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Paper Citation Record · LEDGER

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models

As of 11 August 2026, this Paper Citation Record lists 48 of 48 outbound references and 0 inbound Pith citation observations for arXiv:2607.28077.

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

pith.paper-citation-record.v1
2607.28077 v1

Coverage vector

measured 48 of 48 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T18:34:16.916502Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

48 of 48 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved48
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ee94d858-5421-4682-82c3-a23559e4b9df · outbound

This paper cites Tulu 3: Pushing Frontiers in Open Language Model Post-Training.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Tulu 3: Pushing Frontiers in Open Language Model Post-Training

Reference 1

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no resolver link, observed 2026-07-31T18:34:16.344258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T18:34:16.344258Z digest=sha256:7664aedb50cf35f0c30a31a075f961fa21bd389d81d6b91b5e495e6c272d8536

Observation 7df2fb86-6cf9-48a0-be5c-c82780243a82 · outbound

This paper cites Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Reinforcement Learning with Verifiable Rewards Implicitly Incentivizes Correct Reasoning in Base LLMs

Reference 2

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no resolver link, observed 2026-07-31T18:34:16.348704Z

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source=arxiv_source observed=2026-07-31T18:34:16.348704Z digest=sha256:0a1c63a209a783dd612395184329691738435deac66416569a08f667106ac438

Observation a32c7b37-bee2-4c78-b8b6-24cef68e4dd4 · outbound

This paper cites Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning

Reference 3

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no resolver link, observed 2026-07-31T18:34:16.352742Z

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source=arxiv_source observed=2026-07-31T18:34:16.352742Z digest=sha256:ecc2d00b4d97426ce3be70de479048bc6deace7d8fd9e174c51e2baa462e32a0

Observation 6c9463d0-7674-4b14-a9dd-f3bc26f16570 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 4

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no resolver link, observed 2026-07-31T18:34:16.356595Z

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source=arxiv_source observed=2026-07-31T18:34:16.356595Z digest=sha256:12b4df4e2679681f2e717dea3b782a140817e1f27c4dde96f57ebe73f9e38bb4

Observation 14aee6da-2da9-4fad-91bb-3113ae3993e0 · outbound

This paper cites Solving math word problems with process- and outcome-based feedback.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Solving math word problems with process- and outcome-based feedback

Reference 5

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source=arxiv_source observed=2026-07-31T18:34:16.360171Z digest=sha256:0fae1d76d4098dd1f316e61c606a13b69b67c1aaad68f2fb4a9a5f6e76a656ca

Observation 1c56aa36-1193-47d7-a31f-bd1ee28bc587 · outbound

This paper cites International Conference on Learning Representations , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models International Conference on Learning Representations , volume=

Reference 6

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no resolver link, observed 2026-07-31T18:34:16.363889Z

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source=arxiv_source observed=2026-07-31T18:34:16.363889Z digest=sha256:ef3630eed73732dec003e759c2fb9784758437f8318cd1863c455f90a8b17809

Observation d84a5a00-0ef7-40d7-b9ed-d1377835d834 · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 7

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no resolver link, observed 2026-07-31T18:34:16.367599Z

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source=arxiv_source observed=2026-07-31T18:34:16.367599Z digest=sha256:68cc014589f87be3ec314df26672e8fc6adf519734eba782b128b9837988f365

Observation 9372ce85-4062-47f9-95b9-5cf3c9ee8cf9 · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 8

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no resolver link, observed 2026-07-31T18:34:16.370624Z

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source=arxiv_source observed=2026-07-31T18:34:16.370624Z digest=sha256:e1292b76f08ba6e73271010ad4d2a2ea84570b6f79465a3b1585a2e529df64a0

Observation 0eb60f74-2525-4ca9-8c0b-e77632b6d78e · outbound

This paper cites arXiv preprint arXiv:2503.17287 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2503.17287 , year=

Reference 9

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no resolver link, observed 2026-07-31T18:34:16.374288Z

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source=arxiv_source observed=2026-07-31T18:34:16.374288Z digest=sha256:e28860b70690e15b7ce8b3e00b4283a6dad0e801778340b40d5e5f892bca756a

