DeepSeek-Prover-V1.5: Harnessing Proof Assistant Feedback for Reinforcement Learning and Monte-Carlo Tree Search research paper by DeepSeek, 2024

DeepSeek · Retrieval and data · Aug 15, 2024 · 229 citations · 64 upvotes · unverified

DeepSeek-Prover-V1.5 improves theorem proving by optimizing training and inference, utilizing reinforcement learning, and proposing RMaxTS for diverse proof paths, achieving state-of-the-art results on miniF2F and ProofNet benchmarks.

By Huajian Xin, Z. Z. Ren, Junxiao Song and 14 more · arXiv 2408.08152 · PDF · Code

UnverifiedHugging Face's summary; not yet checked by hand.

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About this paper

Venue: arXiv.org
Citations: 229, 29 influential · Semantic Scholar
Upvotes: 64 · Hugging Face
Lab: DeepSeek · on Companies · on breaches · on Rounds · on labs · on Leaders · on Arena · on legislations · on Paydays · on Metered · on problems · on repos · on socials · on standards · on terms

Changes

UpvotesNov 2, 2026Hugging Face upvotes rose from 63 to 64.

CitationsNov 2, 2026Influential citations rose from 28 to 29.

CitationsNov 2, 2026Citations rose from 218 to 229.

CitationsOct 12, 2026Citations rose from 210 to 218.

CitationsOct 5, 2026Citations rose from 207 to 210.

CitationsSep 25, 2026A first count of 28 influential citations.

CitationsSep 25, 2026A first count of 207 citations.

New paperSep 25, 2026Found by the weekly Hugging Face scan; not yet checked by hand.

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