Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-07-11T09:38:44.568685Z
Paper Citation Record · LEDGER
As of 14 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 2 inbound Pith citation observations for arXiv:2607.05046.
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 2026-07-11T09:38:44.568685Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T18:08:21.473999Z
A source-named dated measurement, never combined with another source.
Source: cited_works
37 of 37 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation ee6e8239-a555-4645-a335-e290ca5af5fd · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Prediction-powered inference.Science, 382(6671):669–674, 2023
Reference 1
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Observation 9b4f31b6-3762-481e-a4b7-fad3765f6c9f · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion PPI++: Efficient Prediction-Powered Inference
Reference 2
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Observation be2e3506-c2fc-4221-8876-210ce47a74a4 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Cost-Optimal Active AI Model Evaluation
Reference 3
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Observation d371683d-e1a6-4b45-bb45-8b4857c73394 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Pythia: A suite for analyzing large language models across training and scaling
Reference 4
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Observation 8199bf4f-c6f3-4619-a026-83f5c73abe93 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models
Reference 5
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Observation 0afdce97-1a9b-4ac9-a09c-ac810dbd5070 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion AutoEval Done Right: Using Synthetic Data for Model Evaluation
Reference 6
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Observation 76512655-8e38-49eb-a3af-f1b69383252b · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Prediction- powered ranking of large language models
Reference 7
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Observation 7503b542-aac3-458a-80bf-a91ebbf0811c · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Unresolved cited work
Reference 8
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Observation 55fa8252-edae-4ca2-a148-8c31a00822a5 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion WMT24++: Expanding the language coverage of WMT24 to 55 languages & dialects
Reference 9
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Observation 9aba35cc-b374-47e7-a9e3-23f33ef68b6d · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion ISBN 979-8-89176-256-5
Reference 10
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Observation 6bd22a3e-36df-4bbc-8a8a-b8c582db8871 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Alex Hofer, Bhuwan Dhingra, Amir Globerson, and William W
Reference 11
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Observation 6a243a6d-20e9-42fc-8827-2761071f6ab1 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Can Unconfident LLM Annotations Be Used for Confident Conclusions?
Reference 12
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Observation 0370cbdf-98d8-4cfc-bfe3-cb9bc0f1b549 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Olmo: Accelerating the science of language models
Reference 13
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Observation 6e3e85ee-9fed-4849-bc68-bd8eeb72f474 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Measuring Massive Multitask Language Understanding
Reference 14
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Observation b3334b36-6038-4fdd-a87c-9ab1cd4c38c4 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Unresolved cited work
Reference 15
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Observation 110d7b0f-8dc6-4174-940f-fd21bd54dda9 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion SWE-bench: Can language models resolve real-world github issues? InThe Twelfth International Conference on Learning Representations, 2024
Reference 16
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Observation 5099a01d-3c86-4a8a-98b6-df9c475090cb · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion MetricX-24: The Google submission to the WMT 2024 metrics shared task
Reference 17
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Observation 85524a48-99f5-4ebc-9471-bba80e90b4ff · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Schulze Buschoff, and Eric Schulz
Reference 18
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Observation 14f2a2f7-6923-4fb8-af7c-457cd7089a34 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Hashimoto
Reference 19
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Observation 1cbae9d5-e679-4250-af8f-a74275fc6ec4 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion LLM360: Towards Fully Transparent Open-Source LLMs
Reference 20
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Observation 37d2254b-2d91-4067-b330-26975a3278ec · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion LLM360 K2: Building a 65B 360-Open-Source Large Language Model from Scratch
Reference 21
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Observation 718b6d60-243e-498b-b22f-7feb346fa610 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion tinyBenchmarks: evaluating LLMs with fewer examples
Reference 22
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Observation 20693ff7-817a-4148-a283-415ad68ad40e · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Unresolved cited work
Reference 23
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Observation 4f83792d-34d7-4869-abcd-ec99aa264564 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Rich insights from cheap signals: Efficient evaluations via tensor factorization.arXiv preprint arXiv:2603.02029, 2026
Reference 24
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Observation 0f7e8fb6-3f15-4d90-b702-972713cba68a · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Item response theory in ai: Analysing machine learning classifiers at the instance level
Reference 25
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Observation fa2248b8-1ae9-40c8-919f-a0c1375a434f · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Spectral regularization algorithms for learning large incomplete matrices.Journal of Machine Learning Research, 11(80):2287–2322, 2010
Reference 26
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Observation 5dc8a9fd-4260-400c-81a5-bb59980b421b · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion 2 OLMo 2 Furious
Reference 27
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Observation 2de3510d-d014-4691-a03b-bc3fd55706e3 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion You don’t need to run every eval, 2026
Reference 28
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Observation d8ecda5b-3b5d-416e-8d88-4fed4a6ba198 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Unresolved cited work
Reference 29
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Observation 17ccc8fc-b4a2-4191-9cab-a4f68ef7ff72 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Lalor, Robin Jia, and Jordan Boyd-Graber
Reference 30
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Observation 0ce38cd9-04ca-4238-b050-991533acf57c · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Missing value estimation methods for dna microarrays
Reference 31
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Observation f15d79b8-bac1-42c5-afd2-29ccf8a163b6 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Anchor points: Benchmark- ing models with much fewer examples
Reference 32
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Observation 0c347fb9-8008-487b-9d6b-fa8c8ae999a6 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion doi: 10.18653/v1/2024.eacl-long.95
Reference 33
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Observation 83723642-977d-46eb-a9fc-e0ba118d374a · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion How predictable are large language model capabilities? a case study on BIG-bench
Reference 34
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Observation 039ad392-d0be-4578-af57-d52281d244d8 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion Collaborative performance prediction for large language models
Reference 35
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Observation 753df974-f078-4927-8ddb-57e31fd8d0a3 · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion On speeding up language model evaluation
Reference 36
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Observation 206bc132-e769-43c5-a55e-49631af956fa · outbound
CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion power tuning
Reference 37
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Observation ce0c4fc5-f706-427d-809b-790d6c5acc41 · inbound
Efficient Sequential Evaluation of Large Language Models CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion
Reference 24
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Observation f1075e93-4eab-403b-bb71-6bb7527ea992 · inbound
BayesAME: Bayesian Active Model Evaluation CollabEval: Statistically Efficient Collaborative Model Evaluation via Matrix Completion
Reference 2018
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