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  1. Home
  2. Signal Canvas
  3. Demystifying Reinforcement Learning for Long-Horizon Tool-Us
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Demystifying Reinforcement Learning for Long-Horizon Tool-Using Agents: A Comprehensive Recipe

Fresh1d ago
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Viability
0.0/10

Compared to this week’s papers

Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 0

Proof: pending

Distribution: unknown

Source paper: Demystifying Reinforcement Learning for Long-Horizon Tool-Using Agents: A Comprehensive Recipe

PDF: https://arxiv.org/pdf/2603.21972v1

Repository: https://github.com/WxxShirley/Agent-STAR

First buyer signal: unknown

Distribution channel: unknown

Last proof check: 2026-03-24T21:26:51.890779+00:00

Starting…

Dimensions overall score 7.0

GitHub Code Pulse

Stars
15
Health
C
Last commit
3/24/2026
Forks
0
Open repository

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Score 5.0down
Prior Work
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Score 7.0stable
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Prior Work
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Score 7.0stable
Higher Viability
RetroAgent: From Solving to Evolving via Retrospective Dual Intrinsic Feedback
Score 8.0up
Competing Approach
ToolRLA: Fine-Grained Reward Decomposition for Tool-Integrated Reinforcement Learning Alignment in Domain-Specific Agents
Score 7.0stable
Competing Approach
From Self-Evolving Synthetic Data to Verifiable-Reward RL: Post-Training Multi-turn Interactive Tool-Using Agents
Score 3.0down
Competing Approach
Scaling Agentic Capabilities, Not Context: Efficient Reinforcement Finetuning for Large Toolspaces
Score 7.0stable

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