembling large language models with pairwise ranking and generative fusion
Reference 23
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Observation 5e407d3b-abc6-4812-a331-f002f987fade · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Let's Verify Step by Step
Reference 24
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Observation 0671b9ff-afc8-451c-8062-dafbcbab9637 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Mechanism design for large language models
Reference 25
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Observation f26b4916-9388-4add-93ef-8b94fadd0ec9 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Auctions with llm summaries
Reference 26
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Observation 48ca851b-79c4-41f7-b352-eec4a12e8fb2 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Data- driven mechanism design: Jointly eliciting preferences and information
Reference 27
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Observation 560fe664-08cf-45a9-8e74-d6777e2e4203 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Truthful aggregation of LLMs with an application to online advertising
Reference 28
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Observation 2e715a6d-a82d-4f5e-b4b2-bdb3d264e0f6 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Is your LLM outdated? a deep look at temporal generalization
Reference 29
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Observation f7b463ef-7a7c-4b95-9988-58b671b00375 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Are LLMs prescient? a continuous evaluation using daily news as the oracle
Reference 30
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Observation e0c9c84f-ce9a-4f5e-aed3-09f35d94155c · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Forecasting future world events with neural networks
Reference 31
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Observation 2202fefd-6983-47e4-a56c-5582bcd4d992 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Approaching human-level forecasting with language models
Reference 32
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Observation 888e3cb3-deff-4204-a730-de4a5e7333f9 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms ForecastQA: A question answering challenge for event forecasting with temporal text data
Reference 33
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Observation 069d5f77-a216-40da-a269-8dc3f8c26487 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Analyzing temporal complex events with large language models? a benchmark towards temporal, long context understanding
Reference 34
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Observation d18c8b32-988b-4a36-9391-a8802feb1a00 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Forecastbench: A dynamic benchmark of AI forecasting capabilities
Reference 35
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Observation 32851491-fd05-47e5-95c9-7fbf01826f02 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms OpenForecast: A large-scale open-ended event forecasting dataset
Reference 36
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Observation 498f3c86-cc5f-413e-9032-7a07a0b7f324 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms FutureX: An Advanced Live Benchmark for LLM Agents in Future Prediction
Reference 37
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Observation 786946a9-bc87-4dd5-a0e2-558771c0c6f7 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms OpenEP: Open-ended future event prediction.ACM Trans
Reference 38
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Observation a904b205-2512-4c9c-a435-9b3cffae89e2 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms LLM-as-a-prophet: Understanding predictive intelligence with prophet arena
Reference 39
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Observation 926b7cd7-74cc-4479-9e27-fa18e8868451 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Park, Rafael Valdece Sousa Bastos, and Philip E
Reference 40
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Observation 87f23c5d-86df-4919-b2c4-4de126935954 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Pennock, Chara Podimata, and Jennifer Wortman Vaughan
Reference 41
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Observation a3d8a42a-b6e4-4d9b-a4c8-3bc884729de4 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms A market for trading forecasts: A wagering mechanism.International Journal of Forecasting, 40(1):142–159, 2024
Reference 42
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Observation cca3d90c-6b20-4bcb-9284-01554d07f217 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Frongillo
Reference 43
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Observation 12f25b09-55a9-4b0f-9fcc-479bc1d86607 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Unresolved cited work
Reference 44
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Observation ad9f9da5-9008-4943-8932-81e4055f6532 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Interpreting prediction markets: a stochastic approach
Reference 45
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Observation 81a4c6c0-e871-46a1-a639-253097e070e2 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Efficient market making via convex optimization, and a connection to online learning.ACM Transactions on Economics and Computation, 1 (2), 2013
Reference 46
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Observation 2174f314-af59-40eb-8077-f5b023295dd0 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Multi-period trading prediction markets with connections to machine learning
Reference 47
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Observation 6ced80d0-79fc-425f-965c-1a28958005ce · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Unresolved cited work
Reference 48
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Observation 0148de12-db20-4601-8620-1201bd337e5d · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Strictly proper scoring rules, prediction, and estimation
Reference 49
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Observation 3e40c2f3-adeb-4c66-bc0e-5761cffd5ffe · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Bayesian model averaging: a tutorial.Statistical science, 14(4):382–417, 1999
Reference 50
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Observation d90c41e9-de33-4b95-a236-0b1defb5479f · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms A Characterization Theorem for Externally Bayesian Groups.The Annals of Statistics, 12(3):1100 – 1105, 1984
Reference 51
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Observation d7a3dc98-bbc4-480f-810a-dc7678eab862 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Gemma 2: Improving Open Language Models at a Practical Size
Reference 52
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Observation 510e53ea-4bf0-4758-92f1-edca7ab0473d · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms The Llama 3 Herd of Models
Reference 53
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Observation 06bb4ff5-59db-4ab6-946a-8a01da8b9092 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Aloe: A Family of Fine-tuned Open Healthcare LLMs
Reference 54
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Observation a09f3e7b-7a08-48c3-a6ff-1f5e66247fdb · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms BioMistral: A collection of open-source pretrained large language models for medical domains
Reference 55
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Observation 7a5800a0-6094-4502-815d-9ee245ade7ec · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms PubMedQA: A dataset for biomedical research question answering
Reference 56
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Observation 36e9c08d-cb0a-4026-b77a-d62328c21973 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms MedMCQA: A large-scale multi- subject multi-choice dataset for medical domain question answering
Reference 57
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Observation 267699d5-3a3f-4294-b124-0156698323e2 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Measuring massive multitask language understanding
Reference 58
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Observation 1e247864-32a2-4009-9fd0-6f46e5547c4d · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
Reference 59
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Observation 05cc256b-1dfd-4069-bcc3-264758f2eca7 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Calibrating language models with adaptive temperature scaling
Reference 60
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Observation fdb77dc4-3d72-48c9-ac4f-ba93be775725 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms Improving cooperation in language games with bayesian inference and the cognitive hierarchy
Reference 61
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Observation 4f7564fe-ca8c-43c9-9778-332ab5ab656c · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms The multiplicative weights update method: a meta- algorithm and applications.Theory of Computing, 8(6):121–164, 2012
Reference 62
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Observation 13d504cf-7af9-4413-b850-f39726b9b777 · outbound
Decentralized Aggregation of LLM Predictions via Wagering Mechanisms yes,” “no,
Reference 63
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No inbound Pith citation observations are available.