Paper Citation Record · LEDGER

Towards Contamination Resistant Benchmarks

As of 17 August 2026, this Paper Citation Record lists 56 of 56 outbound references and 1 inbound Pith citation observation for arXiv:2505.08389.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.08389 v1

Coverage vector

measured 56 of 56 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:00:10.470063Z

measured 57 of 57 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T07:19:50.354875Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-20T07:23:07.041987Z

Reference resolution

56 of 56 outbound references displayed

verified exact2
verified fuzzy15
unresolved39
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 69940e1e-cddd-4802-a9de-6a158853e6e8 · outbound

This paper cites What learning algorithm is in-context learning? investigations with linear models.

Towards Contamination Resistant Benchmarks What learning algorithm is in-context learning? investigations with linear models

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.035486Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb7d25df-a325-4e73-a1b0-4198f9551556 · outbound

This paper cites The Surprising Effectiveness of Test-Time Training for Few-Shot Learning.

Towards Contamination Resistant Benchmarks The Surprising Effectiveness of Test-Time Training for Few-Shot Learning

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.060656Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 679693a7-2f00-4adf-bb6c-f512b27a3bbb · outbound

This paper cites Leak, cheat, repeat: Data contamination and evaluation malpractices in closed-source llms.

Towards Contamination Resistant Benchmarks Leak, cheat, repeat: Data contamination and evaluation malpractices in closed-source llms

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.363940Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 61240b48-40e3-4d10-b95e-e38734ebd56b · outbound

This paper cites Do, Yan Xu, and Pascale Fung.

Towards Contamination Resistant Benchmarks Do, Yan Xu, and Pascale Fung

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.106629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation da1627ff-46a5-47f4-b407-c5ffef23943e · outbound

This paper cites Managing extreme ai risks amid rapid progress.

Towards Contamination Resistant Benchmarks Managing extreme ai risks amid rapid progress

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.114432Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96c32ab6-d82b-4475-b5a9-ce0a2804a633 · outbound

This paper cites Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, et al.

Towards Contamination Resistant Benchmarks Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, et al

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.332096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a222112e-aace-4c1a-bd86-27d64ddfa00c · outbound

This paper cites Sparks of Artificial General Intelligence: Early experiments with GPT-4.

Towards Contamination Resistant Benchmarks Sparks of Artificial General Intelligence: Early experiments with GPT-4

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.135591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9afb45fe-9725-4a00-953f-ba4af404d928 · outbound

This paper cites TRUCE: Private Benchmarking to Prevent Contamination and Improve Comparative Evaluation of LLMs.

Towards Contamination Resistant Benchmarks TRUCE: Private Benchmarking to Prevent Contamination and Improve Comparative Evaluation of LLMs

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.141863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87c02f98-6247-419a-8ac1-f330f1090157 · outbound

This paper cites Palm: Scaling language modeling with pathways.

Towards Contamination Resistant Benchmarks Palm: Scaling language modeling with pathways

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.315065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9b19019a-fbde-4bf2-9906-fbb9ef6bf8e6 · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

Towards Contamination Resistant Benchmarks Scaling Instruction-Finetuned Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.164195Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a102519-49cd-4d08-8674-c0cfcf141338 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Towards Contamination Resistant Benchmarks Training Verifiers to Solve Math Word Problems

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.171454Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67c3b58c-0549-4070-9353-333d8b900a68 · outbound

This paper cites Why can GPT learn in-context? language models secretly perform gradient descent as meta-optimizers.

Towards Contamination Resistant Benchmarks Why can GPT learn in-context? language models secretly perform gradient descent as meta-optimizers

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.300322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 0db4f8e0-25b6-4f1f-ae6c-6bb1978294c1 · outbound

This paper cites Generalization or memorization: Data contamination and trustworthy evaluation for large language models.

Towards Contamination Resistant Benchmarks Generalization or memorization: Data contamination and trustworthy evaluation for large language models

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.284886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9682585c-cd52-4507-93c8-ea1ec6a6b3c6 · outbound

This paper cites The Llama 3 Herd of Models.

Towards Contamination Resistant Benchmarks The Llama 3 Herd of Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.190458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 57bfe173-e544-4f93-879f-1cadb603ae5a · outbound

This paper cites Cole, Fangyu Liu, and William W.

Towards Contamination Resistant Benchmarks Cole, Fangyu Liu, and William W

Reference 15

Resolution: verified exact; doi, observed 2026-08-15T22:00:10.787781Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 06e56a22-f3b8-4d18-943a-df202aaec5ab · outbound

This paper cites What can transformers learn in-context? A case study of simple function classes.

Towards Contamination Resistant Benchmarks What can transformers learn in-context? A case study of simple function classes

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.269783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 78704c4c-d05c-4b92-b5ac-329530667238 · outbound

This paper cites Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in chatgpt.

Towards Contamination Resistant Benchmarks Human-like intuitive behavior and reasoning biases emerged in large language models but disappeared in chatgpt

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.254168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9c551f1c-83c8-45a8-9a2d-e3c0714bbc48 · outbound

This paper cites Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias.