Observation ca37b690-4ceb-4e53-ae49-edde598012af · outbound

This paper cites arXiv preprint arXiv:2506.06632 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2506.06632 , year=

Reference 10

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no resolver link, observed 2026-07-31T18:34:16.377439Z

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source=arxiv_source observed=2026-07-31T18:34:16.377439Z digest=sha256:53b27f8f81c47a1fb193d8187bb376732efef79008a9639116459c1f089cdd1f

Observation 0a8a76b7-c856-4144-b28d-37faf4bdbd3d · outbound

This paper cites Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 11

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no resolver link, observed 2026-07-31T18:34:16.380404Z

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source=arxiv_source observed=2026-07-31T18:34:16.380404Z digest=sha256:e47ba3514df3f87eb9eff5f6083325146e6b90eeb953c0a24ae22d77b2905b99

Observation 289a2a56-fe04-43ac-b275-5f84b15ad33f · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 12

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no resolver link, observed 2026-07-31T18:34:16.383443Z

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source=arxiv_source observed=2026-07-31T18:34:16.383443Z digest=sha256:c31822e81e27ba1e2cdd6905206ca20f516abc721a9db7602d58ac65aad4f424

Observation 8ee3c5da-a7a6-4847-908b-478d56ff2296 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 13

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no resolver link, observed 2026-07-31T18:34:16.386473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T18:34:16.386473Z digest=sha256:88f73fdd53d8b24eb10742a0f8534ce24fbd8b6ea6b5e161712019819fac4d5e

Observation 3c403dbf-6adb-4157-a540-59103f6e1808 · outbound

This paper cites arXiv preprint arXiv:2506.09016 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2506.09016 , year=

Reference 14

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no resolver link, observed 2026-07-31T18:34:16.389401Z

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source=arxiv_source observed=2026-07-31T18:34:16.389401Z digest=sha256:e0f27fae044d3a653a6bd940e4c8e89e60b61804b07f5023668878f0139f7943

Observation fc198569-6ca4-40d5-8d9a-64be99f57b27 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 15

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no resolver link, observed 2026-07-31T18:34:16.392462Z

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source=arxiv_source observed=2026-07-31T18:34:16.392462Z digest=sha256:f46b923d9847c46f293bbbf1e28e727da644a83f3751b8eab797e23f82314586

Observation b52d8413-a148-45ad-ab34-72fe9ba1f020 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 16

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no resolver link, observed 2026-07-31T18:34:16.395533Z

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source=arxiv_source observed=2026-07-31T18:34:16.395533Z digest=sha256:7f0365a4e0d7d8ba80cafa1cf0cf343e2a5cf7e3bdc080266f6c28af48f02bfd

Observation 40a690dd-a4ba-4986-a1de-837b16f685a2 · outbound

This paper cites arXiv preprint arXiv:2510.01037 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2510.01037 , year=

Reference 17

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no resolver link, observed 2026-07-31T18:34:16.399843Z

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source=arxiv_source observed=2026-07-31T18:34:16.399843Z digest=sha256:34fc863d1d678b9be1a2ac3407a41b48c576a4f2b5f3a6cf70d25c7a7582af3e

Observation beaf8e34-ed80-4f40-b8ec-d0e3c150a4e9 · outbound

This paper cites Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V

Reference 18

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no resolver link, observed 2026-07-31T18:34:16.403482Z

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source=arxiv_source observed=2026-07-31T18:34:16.403482Z digest=sha256:d1fe1388461dc86cd662848039604f2e92e0e75986e4501d41b6cb838fa55334

Observation 7664759a-5aad-40e4-ac54-d5d99cf95034 · outbound

This paper cites arXiv preprint arXiv:2603.10887 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2603.10887 , year=

Reference 19

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no resolver link, observed 2026-07-31T18:34:16.406952Z

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source=arxiv_source observed=2026-07-31T18:34:16.406952Z digest=sha256:14d35d97ec7b2853d28a3e99804dad37dcac34ab0b148acd5eddea582a398bdd

Observation e7859ec3-bd5e-4fa9-b6e5-85bd83eb83d5 · outbound

This paper cites arXiv preprint arXiv:2505.14970 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2505.14970 , year=

