Microsoft collaboration TRACE tackles credit assignment for long-horizon agents
SharonYixuanLi · x · 2026-07-21
Core idea
Outcome-based RL works reasonably well when the task is short and the final answer is easy to verify, but it breaks down for long-horizon agents that may take dozens or hundreds of tool actions before producing an output.
What TRACE does
TRACE (Turn-level Reward Assignment via Credit Estimation) aims to assign rewards at the turn level without:
- process labels
- trained critics
- Monte Carlo continuations
- strong LLM judges
The paper argues that credit assignment, not just scaling, is the real bottleneck for long-horizon agentic tasks.
Why it matters
The work suggests that if agents are going to handle long workflows reliably, reward design will likely need to move beyond a single final outcome signal and toward more direct per-turn supervision.
Related event: TRACE: A New Credit Assignment Method for Long-Horizon Agents(3 posts)→
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