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  3. KnowRL: Boosting LLM Reasoning via Reinforcement Learning wi
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KnowRL: Boosting LLM Reasoning via Reinforcement Learning with Minimal-Sufficient Knowledge Guidance

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Evidence Receipt

Freshness: 2026-04-15T16:46:45.033392+00:00

Claims: 0

References: 0

Proof: unverified

Freshness: fresh

Source paper: KnowRL: Boosting LLM Reasoning via Reinforcement Learning with Minimal-Sufficient Knowledge Guidance

PDF: https://arxiv.org/pdf/2604.12627v1

Repository: https://github.com/Hasuer/KnowRL

Source count: 4

Coverage: 67%

Last proof check: 2026-04-15T16:58:09.865Z

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Paper Mode

KnowRL: Boosting LLM Reasoning via Reinforcement Learning with Minimal-Sufficient Knowledge Guidance

Overall score: 8/10
Lineage: 8f03eb757515…
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Canonical Paper Receipt

Last verification: 2026-04-15T16:58:09.865Z

Freshness: fresh

Proof: unverified

Repo: active

References: 0

Sources: 4

Coverage: 67%

Missingness
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Starting…

Dimensions overall score 8.0

GitHub Code Pulse

Stars
42
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Last commit
4/15/2026
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Keep exploring

Builds On This
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Score 5.0down
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ContextRL: Enhancing MLLM's Knowledge Discovery Efficiency with Context-Augmented RL
Score 5.0down
Builds On This
KG-Reasoner: A Reinforced Model for End-to-End Multi-Hop Knowledge Graph Reasoning
Score 7.0down
Builds On This
Less Noise, More Voice: Reinforcement Learning for Reasoning via Instruction Purification
Score 2.0down
Builds On This
Detecting RLVR Training Data via Structural Convergence of Reasoning
Score 5.0down
Prior Work
Cog-DRIFT: Exploration on Adaptively Reformulated Instances Enables Learning from Hard Reasoning Problems
Score 8.0stable
Competing Approach
RefineRL: Advancing Competitive Programming with Self-Refinement Reinforcement Learning
Score 8.0stable
Competing Approach
KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning
Score 8.0stable

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Related Resources

  • What are the emerging techniques for improving LLM reasoning beyond simple pattern matching?(question)
  • How do LLM reasoning traces contribute to more transparent and auditable AI systems?(question)
  • How can understanding LLM reasoning traces lead to more trustworthy AI assistants in customer service?(question)

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