Reference 20

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no resolver link, observed 2026-07-31T18:34:16.410463Z

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source=arxiv_source observed=2026-07-31T18:34:16.410463Z digest=sha256:3610ddb55d272707930fafc369fba1d618e3494b681c5543dde43da4f0ef71e5

Observation 219ee3bd-66fd-4a6e-b818-f9acd1b64784 · outbound

This paper cites How to Allocate, How to Learn? Dynamic Rollout Allocation and Advantage Modulation for Policy Optimization.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models How to Allocate, How to Learn? Dynamic Rollout Allocation and Advantage Modulation for Policy Optimization

Reference 21

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no resolver link, observed 2026-07-31T18:34:16.414029Z

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source=arxiv_source observed=2026-07-31T18:34:16.414029Z digest=sha256:5fc7d910557dd7f571bfbb3f21ce64c484eb63a3de7fc1e48dee6636221b98d8

Observation 7feb79b7-381a-45b2-a2b2-74882e15702d · outbound

This paper cites Efficient Reinforcement Finetuning via Adaptive Curriculum Learning.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Efficient Reinforcement Finetuning via Adaptive Curriculum Learning

Reference 22

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no resolver link, observed 2026-07-31T18:34:16.418758Z

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source=arxiv_source observed=2026-07-31T18:34:16.418758Z digest=sha256:1cc24d4146f71052ed41709e76a585181c4765d1aa69c690fa8cc37d98a5e2c8

Observation 86114a98-e6c7-46ad-a1dd-f63dee62c9d0 · outbound

This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 23

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no resolver link, observed 2026-07-31T18:34:16.424440Z

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source=arxiv_source observed=2026-07-31T18:34:16.424440Z digest=sha256:b808613837650d538de2178092792b38af0a6ddc5ef73f40d5580f2898661ca5

Observation e0156dd9-cc2e-4105-80e1-e627ba5dc0ad · outbound

This paper cites arXiv preprint arXiv:2510.01135 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2510.01135 , year=

Reference 24

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no resolver link, observed 2026-07-31T18:34:16.435036Z

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source=arxiv_source observed=2026-07-31T18:34:16.435036Z digest=sha256:05be65ab53fa9f85148114d87b7c067e9312e5e3424a2995deb3d79b061aeca2

Observation 4780e41a-2fbe-47f2-9259-e700ea27a6f8 · outbound

This paper cites Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Not All Rollouts are Useful: Down-Sampling Rollouts in LLM Reinforcement Learning

Reference 25

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source=arxiv_source observed=2026-07-31T18:34:16.443920Z digest=sha256:bc17f6bedc24a08b4892cdf6770095a5cba37bbd240ff67763b59ffc5c1a9321

Observation 8b97658a-80f3-4799-b633-69a077bdf0c0 · outbound

This paper cites Advances in neural information processing systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in neural information processing systems , volume=

Reference 26

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no resolver link, observed 2026-07-31T18:34:16.451751Z

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source=arxiv_source observed=2026-07-31T18:34:16.451751Z digest=sha256:5b5eb5a832b7208768063fc6ec6507669f05dcfbec0ac676c68e69dd3ebda0b0

Observation 80513b2a-6e96-44af-8c9f-329befdacf6f · outbound

This paper cites Advances in neural information processing systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in neural information processing systems , volume=

Reference 27

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no resolver link, observed 2026-07-31T18:34:16.459350Z

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source=arxiv_source observed=2026-07-31T18:34:16.459350Z digest=sha256:d3bfdc29215b0e6c9ae7c9e4014670113e9317142a83e97b538f194110a83488

Observation 384493e4-dca9-485f-8079-2331ece1a582 · outbound

This paper cites Advances in neural information processing systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in neural information processing systems , volume=

Reference 29

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no resolver link, observed 2026-07-31T18:34:16.477161Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T18:34:16.477161Z digest=sha256:10b4ce577412e48656c9879a8cde5ec097fd2eea1e6d25e59cf2645adeabef67

Observation e1a1c7b2-bb42-4c53-b45f-65048bdfc867 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 30

