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HindSearch: Trajectory-Level Hindsight Critique for Search-Augmented Reinforcement Learning

简体中文

Core-mechanism mini-suite. Executes the search-trajectory hindsight operator. A small deterministic evaluation does not reproduce the full paper.

Paper information

Field Details
Paper arXiv 2608.01597
Organization Santa Clara University
First public release 2026-08-03 (arXiv v1)
Authors' code https://anonymous.4open.science/r/hindsearch-anon-EBDC
Adapter / method hindsearch
Local reproduction code src/auto_research/agent_research/latest_20260809.py

Original paper

Motivation and method

Topic: hindsight for search trajectories. A frozen judge uses gold answers to write trajectory-level critiques for failed searches. Sparse success/failure becomes auxiliary on-policy distillation, combined with GRPO.

Architecture

flowchart LR
    N0["Search rollouts"] --> N1
    N1["Final verifier"] --> N2
    N2["Failed trajectory"] --> N3
    N3["Gold-aware critique"] --> N4
    N4["GRPO and distillation"]

Key figure from the paper

HindSearch: Trajectory-Level Hindsight Critique for Search-Augmented Reinforcement Learning — Figure 2

Figure 2: Training flow and key optimization steps. From the original paper; copyright remains with the authors.

Core equation

\(\mathcal L=\mathcal L_{GRPO}+\lambda\mathcal L_{distill}(\pi_\theta,\text{critique})\).

Paper results

The paper reports consistent gains on search-augmented reasoning under its protocol. Local experiments do not present a gold-aware judge as deployed capability.

Local reproduction

See the stable metrics. Checkpoints and raw run directories are not committed.

auto-research agent-research --method hindsearch --benchmark planbench-mini --episodes 120 --seed 42

Local comparison: Compare HindSearch with a control without the mechanism in the same public mini-suite. Report only local artifact metrics; large-model and real-environment paper results are not local gains.

Reproduction boundaries

  • Implements the paper-specific state, credit, or selection operator, not merely a renamed method.
  • No original large model, proprietary environment, or expensive judge was run; these are not marked integrated.
  • HindSearch participates in unified evolve candidate discovery. Composed genomes remain subject to public evaluation and budget constraints.