Towards Contamination Resistant Benchmarks Instructed to Bias: Instruction-Tuned Language Models Exhibit Emergent Cognitive Bias

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.213556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e3b71f0-7d93-4473-815c-50eda4a52d82 · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

Towards Contamination Resistant Benchmarks LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.217836Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff868702-fe1a-423e-99fa-885499a739df · outbound

This paper cites Does data contamination make a difference? insights from intentionally contaminating pre-training data for language models.

Towards Contamination Resistant Benchmarks Does data contamination make a difference? insights from intentionally contaminating pre-training data for language models

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.240666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation faa7495c-5684-4147-86ab-518b2fae3cc3 · outbound

This paper cites Large language models are zero-shot reasoners.

Towards Contamination Resistant Benchmarks Large language models are zero-shot reasoners

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.224617Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 120ad59c-f67d-498d-af83-09969a6ee94a · outbound

This paper cites Task contamination: Language models may not be few-shot anymore.

Towards Contamination Resistant Benchmarks Task contamination: Language models may not be few-shot anymore

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.263224Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c769f84a-a61c-44a5-a3c1-355cca4e40c3 · outbound

This paper cites Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource Languages.

Towards Contamination Resistant Benchmarks Language Ranker: A Metric for Quantifying LLM Performance Across High and Low-Resource Languages

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.269455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8a2aba1a-0999-4c81-b000-1a3fe0e4a1df · outbound

This paper cites an unresolved cited work.

Towards Contamination Resistant Benchmarks Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:00:11.202371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 91be474c-debb-4978-af9e-e49d7067a69e · outbound

This paper cites an unresolved cited work.

Towards Contamination Resistant Benchmarks Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:00:11.188688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation f81a0d5a-71e7-493d-802d-61f26c9b7f61 · outbound

This paper cites Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation.

Towards Contamination Resistant Benchmarks Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.289031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a828076-cf65-4803-bece-354477b49413 · outbound

This paper cites Thomas McCoy, Shunyu Yao, Dan Friedman, Mathew D.

Towards Contamination Resistant Benchmarks Thomas McCoy, Shunyu Yao, Dan Friedman, Mathew D

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.293932Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3fd22f3c-3528-4a6a-8fc5-7c039a60179a · outbound

This paper cites When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1.

Towards Contamination Resistant Benchmarks When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.298851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3fbf80f-7f20-4aa9-949e-88a247feca54 · outbound

This paper cites Sources of hallucination by large language models on inference tasks.

Towards Contamination Resistant Benchmarks Sources of hallucination by large language models on inference tasks

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.303348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 987d4032-2c32-437a-b2bd-6c8a72860bb0 · outbound

This paper cites Language Models Implement Simple Word2Vec-style Vector Arithmetic.

Towards Contamination Resistant Benchmarks Language Models Implement Simple Word2Vec-style Vector Arithmetic

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.309873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2681c611-dad7-4fec-a5f4-722a252c47b6 · outbound

This paper cites In-context learning generalizes, but not always robustly: The case of syntax.

Towards Contamination Resistant Benchmarks In-context learning generalizes, but not always robustly: The case of syntax

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.322626Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cff4232b-5ded-4a76-84dd-241b01e606b0 · outbound

This paper cites Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation.

Towards Contamination Resistant Benchmarks Self-contradictory Hallucinations of Large Language Models: Evaluation, Detection and Mitigation

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.328149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 67ed016a-5efd-4da6-bf20-2aa0df251489 · outbound

This paper cites Know what you don't know: Unanswerable questions for squad.

Towards Contamination Resistant Benchmarks Know what you don't know: Unanswerable questions for squad

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.333342Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a9af2165-f0c5-4b2d-b9ec-99c587bbab03 · outbound

This paper cites A Comprehensive Survey of Contamination Detection Methods in Large Language Models.

Towards Contamination Resistant Benchmarks A Comprehensive Survey of Contamination Detection Methods in Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.339578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29ced63f-40b0-47cb-b9c7-00ca0ccff7b5 · outbound

This paper cites Prompt programming for large language models: Beyond the few-shot paradigm.

Towards Contamination Resistant Benchmarks Prompt programming for large language models: Beyond the few-shot paradigm

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.345705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42649257-1eac-41fb-8027-bb5b2e74d59e · outbound

This paper cites A natural experiment on LLM data contamination in code generation.

Towards Contamination Resistant Benchmarks A natural experiment on LLM data contamination in code generation

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.174912Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation efe9794c-e9ff-4b6f-9d06-2e5f1528e393 · outbound

This paper cites NLP evaluation in trouble: On the need to measure LLM data contamination for each benchmark.

Towards Contamination Resistant Benchmarks NLP evaluation in trouble: On the need to measure LLM data contamination for each benchmark

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.358528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1905e593-47d4-498b-b7b1-f4089f73099e · outbound

This paper cites Language models are greedy reasoners: A systematic formal analysis of chain-of-thought.