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no resolver link, observed 2026-07-31T18:34:16.485434Z

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source=arxiv_source observed=2026-07-31T18:34:16.485434Z digest=sha256:320b6cd2e8d0606d3b560425f44b38e826ccc1fbab7ee5c256625cb3eceb6bc7

Observation 56f891fd-6e39-4461-a27f-7c11a11c6262 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 31

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no resolver link, observed 2026-07-31T18:34:16.498285Z

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source=arxiv_source observed=2026-07-31T18:34:16.498285Z digest=sha256:aea10045e5203d5765195db231fc4b395848091cb6261ee502341b1ee76e6a59

Observation 47b79656-782f-4d0a-8482-fdd822ed018b · outbound

This paper cites Proximal Policy Optimization Algorithms.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Proximal Policy Optimization Algorithms

Reference 32

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source=arxiv_source observed=2026-07-31T18:34:16.506774Z digest=sha256:0c93924c9ad95e10a2b86d83dc1d4ba51462d29689e78357a7297a8a5c0548bb

Observation 8b18bc8a-04e0-40d8-90fe-cfa90cecffcf · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 33

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source=arxiv_source observed=2026-07-31T18:34:16.516029Z digest=sha256:dc7307932898659416f2bc7a25dba7c01af328e83b0b672e679f7b583578ae69

Observation c795dfb8-050d-491c-b845-83dfe8e78fed · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Training Verifiers to Solve Math Word Problems

Reference 34

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no resolver link, observed 2026-07-31T18:34:16.525444Z

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source=arxiv_source observed=2026-07-31T18:34:16.525444Z digest=sha256:347d74d38d4d4d6ad015b4e4bc290c1435bd04d235344858704e553468a937b5

Observation 445ec05d-b607-4226-8c34-ea1472caefe7 · outbound

This paper cites Qwen2.5-Coder Technical Report.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Qwen2.5-Coder Technical Report

Reference 35

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no resolver link, observed 2026-07-31T18:34:16.534961Z

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source=arxiv_source observed=2026-07-31T18:34:16.534961Z digest=sha256:de01f71a85b53f7c3e5e6445d2bdc4ef3f3253861bf057dd8adb6910e26b4adf

Observation c393f9dd-d3d5-4d12-8522-52f066401895 · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 36

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no resolver link, observed 2026-07-31T18:34:16.544380Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T18:34:16.544380Z digest=sha256:fe9fc9a62c8e410e3768c13b6d3bfb82c68b3dfd4886e45807be831ee417be9b

Observation 4b6df2c4-0c3e-4557-b79e-f097d6227cf0 · outbound

This paper cites Qwen2 Technical Report.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Qwen2 Technical Report

Reference 37

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no resolver link, observed 2026-07-31T18:34:16.553565Z

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source=arxiv_source observed=2026-07-31T18:34:16.553565Z digest=sha256:491d2ffb156e09252efcb4ccbd3baeee15c36763d9becab60c36be3a3ba15498

Observation 8d89896b-5cee-4170-8ded-6ee10197303b · outbound

This paper cites Proceedings of the Twentieth European Conference on Computer Systems , pages=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Proceedings of the Twentieth European Conference on Computer Systems , pages=

Reference 38

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no resolver link, observed 2026-07-31T18:34:16.562590Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T18:34:16.562590Z digest=sha256:35ad7b4b0ebb6bcbd05327f3bbf26c6937cf614daa485e9c71dfadee58be970f

Observation d5d7ce2d-c7b0-4319-a4af-eb6a78e456a0 · outbound

This paper cites Proceedings of the 29th symposium on operating systems principles , pages=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Proceedings of the 29th symposium on operating systems principles , pages=

Reference 39

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no resolver link, observed 2026-07-31T18:34:16.572044Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T18:34:16.572044Z digest=sha256:2ed2df243229b6d3caee6bb8d1f4845d59eedaf1ae20494a62c817f24fdd2b25

Observation 7a2a8dc4-e919-4e6d-b89b-6a02fa74e4af · outbound

This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Measuring Mathematical Problem Solving With the MATH Dataset