Towards Contamination Resistant Benchmarks Language models are greedy reasoners: A systematic formal analysis of chain-of-thought

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.157774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a9aff1ad-87af-4268-86ff-04027412bfba · outbound

This paper cites an unresolved cited work.

Towards Contamination Resistant Benchmarks Unresolved cited work

Reference 39

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:00:11.145225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d874dcdd-8913-499f-9040-60253a9f8e25 · outbound

This paper cites LiveXiv -- A Multi-Modal Live Benchmark Based on Arxiv Papers Content.

Towards Contamination Resistant Benchmarks LiveXiv -- A Multi-Modal Live Benchmark Based on Arxiv Papers Content

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.374324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 206f4690-61c5-4bef-b395-d58e57f13858 · outbound

This paper cites Language models are multilingual chain-of-thought reasoners.

Towards Contamination Resistant Benchmarks Language models are multilingual chain-of-thought reasoners

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.380705Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8b42a115-268b-457f-8442-b96fa8ed7686 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Towards Contamination Resistant Benchmarks Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.385552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cd750b4-6f2e-423d-afa2-42bc77824238 · outbound

This paper cites Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.

Towards Contamination Resistant Benchmarks Beyond the imitation game: Quantifying and extrapolating the capabilities of language models

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.117221Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5405adbb-fdac-4e6b-98d9-d107edeadaeb · outbound

This paper cites an unresolved cited work.

Towards Contamination Resistant Benchmarks Unresolved cited work

Reference 44

Resolution: verified exact; doi, observed 2026-08-15T22:00:10.618573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8b42b87c-fe06-4142-b93a-bcc0cc850ca2 · outbound

This paper cites an unresolved cited work.

Towards Contamination Resistant Benchmarks Unresolved cited work

Reference 45

Resolution: unresolved; raw_fallback, observed 2026-08-15T22:00:11.100511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3d52a43f-9462-4e91-838d-1191469dd8d1 · outbound

This paper cites Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning.

Towards Contamination Resistant Benchmarks Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.410510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62cfa28b-8cf7-406a-ae08-9ff25a4369f9 · outbound

This paper cites Emergent analogical reasoning in large language models.

Towards Contamination Resistant Benchmarks Emergent analogical reasoning in large language models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.419376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b51b3e6-bd18-48c8-809c-7c2f0eb35081 · outbound

This paper cites Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus.

Towards Contamination Resistant Benchmarks Chi, Tatsunori Hashimoto, Oriol Vinyals, Percy Liang, Jeff Dean, and William Fedus

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.071915Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b6c125aa-dd19-4f26-bcaa-b743fbf0b004 · outbound

This paper cites Chi, Quoc V.

Towards Contamination Resistant Benchmarks Chi, Quoc V

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.056355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 1e998387-12eb-473e-b624-66cee9e76a4d · outbound

This paper cites LiveBench: A Challenging, Contamination-Limited LLM Benchmark.

Towards Contamination Resistant Benchmarks LiveBench: A Challenging, Contamination-Limited LLM Benchmark

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.433948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b5a4af3f-3c19-4c74-80d1-433faf371b24 · outbound

This paper cites Adaptive chameleon or stubborn sloth: Revealing the behavior of large language models in knowledge conflicts.

Towards Contamination Resistant Benchmarks Adaptive chameleon or stubborn sloth: Revealing the behavior of large language models in knowledge conflicts

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-15T22:00:11.038296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 7c7ec1f2-e068-407e-8440-e7518e97d44d · outbound

This paper cites Qwen2.5 Technical Report.

Towards Contamination Resistant Benchmarks Qwen2.5 Technical Report

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.450042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95ca64ea-383a-474a-a83e-d399c0dea817 · outbound

This paper cites A Careful Examination of Large Language Model Performance on Grade School Arithmetic.

Towards Contamination Resistant Benchmarks A Careful Examination of Large Language Model Performance on Grade School Arithmetic

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.454387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d833ab05-622d-4d38-8aed-abd04f39f60f · outbound

This paper cites How Language Model Hallucinations Can Snowball.

Towards Contamination Resistant Benchmarks How Language Model Hallucinations Can Snowball

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.460187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0c9024f9-24d6-4bf0-b6c3-8fde42d56ac7 · outbound

This paper cites Trained Transformers Learn Linear Models In-Context.

Towards Contamination Resistant Benchmarks Trained Transformers Learn Linear Models In-Context

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.464998Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff9803c0-7e34-4f03-955c-2ea6bd322445 · outbound

This paper cites Why Does ChatGPT Fall Short in Providing Truthful Answers?.

Towards Contamination Resistant Benchmarks Why Does ChatGPT Fall Short in Providing Truthful Answers?

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-15T22:00:10.470063Z

Source-reported events for the cited work

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Pith citing papers

Observation eeba85aa-00bb-43c1-af8b-210a0fb75436 · inbound

LLM Benchmark Datasets Should Be Contamination-Resistant cites this paper.

LLM Benchmark Datasets Should Be Contamination-Resistant Towards Contamination Resistant Benchmarks

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:23:07.043308Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.