Reference 40

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no resolver link, observed 2026-07-31T18:34:16.581107Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T18:34:16.581107Z digest=sha256:84e26924adb395939e3f9a6e72b6fe61a779c1668017672302f3d181fd2a562f

Observation 89006e4d-2fee-42f2-8c76-7eb7a2fc09a3 · outbound

This paper cites Advances in neural information processing systems , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Advances in neural information processing systems , volume=

Reference 41

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no resolver link, observed 2026-07-31T18:34:16.590387Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T18:34:16.590387Z digest=sha256:5cccc4e13f3836e9a4469aea189ac836114df9e6fb7c352246f5dfb35eb13698

Observation ee8b2bc1-946f-4e64-83e3-cfecdb9b6b66 · outbound

This paper cites Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) , pages=

Reference 42

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no resolver link, observed 2026-07-31T18:34:16.599943Z

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source=arxiv_source observed=2026-07-31T18:34:16.599943Z digest=sha256:b1ab8887719e9a09f22c110acdc54d146781016465bca6af95089dc02258f3e8

Observation bb76a247-688f-4957-9cb6-daf45fedd8fc · outbound

This paper cites Hugging Face repository , volume=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Hugging Face repository , volume=

Reference 43

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no resolver link, observed 2026-07-31T18:34:16.608955Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T18:34:16.608955Z digest=sha256:9161fae7b43db8dec24fb3b11c3a863e57558c33f4daf6c69f3d9ab3107dd116

Observation 12485ec5-04ea-4473-881a-ebc797ba9586 · outbound

This paper cites arXiv preprint arXiv:2509.10625 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2509.10625 , year=

Reference 44

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no resolver link, observed 2026-07-31T18:34:16.619391Z

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source=arxiv_source observed=2026-07-31T18:34:16.619391Z digest=sha256:67f2a8059d60eb0e040666d1c3f9f4a5d45a21c92282f433689283d55a873ce8

Observation 17b49c01-62bb-4123-b649-65b6ef731d72 · outbound

This paper cites MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Reference 45

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no resolver link, observed 2026-07-31T18:34:16.684880Z

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source=arxiv_source observed=2026-07-31T18:34:16.684880Z digest=sha256:1f1275649c5aac31eb223818f2289fe1a0d3f95d96aa4d4fb414538e73eee568

Observation c168a90c-f079-443c-be8f-4ee72eb3c1e4 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 46

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no resolver link, observed 2026-07-31T18:34:16.749284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T18:34:16.749284Z digest=sha256:bd30175b252497e83f46153334557bdd26971e48a5810a64b3a8c4d254a6b5b4

Observation ea0de988-f89d-4450-b14f-dd4983d2e48f · outbound

This paper cites GPQA: A Graduate-Level Google-Proof Q&A Benchmark.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models GPQA: A Graduate-Level Google-Proof Q&A Benchmark

Reference 47

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no resolver link, observed 2026-07-31T18:34:16.817682Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T18:34:16.817682Z digest=sha256:9ee0f6c798e86ef35ad8ff9ee24e6d8ed0816f13d06c11191b7772a458428226

Observation 951ce4ef-14d2-45d6-927c-48d7333fb873 · outbound

This paper cites arXiv preprint arXiv:2509.24711 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2509.24711 , year=

Reference 48

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no resolver link, observed 2026-07-31T18:34:16.881976Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T18:34:16.881976Z digest=sha256:a3a8302bc1fd1de60000791e0adb34df5dcedafb81c9c41d2bb669c72b4550d4

Observation 8c023dc8-96d0-4b3e-bc8c-2727fa810f45 · outbound

This paper cites arXiv preprint arXiv:2510.26374 , year=.

LEEPS: Latent-Guided Explore-Exploit Prompt Sampling for Efficient RLVR in Large Language Models arXiv preprint arXiv:2510.26374 , year=

Reference 49

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no resolver link, observed 2026-07-31T18:34:16.916502Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T18:34:16.916502Z digest=sha256:facaf0437815c9dabdb74523e4daf64d18f86dff2cddb3eeb50b63def828b1fd

Pith citing papers

No inbound Pith citation observations are available.